In recent years, the private equity and venture capital investment landscape in India has witnessed substantial shifts. Despite a decline in the overall deal value of investments in India, the number of deals in the startups has seen a considerable increase. 

May 2024 saw Indian startups raise $657 Mn through 100 deals, up 11% month-on-month (MoM) and 25% year-on-year (YoY)., However, this growth is not without its challenges.

The Rise of Governance Concerns In Startups

The surge in investments has been accompanied by an uptick in reports of regulatory non-compliance, impropriety and operational lapses. In 2023 alone, reports emerged highlighting governance lapses in at least five sizable Indian startups operating in areas such as edtech, multi-brand car servicing, technology and commerce, partner-model hospitality, food delivery etc.

To navigate the complexities inherent in the investment landscape, it has become essential for investors to effectively employ pre-investment forensic due diligence measures.

Corporate governance-related issues not only pose challenges for the businesses themselves but can cause significant financial and reputational loss to investors and other stakeholders associated with the businesses. To navigate these complexities, a majority of investments usually go through due diligence measures, before investors deploy funds.

Why PEs and VCs Must Prioritise Pre-Investment Due Diligence

In response to the evolving risks, investment committees have started demanding thorough pre-investment forensic due diligence to be conducted for internal compliance and to identify critical risks relevant to the target’s operating model and financial performance.

A forensic due diligence enables investors to identify areas of risk and obtain answers to questions which would typically not be addressed or may remain unidentified from other types of due diligence, such as a review of financial information and operating data. This is particularly true in the case of early-stage businesses, where such information is limited and not readily available.

Identifying Red Flags In Startups: A Due Diligence Checklist

Some key risks for early-stage businesses include reputational risk, risk of unknown political exposure, governance risks – such as the sanctity of numbers, unreported related party transactions, overstatement of financial and operational performance, and risk of unknown or unreported regulatory exposure.

Some indicators that should be checked in a well-executed pre-investment forensic due diligence include:

• Ambiguity regarding the sources of seed capital
• Understanding if the founder/promoter has a pattern of excessive control, weak interpersonal skills and rejects any advice given (including that provided by partners or investors)
• Changing industry or economic conditions
• Intense recent regulatory action in the industry
• Delays in the filing of financial statements / corporate records with the relevant authorities
• Frequent changes in statutory auditors or qualified opinions of auditors
• Availing statutory audit services from audit firms with limited experience, track record and reputation
• Appointment of family members and friends in important management positions, and second-tier management personnel lacking the necessary expertise, qualifications and experience
• High attrition of newly appointed senior executives (particularly in the first two years of employment) 
• A high degree of reliance on very few customers coupled with a high volume of related-party transactions
• Disproportionate concentration of business in certain territories or regions; and
• Any governance/ethical concerns associated with past business ventures or past employment of the founder/promoter 

In addition to protecting the financial interests of investors, proactive forensic due diligence also protects investors and their stakeholders from any reputational or financial damage arising from a sunk investment. 

In a market where information on early-stage businesses can be limited, pre-investment forensic due diligence acts as a sound safeguard, offering a comprehensive understanding of potential risks. 

At such a time, staying vigilant by using thorough due diligence for decision-making, is crucial to ensure the long-term success of investments in young businesses.

The post Why Pre-Investment Due Diligence Has Become Essential For PEs & VCs appeared first on Inc42 Media.

Healthcare is one of the major contributors to India’s economic growth and has been rising at a steady pace with an influx of capital, better services, and technological innovations. However, the same cannot be said about the health insurance ecosystem as it continues to face market volatility, complexities, and ambiguity. 

Given the sector’s decentralised approach, the insurance penetration stands at a staggering low with nearly 400 Mn people failing to access health insurance.

Against this backdrop, the health insurance industry has been reinventing itself by moving the needle on technological advancements. By seeking a different approach to survive and thrive in this evolving world, the insurance sector is actively harnessing AI algorithms and is shifting the focus to a data-driven insurance underwriting process. 

The digitisation of health insurance is also being driven by government initiatives like Ayushman Bharat Health Account which is bringing uniformity to the overall process.

The development of Health Insurance 2.0 is only possible with the power of AI and data-driven insurance procedures.

Easy Customer Onboarding With An Emphasis On Advanced Data Collection 

Insurance sector has long followed conventional models which involved mostly manual processes. The pre-medical check-up which serves as the basis for insurance eligibility is no longer paper-based as modern health monitoring platforms help insurers onboard customers with a quick facial scan. 

This technology eliminates paperwork and complex procedures which in turn improves efficiency and customer satisfaction.

The previous insurance model had major setbacks in the data-first insurance landscape, which led to the emergence of AI-based facial scanners. These face scanners are capable of capturing vital health parameters like heart rate, BMI, diabetes, and others which provide insurers with detailed insights into an individual’s health profile. 

With the assessment of these vitals, one can seek out potential health risks which will enable insurers to make informed decisions about coverage, overall well-being and risk management strategies.

Improved Customer Experience Backed By Cost Effectiveness

The insurance industry has always been committed to enhancing the policyholder experience at each touchpoint. Amidst this profound revolution, health insurers leverage data-driven insights to offer a superior customer experience. 

In tandem, policyholders can benefit from customised insurance plans, proactive health management support, transparent pricing based on their actual health risks, and personalised recommendations for improving their well-being.

India’s low insurance penetration can certainly be accredited to hefty premiums and mismanagement in the claims settlement process. Having understood the insurance industry’s primary concerns, platforms that stand at the intersection of fintech and healtech are actively combining the two by helping insurers reduce claims via preventive measures and right risk assessment. 

With early identification of high-risk individuals, insurers can implement targeted intervention, thereby reducing claims costs, improving profitability, and offering cost-effective premiums to attract more customers.  

Risk Profiling And Personalised Underwriting

From an insurer’s point of view, one has to go beyond traditional risk assessment methods. By analysing collected data, insurance providers can create comprehensive risk profiles for each individual, whilst keeping in mind factors like lifestyle, genetic predispositions and current health status. This in-depth profiling helps insurers accurately assess the level of risk associated with each policyholder.

It has become possible to redesign the credit underwriting process by using AI algorithms to offer personalised underwriting based on the individual’s unique health profile. Turning a new leaf over the previous paper-based process, this personalised approach ensures fair pricing. Simultaneously, the coverage is also tailored to the specific needs and risks of each policyholder, enhancing customer satisfaction and loyalty.

Predictive Analytics Promoting Preventive Care  

Through the widespread adoption of machine learning capabilities, individuals are more than prepared to face potential health risks that might pose significant threats in the future. By analysing historical data and patterns, one can forecast the likelihood of specific medical conditions and take preventive measures accordingly.  

In fact, by identifying potential health risks early on, insurers can incentivise policyholders to adopt healthier lifestyles, participate in wellness programs, and undergo regular health screenings. 

This proactive approach to promote preventive care will be instrumental in improving overall health outcomes, whilst enabling insurers to anticipate future claims and make adjustments accordingly.   

Closing Thoughts

The move to achieve IRDAIs vision “Insurance for All” by 2047 starts by integrating technological innovations, primarily AI, data-driven solutions, and predictive analytics in a predominantly manual insurance model. 

With a cohesive blend of strategies and cross-functional collaboration between diverse players, the health insurance sector can pivot towards a more inclusive model, ensuring each household in the country is protected against unforeseen health complications.          

The post Navigating The Transformative Power Of Data-Driven Health Insurance & AI appeared first on Inc42 Media.

In an era marked by rapid technological advancements, the insurance industry is at the cusp of a significant transformation. Artificial Intelligence is at the forefront of various aspects of the industry, with fraud detection emerging as a particularly vital application. 

Fraudulent insurance claims represent one of the largest preventable losses for insurers. Despite advancements in technology, insurance fraud remains at an all-time high. 

In the United States, insurance fraud costs an estimated $308 Bn annually, which is approximately 1.5% of the GDP. Similarly, insurance fraud in India increased by 212% in 2023 compared to the previous year(Source: Deloitte). 

This dramatic rise in fraud is straining traditional fraud detection methods. Beyond significant monetary losses, both middle and high-velocity insurers face the erosion of trust and confidence among users and stakeholders.

AI technologies, including machine learning (ML), natural language processing (NLP), and computer vision, are revolutionising the way insurers approach fraud detection. These technologies enable the analysis of vast amounts of data, identification of patterns, and prediction of fraudulent activities with a high degree of accuracy. 

The need for AI to monitor fraud detection and prevention is increasing as insurance is one of the most intensive industries in the world, with billions of premiums being processed every year. 

Unlike the traditional fraud detection methods, which are based on historical data and patterns, AI can automate the claims process, reduce fraudulent claims, and identify abnormal activities that may indicate fraud as part of prevention avenues to combat it. 

How AI Is Changing The Insurance Sector And Mitigating Fraud

AI-Driven Data Analytics

Leveraging advanced analytics, artificial intelligence is transforming fraud detection in the insurance industry. AI automates the process, significantly increasing speed and accuracy. 

This is achieved through two key functionalities: Predictive detection and Natural Language Processing (NLP). 

By analysing vast quantities of historical claims data, AI establishes a baseline for normal claim behaviour. Deviations from this baseline are flagged as potential anomalies, empowering insurers to proactively investigate and mitigate fraudulent activity.

With AI-enabled fraud detection, insurers can create a critical preventive role before any fraud attempt has been made.  AI algorithms can assess risk more accurately by evaluating a wider range of variables than traditional methods and allow for better pricing of insurance policies and more accurate underwriting, reducing the likelihood of fraudulent claims being approved. 

40% of insurance organisations are highly prioritising the assignment of AI to fraud management (Source: Deloitte, Insurance Fraud Report 2023). 

Automated Claims Processing

AI also revolutionises claim processing through automation, spanning from submission to payout. Advanced algorithms swiftly verify claim details against extensive datasets, detecting discrepancies and anomalies with precision, thereby minimising human errors. 

This automation expedites the processing of legitimate claims, enhancing operational efficiency and customer satisfaction in insurance and related industries. By automating routine tasks, AI enables insurers to allocate human resources more strategically, focusing on complex cases and improving overall service quality. 

This transformation not only accelerates claim resolutions but also ensures accuracy and compliance, ultimately optimising the entire claims management process. As AI continues to evolve, its role in claim processing promises continued advancements in efficiency, speed, and customer experience across the insurance sector.

20% of claim adjusters are extensively using AI as a preventive technique against fraudulent claims. (Source: Deloitte, Insurance Fraud Report 2023)

Integration With Existing Systems

Integrating AI into existing insurance systems enables insurers to enhance operations without requiring a complete infrastructure overhaul. This seamless integration ensures that AI tools can complement legacy systems and traditional methods by incorporating modern analytics and detection tools. 

This upgrade improves overall efficiency and effectiveness in identifying and preventing fraudulent activities, thus advancing operational capabilities while leveraging existing technological investments.

Advanced Pattern Recognition

AI can leverage machine learning algorithms and Natural Language Processing (NLP) to automatically identify patterns of fraud in historical data. These algorithms can identify unusual behaviours or irregularities in claims data i.e.: In simple terms, if a claimant files multiple compensation claims with similar details across different insurers, AI can detect this type of pattern and flag it for further investigation. 

The aforementioned example can enhance the ability of insurers to evaluate behavioural patterns, identify inconsistencies, and predict fraudulent intent by comparing them against established patterns of normal behaviour. 

These deviations might include unusual filing patterns, discrepancies in reported information, or inconsistencies in the claimant’s history. NLP can identify patterns in language use that might indicate deception or inconsistency.

Predictive behaviour modelling involves using AI to predict the likelihood that a claimant has fraudulent intent. This is done by analysing various factors, including past behaviour, claim history, and demographic information. AI models can assign a risk score to each claimant based on these factors, helping insurers prioritise which claims to investigate further.

Identifying Irregularities Indicative Of Fraudulent Intent

With the help of AI one can identify irregularities that suggest fraudulent intent by continuously monitoring claims, cross-referencing data sources, and utilising geospatial analysis.

Real-Time Monitoring

AI systems can provide continuous, real-time monitoring of all submitted claims, ensuring ongoing oversight and detection of suspicious activity. This continuous surveillance allows insurers to detect unusual patterns or behaviours as they occur, rather than relying on periodic reviews. 

This quick identification process helps prevent fraudulent claims from being processed and paid out, saving the insurer time and money.

Cross-Checking Claimant Information

By verifying the information provided by the claimant with data from other sources, AI can identify inconsistencies that may indicate fraud. For example, if a claimant reports an address that does not match public records or if their employment history is inconsistent with previous claims, these irregularities can be flagged for further scrutiny. This cross-checking process ensures that all provided information aligns with verified data, reducing the risk of fraud.

Geospatial Analysis

Geospatial analysis involves using geographic information to analyse the locations related to a claim. AI can examine the location data associated with the claimant, the incident, and any involved parties. By mapping these locations, AI can identify patterns that may indicate fraudulent activity. To elaborate, if multiple claims are filed from the same geographic area in a short period, this pattern could suggest organised fraud. Geospatial analysis can help insurers spot these unlikely scenarios and investigate them further.

Future AI Capabilities

Machine learning algorithms are continuously improving, becoming more sophisticated and capable of handling complex datasets. Future advancements may involve the development of algorithms that can better understand context and nuances in data, making fraud detection more accurate and reliable. 

The adoption of AI in the Indian insurance market is growing, with many companies beginning to integrate AI tools into their operations. This includes the use of AI for customer service, risk assessment, and fraud detection. However, the level of integration varies across different companies and regions.

As AI adoption accelerates within the insurance sector, adherence to Indian regulations governing data privacy, security, and ethical AI utilisation becomes increasingly critical. Insurance companies must comply rigorously with guidelines established by regulatory bodies such as the Insurance Regulatory and Development Authority of India (IRDAI). 

Ethical considerations are paramount in the deployment of AI technologies. Insurers must ensure that AI systems operate with fairness, transparency, and impartiality. This entails implementing robust security protocols to safeguard customer data, prevent discriminatory practices, and provide clear explanations for AI-driven decisions.

The evolution of AI, machine learning, blockchain, and predictive analytics is poised to significantly impact the Indian insurance market, bolstering fraud prevention capabilities and operational efficiency. 

By embracing these advancements responsibly, the insurance industry can position itself as a leader in innovation, delivering secure and advanced services that meet the evolving needs of policyholders nationwide.

The post How AI Is Changing The Insurance Sector And Mitigating Fraud appeared first on Inc42 Media.

Social media has allowed the global village to shrink. In a country like India, where every third person has a smartphone, social media adoption rates are globally the highest. On Facebook, India boasts a user base of nearly 387 Mn people; Instagram has 362 Mn users and 462 Mn YouTube users. 

Global commentators are often quick to assign rural India a biased reputation of poverty, illiteracy, and helplessness. Anybody who has done some fieldwork would know just how warped that perception is. 50% of these social media users come from rural areas, reflecting significant digital engagement and technological advancement across the country.

The highly rapid inclusion of the Indian population into using these platforms has had a two-fold effect. On one side, social media has allowed for a more democratic dissemination of information. Some information has been lifesaving, such as guidelines on public health, digital public goods, government alerts, and more. 

But the other side of social media is where fraudsters thrive. These platforms offer you the luxury of anonymity – and that is all a fraudster needs. This pervasion of social media into people’s daily lives has also actively allowed the erosion of previously sacred elements like “privacy.” 

Social Media: A Haven For Fraudsters 

With unregulated use of social media and limited awareness of the lurking dangers, users often overshare on their social streams. It’s easy for fraudsters to scrape personal data from public profiles or just literally find it disclosed on certain social profiles. 

This data is sold to bad actors who use it to create synthetic data, conduct account takeovers of unaware victims, or directly use it to open multiple accounts. These accounts that have been hacked or taken over are called ‘money mules’ because of their role in money laundering and terror financing. 

Encrypted social media platforms have fuelled the money mule pandemic by allowing users to exchange information with little accountability. For example, Telegram’s policies of voluntary anonymity in chats have made it a fraudster’s haven, and considering 55% of India’s internet users have a Telegram account, identifying fraud rings on it is a never-ending cat-and-mouse chase. 

Some screenshots show how scraped/stolen PII data is sold over a social media platform in bulk. 

There are platforms like these where you can inject OTPs to conduct account takeovers for a mere ₹7-₹10. That’s the cheap value of an identity today. 

You must have received texts from “job recruiters” who offer money in exchange for minor tasks. Other common fraud types seen are a ‘love interest’ extorting money, citing emergencies or blackmailing.  

All these are pig butchering scams where the fraudsters build a relationship with the victim, create enough trust for the victim to increase the amount of money they invest gradually, and eventually disappear leaving the victim behind with massive losses. 

Cyber Hubs For Money Mule Recruitment 

Most of these frauds have been traced back to cyber fraud hubs operating mainly from India’s hinterland. After Jamtara gained a reputation as a global phishing centre, we hear stories of upcoming fraud centres nationwide. How are these able to sprout up with such industrial vigour? 

For instance, on paper, the villages of Jurehera and Ghamdi in Rajasthan’s Bharatpur district have an average daily income of INR 368. But what’s interesting is not on paper. Deep within their fields, you will find small concrete structures fully equipped with electricity, phones and other devices. Individuals from this village have been running sophisticated fraud scams targeting individuals nationwide, bringing their earnings up to between INR 1,000 and INR 1 Lakh on any given day.   

The motivation for the rural youth turning to fraud is easy enough to understand – easy money. Social media has provided these willing individuals with the tools they need to commit fraud on devastating scales. YouTube is flooded with videos that teach you how to use stolen data to hack accounts, create fake accounts, or conduct mass promotion abuses.  

Who Is Accountable? 

Social media platforms cannot and should not shirk away from the heavy burden on their shoulders. While social media platform spokespeople try to build confidence in their content regulation methods, data privacy laws and other necessary barriers for user protection, some gaps need to be addressed urgently. 

If content with derogatory language and hate speech is flagged, how does sensitive private information about individuals get circulated so easily?  

Historically, social media giants have shown an intent towards user protection, but let’s be practical here. These fraud rings thrive not just because of social media but because of an intricate web of actors operating locally, nationally, and globally. 

Since identity thefts have become effortless, money mule victims must be protected at the financial extraction stage.  

Most banks and fintech tackle the money mule and, consequently money laundering issue during transaction monitoring. But, that is a reactive model that seeks to get the money back once it has passed through the system. 

As experts in fraud prevention and identity decisions, we have seen the most powerful results when we can stop money mule activity even before it starts. That can only happen when there is an extra augmented layer of protection to traditional identity verification methods. So, stop before losses, not after. 

The post The Dark Side Of Social Media: How Online Scams & Money Mule Recruitment Are Exploiting India’s Digital Boom appeared first on Inc42 Media.

India Brand Equity Foundation (IBEF) rightly describes micro, small, and medium enterprises (MSMEs) as the backbone of India’s economic growth story. They play a pivotal role in driving the global economy by facilitating employment creation, fostering innovation across sectors and contributing to GDP growth. 

Today, there are ~633.9 lakh MSMEs in India. Rural areas comprise 324.9 Lakh businesses, and urban India accounts for 309 lakh businesses. Even with their nationwide presence and significant contribution to the country’s development, MSMEs face limited access to finance, lack of new-age tech solutions, inadequate infrastructure, and limited market presence. 

Digital Invoice Financing: An Innovative Solution For MSMEs

The fintech platforms addressing all these challenges with their innovative solutions are truly a blessing in disguise. To resolve the roadblocks related to capital access, they offer digital invoice financing solutions that enable MSMEs to unlock funds tied up in unpaid invoices quickly and efficiently. 

The process involves selling unpaid invoices to lenders or investors at a discount in exchange for immediate cash. This financing method includes key concepts like invoice factoring, where businesses sell their invoices outright, and invoice discounting, where they borrow against the value of their invoices. 

Fintech platforms have revolutionised this process, allowing MSMEs to upload their invoices and receive funds typically within 24-48 hours. This rapid access to capital can be a game-changer for small businesses struggling with liquidity issues. 

Benefits Of Digital Invoice Financing For Small Businesses

The benefits of digital invoice financing for MSMEs are manifold. 

Resolves Liquidity Issues

To start with, digital invoice financing resolves the cash flow issue of small businesses by providing them with immediate access to funds that would otherwise be tied up in receivables. This liquidity enables businesses to cover operational expenses, invest in growth opportunities, and avoid the pitfalls of cash flow gaps. The process ensures a shorter working capital cycle and solves problems related to a lack of liquidity of capital. 

Easy And Convenient Access To Capital 

Tech advancements are integral in making digital invoice financing accessible and convenient for small businesses. The accessibility and convenience of online platforms make the process straightforward and accessible to a broader range of businesses. 

These platforms reduce the need for extensive paperwork and offer faster processing times compared to traditional financing methods. As a result, MSMEs can self-onboard themselves on the platform and conduct transactions seamlessly without any paperwork. 

Collateral-Free Process 

Digital invoice financing enhances financial stability by allowing better management of receivables, reducing the risk of cash flow interruptions, and enabling more accurate cash flow predictions. Moreover, this financing method does not require collateral based on the business’s creditworthiness, making it more accessible to MSMEs that may lack substantial assets for securing traditional loans. 

Hence, small businesses are relieved from the pressure of delayed payments as fintech platforms assume the buyer risk for MSMEs, giving them time and financial support to continue their operations and focus on their growth and sustainability. 

Carving The Path For Long-Term Growth And Expansion

The impact of digital invoice financing on MSME growth is substantial. Increased liquidity allows these enterprises to manage their operations more efficiently, reducing the risk of delays or disruptions. Additionally, the capital can be channelled into expansion initiatives, such as entering new markets, increasing production capacity, expanding the team, or investing in new technologies. 

This infusion of funds not only supports immediate operational needs but also paves the way for long-term growth and development. Furthermore, building a positive financing track record through consistent use of digital invoice financing can enhance a business’s creditworthiness, making future financing easier to obtain. 

Strengthened relationships with suppliers and customers fostered by reliable payment capabilities, further contribute to a stable and robust business environment. 

To Conclude

Despite their important stature in India’s economic development, small businesses face several challenges, especially when it comes to aspects like access to working capital and managing cash flow. These roadblocks hinder their operational efficiency and growth potential. Fintech platforms have provided an absolute solution to this problem by offering digital invoice financing and discounting solutions. 

Invoice financing is a fast and flexible solution for small businesses to accelerate cash flow and free themselves from the liquidity trap, thereby empowering their growth. Adopting digital invoice financing can provide a competitive advantage for MSMEs. Overall, with fintech platforms’ support, small businesses can overcome all the roadblocks and embrace new opportunities to walk on the path of growth and competitiveness.

The post How Digital Invoice Financing Is Empowering India’s Small Businesses appeared first on Inc42 Media.

With the rise of the subscription economy across various business models and industries, several startups now have their valuations based on subscription charges. 

This shift marks a departure from traditional pay-per-product models to those that generate recurring revenue through subscriptions, a concept eloquently encapsulated by Aswath Damodaran’s insight on the complexities of modern valuation. 

Here, we explore how businesses and investors navigate this landscape, focussing on key metrics like Monthly Recurring Revenue (MRR) and Annual Recurring Revenue (ARR).

The Foundation Of Subscription-Based Models

Companies in a subscription economy rely on recurring revenue streams, primarily measured through MRR and ARR. These metrics provide a steady income flow and a clearer picture of a company’s financial health and potential for growth. 

Understanding these metrics is crucial for the founders and the investors, as they offer insights into revenue stability, customer retention, and long-term profitability.

Monthly Recurring Revenue (MRR)

MRR represents the total monthly income from subscriptions. It’s a snapshot of a company’s recurring revenue, providing a straightforward metric to track growth on a month-to-month basis. However, MRR can fluctuate due to seasonal changes or promotional spikes, potentially leading to overestimated revenue if used in isolation.

Annual Recurring Revenue (ARR)

ARR is derived by annualising the MRR, giving a broader view of expected yearly revenue. This metric is useful for assessing long-term financial health and making strategic decisions. ARR incorporates several components:

• • ARR from New Customers: Revenue generated from new subscriptions.
  • ARR from Renewals: Revenue from existing customers who renew their subscriptions.
  • Incremental ARR: Revenue from upgrades or add-ons.
  • ARR Losses: Revenue lost from downgrades or churn.

Key Considerations For Choosing Metrics

When deciding between MRR and ARR, businesses should consider:

• Subscription Length: ARR is ideal for businesses with long-term contracts (one year or more), whereas MRR suits models with shorter, more flexible terms.
• Business Model Complexity: ARR offers a comprehensive view, useful for complex models and long-term planning. MRR provides more immediate, granular insights.
• Investor Preferences: Investors often favour ARR for its predictability and reliability over longer periods, aiding in assessing a company’s growth potential and market positioning.

Evaluating Recurring Revenue Quality

Beyond the sheer volume of revenue, investors and stakeholders must assess the quality of recurring revenue. This involves examining gross margins, revenue costs, and growth rates.

Revenue Quality: High gross margins indicate efficient operations and potential profitability. For instance, a company with 90% gross margins is generally more attractive than one with lower margins, as it retains more revenue after covering the cost of goods sold.

Revenue Cost: This metric evaluates how much a company have to spend to generate each unit of revenue. A lower cost-to-sales ratio signifies a more efficient business. For example, spending $1 to generate $1 in ARR is better than spending $2 for the same return, with the ideal scenario being even lower acquisition costs.

Revenue Growth: Rapid revenue growth suggests a strong market position and potential for future expansion. Investors often pay willingly a premium for companies that demonstrate consistent and significant revenue growth. This indicates a higher likelihood of achieving desired valuations.

ARR Multiples In Valuation

Once recurring revenues are measured, ARR multiples are used to determine a company’s valuation. This simple yet effective approach involves dividing the company’s valuation by its ARR. For instance, a company worth $100 Mn with an ARR of $10 Mn has an ARR multiple of 10.

Balancing The Metrics

It’s important to recognise the interplay between these factors. Companies may sometimes prioritise revenue growth at the expense of revenue quality or incur higher costs to drive growth. A balanced approach, considering gross margins, acquisition costs, and growth rates, is essential for sustainable valuation.

The subscription economy offers a dynamic and profitable model for startups and established companies alike. By focussing on key metrics like MRR and ARR, and evaluating the quality and cost of revenue, businesses can achieve robust valuations. 

Investors, in turn, gain a clearer, more reliable perspective on a company’s long-term potential, making the subscription model a win-win for all stakeholders. Also, remember that ARR is only one of the methods to look at valuation.

The post Evaluating Opportunities Within A Subscription Economy appeared first on Inc42 Media.

In a shocking revelation, a massive data leak has exposed sensitive personal information of over 1.6 Mn individuals, including Indian military personnel, police officers, teachers, and railway workers. 

This breach, discovered by cybersecurity researcher Jeremiah Fowler, included biometric data, birth certificates, and employment records and was linked to the Hyderabad-based companies – ThoughtGreen Technologies and Timing Technologies. 

While this occurrence is painful, it is far from shocking. 

The database, containing 496.4 GB of unprotected data, was reportedly found available on a dark web-related Telegram group. The exposed information included facial scans, fingerprints, identifying marks such as tattoos or scars, and personal identification documents, underscoring a growing concern about the security protocols of private contractors who manage sensitive government data.

The impact of such breaches goes far beyond what was capable years ago. In the past, stolen identity would have led to the opening of fake credit cards or other relatively containable incidents. Today, a stolen identity that includes biometric data or an image with personal information is enough for threat actors to create a deep fake and sow confusion amongst personal and professional colleagues. 

This allows unauthorised personnel to gain access to classified information from private businesses and government agencies, posing a significant risk to national security.

Deepfakes even spread fear throughout southeast Asia, specifically during India’s recent Lok Sabha, during which 75% of potential voters reported being exposed to the deceitful tool. 

The Risks Of Outsourcing Cybersecurity

Governments increasingly rely on private contractors to manage and store vast amounts of sensitive data. However, this reliance comes with significant risks. Private firms often lack robust cybersecurity measures that government systems can implement. 

However, with India continuing to grow as a digital and cybersecurity powerhouse, there was hope that outsourcing the work would save taxpayers money while providing the most advanced technology possible. 

However, a breach risks infecting popular software or other malicious actions such as those seen in the other supply chain attacks which are a stark reminder of the need for stringent security measures and regular audits of third-party vendors.

Leveraging AI For Cybersecurity

Cybercrime is on the rise globally, with threat actors becoming more sophisticated in their methods. The growth of AI has further complicated the cybersecurity landscape. While AI offers powerful tools for defence, it also provides new capabilities for cybercriminals who can use it to pry and prod at a system faster than ever before until a vulnerability is found. 

What’s more, this technology can be used to automate attacks, create more convincing phishing schemes, and even develop malware that can adapt and evolve to avoid detection.

While this may sound like the ultimate nightmare scenario, this same technology offers significant advantages to cybersecurity teams. AI-driven tools can automate threat detection and response, reducing the burden on human analysts and allowing them to focus on more complex tasks. For instance, large language models (LLMs) can process and analyse vast amounts of data quickly, identifying threats in real-time and providing actionable insights.

AI can also play a crucial role in upskilling employees within cybersecurity teams. With the implementation of LLMs, even less experienced team members can make impactful decisions based on AI-driven insights. These models allow analysts to use natural language queries to gather information, eliminating the need for specialised training in various querying languages. By running queries like “Can vulnerability ‘#123’ be found anywhere in the network?” teams can quickly identify potential threats and take appropriate action.

Furthermore, AI assists in automating routine tasks, allowing cybersecurity professionals to focus on strategic initiatives. It can offer next-step recommendations based on previous actions, enhancing the decision-making process. For example, when an alert is triggered, AI can provide insights such as “This alert is typically dismissed by 90% of users” or “An event looks suspicious. Click here to investigate further.” 

This streamlines operations and accelerates the learning curve for junior analysts, allowing them to quickly become proficient in identifying and mitigating threats, thus levelling up the entire team’s capabilities.

Balancing The Scales

As it has always been in the battle between cybersecurity teams and threat actors, there is no one-size-fits-all solution that can secure all networks. However, machine-speed attacks need a machine-speed autonomous response that only AI can deliver. 

The recent data leak in India highlights the importance of robust cybersecurity measures, especially when dealing with sensitive government data. As cyber threats evolve, so too must our defences. 

By leveraging the power of AI, cybersecurity teams can remain one step ahead on the frontlines of protecting government data, digital economies, and even the complex infrastructure that keeps society functioning as it does.

The post How AI-Equipped Teams Can Save Data Leaks From Becoming The Norm For Global Powers appeared first on Inc42 Media.

In today’s fiercely competitive, data-driven marketing landscape, the pursuit of accurate customer insights is critical for businesses aiming to thrive. Customer data serves as the cornerstone of modern business strategies, offering a window into the customer’s world, encompassing a wide array of information from basic demographics to complex trends.

The evolution of consumer data reflects the changing dynamics of consumer interactions, particularly with the widespread use of internet and mobile technologies.

Real-time databases are now equipping businesses with instant insights into customer behaviour, encompassing online browsing activities, social media engagement, and even sensor data from smart devices. The value of customer data lies in its capacity to facilitate informed decision-making. 

By comprehending customer needs, wants, and pain points, companies can customise their strategies to enhance customer satisfaction and drive growth.

Mending The Existing Gaps

The value of consumer data is accompanied by challenges, particularly in terms of privacy concerns and data security. 

Regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) underscore the importance of ethical data processing, necessitating a delicate balance between insights and consumer privacy.

Here are a few areas wherein caution needs to be maintained:

Protecting First-Party Data: On this front, first-party data emerges as a pivotal asset, providing direct insights gleaned from customer interactions with the brand. While its accuracy and relevance are unmatched, companies must tackle challenges such as limited availability and compliance with data protection laws. 

Investing in a robust assessment process and transparent consent from consumers are crucial steps to harnessing the power of first-party data responsibly.

Aiming For Cookieless Marketing: In response to growing privacy concerns and regulatory amendments, the shift towards cookieless marketing presents opportunities for greater consumer confidence and compliance with privacy obligations. However, this also requires the adaptation of new and commercially viable technologies in terms of data granularity.

Traditional Survey Vs Passive Data Collection Strategies

Traditionally, consumer insight providers have relied on a variety of methods to gather information, including probability-based sampling, recall-based surveys, and traffic-based analysis. While these approaches have advantages, their drawbacks compromise their effectiveness and reliability.

Recall-based surveys are conducted among specific target groups to gather comprehensive data on consumer behaviour, preferences, and demographics. These surveys employ methodologies such as the diary method, where respondents or panel members record their responses either through Computer-Assisted Personal Interviews (CAPI) or physical diaries. Businesses gain detailed insights into their target audiences, facilitating the development of more effective marketing strategies tailored to specific consumer segments. 

This data collection method is widely adopted by major entities in the consumer insights market, such as TGI, IRS and RAM, which play a crucial role in providing comprehensive and accurate data for informed decision-making in marketing and media planning.

In addition to traditional data collection methods, passive data collection emerges as a significant approach to understanding consumer behaviour. This involves gathering data without direct interaction with consumers, often through tracking online activities, sensor data from devices, or monitoring user behaviour in digital environments. 

Companies like Comscore, VTION.AI, Data.AI  utilise passive data collection methods to provide real-time insights into consumer behaviour, without relying on self-reported data or surveys, thus offering a more accurate depiction of consumer habits and preferences.

One such passive approach is panel-based data collection used by VTION.AI, which involves recruiting groups of individuals and collecting full consent to share their online activity through an app installed on a Panel member’s phone for which they are rewarded. 

This approach allows marketers to gain detailed insights into consumer journeys, engagement levels across various Ad exposures as well as Ecom buying behaviour across NCCS, Demo and Geo.

In Conclusion

The growth of consumer data underlines the importance of responsible data practices and adaptability in a changing regulatory environment. By leveraging first-party data and embracing cookie-free marketing strategies, companies can address these challenges while creating personalised marketing campaigns and building customer trust. 

Advancements in data analytics and machine learning offer promising solutions to these challenges. By using predictive models and advanced analytics techniques, marketers can identify patterns and trends in consumer behaviour without relying on cookies. This allows for more accurate audience segmentation and targeting, improving campaign performance and ROI.

Moreover, with growing concerns about people’s privacy and data security, companies are adopting a more selective and transparent approach to gathering information to build trust among consumers.

The post Redefining Consumer Insights: Understanding Modern Data Collection Challenges & Opportunities appeared first on Inc42 Media.

ChatGPT-4o is OpenAI’s latest breakthrough in artificial intelligence.  ChatGPT-4o is the fourth version of ChatGPT, an artificial intelligence (AI) model developed by OpenAI. 

It’s designed to understand and generate human-like text based on the input it receives. ChatGPT-4o builds on previous versions by improving its ability to understand context, generate more relevant responses, and provide better interactions. 

This model, known for its advanced abilities in understanding text, audio, and visual data in real time, is a big improvement from the earlier versions. 

It’s used in various applications, such as chatbots, customer service, and content generation, to help users interact with machines more naturally and effectively.

ChatGPT-4o is set to create new benchmarks in the AI industry with its speed, efficiency, and versatility.

Key Features Of ChatGPT-4o

1. Enhanced multimodal capabilities: ChatGPT-4o can understand and generate not just text, but also audio and visual data. This allows for more complex and detailed interactions.
2. Speed and efficiency: It works at double the speed of GPT-4 Turbo and is 50% cheaper. The model can process up to 10 million tokens per minute, making it very efficient.
3. Multilingual support: Better support for non-English languages means it can be used by more people around the world.
4. Vision capabilities: Improved vision abilities help it perform better in tasks that need image understanding.

Statistics And Latest Figures

• • Accessing models: GPT-4, GPT-4 Turbo, and GPT-4o are accessible through the OpenAI API.
  • Comparison: GPT-4o is faster, cheaper, and has higher rate limits compared to GPT-4 Turbo.
  • Pricing: GPT-4o is 50% cheaper than GPT-4 Turbo, priced at $5/M input and $15/M output tokens.
  • Rate limits: GPT-4o has rate limits 5x higher than GPT-4 Turbo, up to 10 million tokens per minute.
  • Speed: GPT-4o is 2x as fast as GPT-4 Turbo.
  • Vision: GPT-4o’s vision capabilities outperform GPT-4 Turbo in evaluations.
  • Multilingual support: GPT-4o has improved support for non-English languages compared to GPT-4 Turbo.
  • Context window and knowledge cut-off: GPT-4o has a context window of 128k and a knowledge cut-off date of October 2023.
  • Availability: GPT-4o is available in the Chat Completions API, Assistants API, Batch API, supports function calling and JSON mode, and can be accessed via the Playground.
  • Payment and access: A payment of $5 or more (usage tier 1) grants access to GPT-4, GPT-4 Turbo, and GPT-4o models.
  • API request limits: ChatGPT rate limits are independent of API rate limits.
  • Data handling: Data and files passed to the OpenAI API are not used to train models unless explicitly chosen.
  • Free tier access: Free tier users default to GPT-4o with message limits.
  • Advanced tools: Free users have limited access to advanced tools like data analysis, file uploads, browsing, and vision.
  • Upgrade to Plus: Free users can upgrade to Plus for increased message limits.
  • Message caps: Plus users can send up to 80 messages every 3 hours on GPT-4o and up to 40 messages every 3 hours on GPT-4.
  • Message accumulation: Unused messages do not accumulate.
  • Enterprise plan: The ChatGPT enterprise plan offers unlimited, high-speed access to GPT-4o and GPT-4, defaulting to GPT-4o for new conversations.

How ChatGPT-4o Will Change The World Of AI

ChatGPT-4o’s arrival marks a pivotal moment in the evolution of AI. Its multimodal capabilities, speed, and cost-efficiency will significantly impact various sectors:

Workplace Automation

By processing large volumes of data quickly and accurately, ChatGPT-4o can automate routine tasks across industries. This will free up human workers to focus on more complex and creative activities, increasing productivity and innovation.

Enhanced Human-AI Collaboration

ChatGPT-4o’s ability to understand and generate text, audio, and visual data enables more natural and intuitive interactions between humans and AI. This will lead to better collaboration tools, virtual assistants, and user interfaces that can understand and respond to a wide range of inputs.

Improved Accessibility And Inclusivity

With its advanced multilingual support, ChatGPT-4o can break down language barriers, making AI tools accessible to a broader audience. This inclusivity will empower more people to leverage AI in their daily lives and work.

Innovation In Customer Service

By providing faster and more accurate responses, ChatGPT-4o will revolutionise customer support. Businesses can offer 24/7, high-quality service, leading to improved customer satisfaction and loyalty. For example, a major telecom company reported a 60% reduction in customer query resolution time after using ChatGPT-4o.

Advancements In Education And Training

ChatGPT-4o can transform educational experiences by providing real-time, personalised assistance to students. Its multimodal capabilities will enable interactive and engaging learning environments, fostering better educational outcomes. Early adopters in education reported a 35% improvement in student engagement and learning outcomes.

Revolution In Healthcare

In healthcare, ChatGPT-4o can assist in diagnosing conditions, offering personalised treatment plans, and providing real-time language translation for patient communications. ChatGPT-4o’s multimodal capabilities enable it to help in diagnosing medical conditions through image analysis, provide real-time translations for international patients, and offer personalized treatment plans based on comprehensive data analysis. This can lead to improved patient care and more efficient healthcare delivery.

Revolution In Finance

In the financial sector, ChatGPT-4o can analyze large amounts of data quickly, providing real-time insights and predictions. Financial institutions reported a 25% increase in decision-making speed and accuracy after implementing ChatGPT-4o.

Content Creation And Media

ChatGPT-4o will drive innovation in content creation by enabling the generation of high-quality text, audio, and visual content. This can lead to more immersive media experiences and higher productivity in the creative industries. For instance, a leading video game company used ChatGPT-4o to develop adaptive in-game characters, increasing player engagement. In another example, a leading media outlet increased its content output by 40% using ChatGPT-4o.

Overall, ChatGPT-4o’s advanced features and efficiency will not only enhance existing AI applications but also pave the way for new and innovative uses of AI across various fields. Its impact will be felt globally, driving significant improvements in how we work, learn, communicate, and live. 

Comparison With Other AI Models 

Google Gemini: Google Gemini focuses on integrating large language models with Google’s vast data sources. While it excels in specific areas due to Google’s large datasets, ChatGPT-4o’s multimodal capabilities offer a wider range of applications. Google Gemini’s data-centric approach is powerful, but ChatGPT-4o’s ability to handle different types of data (text, audio, visual) provides a more complete solution.

Perplexity AI: Perplexity AI is known for its question-answering system that gives concise answers. However, it lacks the depth and multimodal abilities of ChatGPT-4o, making it less versatile. Perplexity AI’s focus on text-based interactions limits its uses compared to the comprehensive abilities of ChatGPT-4o.

Microsoft Copilot: Microsoft Copilot is integrated into various Office applications, helping with productivity. ChatGPT-4o, with its wider application range beyond just productivity tools, offers more complete AI solutions. While Microsoft Copilot excels in enhancing productivity within the Microsoft ecosystem, ChatGPT-4o’s applications span many industries, from healthcare to entertainment.

In Conclusion

ChatGPT-4o stands out as a versatile, efficient, and powerful model in the AI world. Its ability to handle text, audio, and visual data seamlessly makes it suitable for transforming industries and everyday applications. 

As AI continues to grow, models like ChatGPT-4o will lead the way, driving innovation and improving user experiences across various fields.

The post How Will ChatGPT-4o Change The World Of AI? appeared first on Inc42 Media.

The exponential growth of AI applications in today’s world is not only throwing challenges and opportunities at us but also is revolutionising India’s data centre infrastructure. As AI workloads surge, data centres face extensive demands in their infrastructure challenges.

In this article, we will touch upon the cause and effect and also go on a journey to dissect the numbers behind India’s data centre boom and find reasoning for the underlying trends, opportunities and challenges shaping the industry’s trajectory.

Data Centre Potential

Historically, data centre power density has seen a remarkable evolution, from 2-4 kW in the late 1970s to over 40 KW today, driven by AI and high-performance computing workloads. Projections suggest a doubling of annual data centre loads by 2035, with India’s capacity expected to surpass 1,300 MW by 2024. 

India’s data centre industry is predicted for a steady growth, with an expected compound annual growth rate (CAGR) of 5.84%, projecting the market size to reach an estimated $9.27 Bn by 2027.

These trends offer lucrative investment opportunities for companies operating in the data centre sector. India has a whopping 759 Mn users accessing the web at least once a month predicted to reach 900 Mn by 2025. 

This kind of user base and an array of businesses bringing in innovative services and products to cater to the masses cry out loud for urgent and innovative solutions to meet these pressing demands. 

Deciphering Data Centre Growth

It is driven by various factors. 

The increasing demands of the IT sector and global capability centres (GCC) are creating a need for more advanced data infrastructure. 

The fast expansion of India’s digital economy, with an increasing number of people having access to digital learning platforms, social media, ecommerce, digital transactions, online gaming, and streaming services, is boosting the demand for reliable data storage and processing capabilities.

Post Covid-19, the ongoing shift towards hybrid work arrangements, especially in light of recent global events, is emphasising the importance of robust data centre solutions to support remote work and digital collaboration.

In summary, India’s data centre sector presents an appealing growth opportunity driven by  , digital transformation initiatives, and the evolving needs of businesses and consumers in the digital space.

Understanding And Embracing Challenges For Delivering Innovative Solutions

To handle the challenge of creating energy efficiency, industry pioneers are advocating for an approach to secure power distribution licences and prioritising energy-efficient design to achieve remarkable Power Usage Effectiveness (PUE – between 1.3 to 1.4). 

While that is impressive the challenges extend beyond power consumption. As AI-driven demands escalate, network requirements and the need for power redundancy become important, necessitating a transition from air to liquid cooling methods. Specialised cooling techniques like rear door heat exchangers become indispensable for efficient heat dissipation.

Moreover, AI’s diverse workloads introduce complexity, demanding tailored approaches to redundancy and cost-efficiency. High-reliability mechanisms and seamless power source switching become necessary to mitigate downtime risks, while operational challenges like power surges and harmonic distortions persist, mandating continuous monitoring and mitigation strategies.

Beyond infrastructure, power and cost challenges mentioned above are the data security, privacy risks, talent acquisition, and ethical concerns which are also equally important. All these concerns emphasise the holistic nature of addressing AI’s impact on data centres.

Lastly, regulatory frameworks play a pivotal role in ensuring long-term sustainability. Clear guidelines on energy efficiency and environmental standards incentivise investments in green technologies, driving positive change across the industry.

In such a scenario innovative solutions are indispensable. There is a need for data centres to innovate and offer solutions in sectors spanning power distribution, cooling, environmental monitoring, security, and scalability, offering tailored solutions to optimise performance, reduce costs, and ensure long-term reliability.

The 3 golden S’s – Sustainability, Scalability and Security are of topmost priority for data centres. Apart from this, a couple of more focus areas for data centres are:

• Adopting energy-efficient hardware,
• Adopting renewable energy sources,
• Working at a cost reduction of the infrastructure and
• Focusing on environmental sustainability. 

As India paces into this age of AI, data centres are working towards or some are already offering innovative solutions and standing strong as trusted partners, offering customisable and modular solutions.

The post Decoding India’s Data Centre Landscape: Challenges, Innovations And Future Prospects appeared first on Inc42 Media.

In recent years, a significant shift has been observed in the startup ecosystem: a move from prioritising revenue growth to focussing on profitability. 

This trend is particularly noticeable in the Indian startup landscape, where the mantra of “growth at all costs” is being replaced by sustainable and profitable business models. This article explores the reasons behind this shift, supported by real data and insights into the latest trends.

Historically, startups have been obsessed with rapid growth and scaling. 

This approach was fuelled by the belief that capturing market share quickly would lead to long-term dominance and profitability. 

Consequently, startups often focus on top-line revenue growth, sometimes at the expense of hefty losses. Investors, too, were more willing to pump money into high-growth companies, betting on future profitability once a dominant market position was secured.

The Wake-Up Call: Learning From Global Failures

Several high-profile failures and underperforming IPOs globally have served as wake-up calls for startups and investors alike. WeWork, for example, saw its valuation plummet from $47 Bn to around $8 Bn within months due to concerns over its business model and profitability. Similarly, Uber and Lyft, despite their massive revenues, continued to post significant losses post-IPO, leading to investor scepticism.

Indian Ecosystem: The Profitability Pivot

The Indian startup ecosystem, traditionally influenced by Silicon Valley’s growth-centric model, has also begun to pivot towards profitability. There are several reasons for this shift:

• Investor Pressure: Investors are becoming more discerning and cautious. They now demand clear paths to profitability before committing large sums of money. This trend is evident in the strategies of major venture capital firms and private equity players operating in India.
• Market Maturity: The Indian market has matured, and there is a growing realisation that sustainable businesses are more valuable in the long run. Startups demonstrating a clear value proposition and profitability are likelier to succeed.
• Regulatory Environment: Indian regulators have tightened corporate governance and financial transparency norms. This has pushed startups to adopt more sustainable and transparent business practices.
• Economic Factors: Economic slowdowns and uncertainties, such as those experienced during the COVID-19 pandemic, have underscored the importance of having a profitable and resilient business model. Startups heavily dependent on external funding faced severe challenges during this period.

To understand this shift better, let’s look at some data and examples from the Indian startup ecosystem:

• Zomato: India’s food delivery giant Zomato made headlines with its IPO in July 2021. Despite being loss-making, the company emphasised its path to profitability, and investors responded positively. As of early 2024, Zomato has significantly reduced its losses and is on track to break even.
• Ola: Ola, a leading ride-hailing service, has been focusing on unit economics and reducing cash burn. By cutting down on discounts and focusing on core markets, Ola has moved closer to profitability.
• BYJU’S: Edtech giant BYJU’S, while still investing heavily in growth, has made strategic acquisitions to enhance its profitability. The company has diversified its offerings and improved its revenue streams, aiming for sustainable growth.

Strategies for Achieving Profitability

Startups are employing several strategies to pivot towards profitability:

• Cost Optimisation: Reducing unnecessary expenses and optimising operations is crucial. For instance, startups are renegotiating vendor contracts, automating processes, and adopting lean methodologies.
• Revenue Diversification: Relying on multiple revenue streams helps mitigate risks. For example, fintech startups in India are expanding their services to include wealth management, insurance, and lending.
• Focus on Core Competencies: Startups are narrowing their focus to core products and services that offer the highest margins. This approach helps in better resource allocation and enhances customer satisfaction.
• Data-Driven Decision Making: Leveraging data analytics to understand customer behaviour and market trends allows startups to make informed decisions, improving profitability.
• Strategic Partnerships: Forming alliances with other companies can help in sharing costs and accessing new markets. For example, ecommerce startups partnering with logistics firms to reduce delivery costs.

Case Studies: Profitable Indian Startups

OfBusiness

OfBusiness, a fintech platform founded in 2015, provides financial solutions to small and medium enterprises (SMEs). By leveraging data analytics and modern technology, it assesses creditworthiness and offers customised financing. This approach has led to the disbursement of loans over INR 10,000 Cr to more than 10,000 SMEs across sectors like manufacturing and healthcare. Partnering with financial institutions like RBL Bank and ICICI Bank, OfBusiness has expanded its reach and achieved a market valuation of $5 Bn as of 2023​.

 Nykaa

Nykaa, founded by Falguni Nayar in 2012, has become a leading beauty and wellness brand in India. It expanded from an ecommerce platform to a chain of retail stores, known as Nykaa Luxe and Nykaa on Trend. Listed on the Indian stock exchange in 2021, Nykaa has consistently focused on profitability through a diverse product range and strategic offline expansion. As of 2023, Nykaa’s market valuation stands at $4.9 Bn​.

Gupshup

Gupshup, established in 2004 by Beerud Sheth, is a leading conversational messaging and bot-building platform. It provides automated messaging solutions to businesses across sectors like banking, insurance, and ecommerce. Gupshup’s success is driven by its ability to facilitate real-time customer interactions, enhancing engagement and customer satisfaction. With a market valuation of $1.4 Bn in 2023, Gupshup’s profitability is a testament to its innovative solutions and widespread adoption​.

Zerodha

Zerodha, India’s largest retail stockbroker, is a prime example of a startup that prioritised profitability from the beginning. Founded in 2010, Zerodha focused on a low-cost, technology-driven model, which allowed it to offer competitive pricing while maintaining healthy profit margins. By avoiding the high-burn strategies of other fintech firms, Zerodha has been consistently profitable, earning the trust of investors and customers alike.

Benefits Of Focusing On Profitability

Startups focusing on profitability over mere revenue growth experience several benefits:

1. Investor Confidence: Profitable startups attract more discerning investors who seek sustainable business models.
2. Market Stability: Profitability ensures better resilience against economic downturns and market fluctuations.
3. Operational Efficiency: Prioritising profitability encourages startups to optimise costs and streamline operations.
4. Long-term Success: Sustainable profitability aligns with long-term business goals, ensuring steady growth and stability.

The Future Of Indian Startups

The shift towards profitability is expected to continue, driven by both market dynamics and investor expectations. Startups that can demonstrate a clear path to profitability are more likely to secure funding and achieve long-term success. This trend will lead to a more resilient and sustainable startup ecosystem in India.

In conclusion, the focus on profitability over revenue growth marks a significant and positive change in the startup landscape. By building sustainable and profitable businesses, Indian startups are not only ensuring their own survival but also contributing to the overall economic growth and stability of the country. This trend, backed by real data and strategic insights, sets the stage for a more mature and balanced entrepreneurial ecosystem in India.

The post The Shift from Revenue To Profit: Why Startups Are Prioritising Profitability Over Growth appeared first on Inc42 Media.

Creating an Employee Stock Ownership Plan (ESOP) is a strategic move for any company, especially within the startup ecosystem. An ESOP not only serves as a powerful tool to reward, attract, and retain talent but also aligns employees’ interests with the organisation’s success, fostering a sense of ownership and commitment among the workforce. 

Unlike direct stock ownership, an ESOP is a plan that outlines how, when, and under what circumstances employees can acquire actual shares in the company. 

It is not an immediate grant of stock but rather a structured path towards stock ownership, typically involving a long vesting period. This deferred allocation can be beneficial for managing the stock pool effectively, but it also requires careful planning to avoid unnecessary complications.

The timing of creating an ESOP is crucial and can have significant implications for both the founders and the investors. This article delves into the optimal timing for establishing ESOPs and the considerations that entrepreneurs should bear in mind.

The Early Investment Phase

At the early stages of a startup, entrepreneurs often raise initial investments from friends, family, and angel investors. At this point, there is typically less emphasis on ESOPs, as the primary focus is on securing capital to get the business off the ground. However, this can lead to challenges down the road when the company seeks institutional investment.

The Institutional Investment Phase

As startups grow and move towards raising institutional investments, the need for an allocated pool of stock for ESOPs becomes more pressing. Institutional investors usually place a strong emphasis on having a well-defined ESOP plan in place. 

However, creating a stock pool post-investment can lead to dilution issues. When new stock pools are created after initial investments, it dilutes the stakes of both founders and early investors proportionately. 

This additional dilution, even as small as 0.8%, can lead to delays, pushbacks, and extended negotiations, complicating the investment process.

The Preferred Approach

To avoid the complications of post-investment dilution, entrepreneurs should allocate the stock pool for ESOPs right from the beginning. Even if the ESOP is not immediately granted, having a pre-allocated pool can prevent the dilution issues that arise later. It will help streamline the process of securing institutional investment.

Where the stock pool is allocated from the outset, founders maintain their stake, and investors benefit from holding a larger portion of equity. Both founders and investors generally prefer this scenario as it avoids the additional dilution and the associated challenges.

Takeaway

Scenario 2 is a preferred choice for founders and Investors. Founders tend to maintain the same stake in both scenarios while investors benefit in terms of holding. 

Important Considerations For Entrepreneurs:

When setting up an ESOP, there are several critical considerations:

SHA Clauses

Under the Shareholders’ Agreement (SHA), there is often no mention of the treatment for the unallocated portion of the ESOP stock pool. Typically, any unallocated shares are proportionately distributed among all shareholders, which can disadvantage founders who initially diluted their stakes to create the pool. 

To address this, founders can include a “plough back of unallocated ESOP” clause in the SHA. This clause ensures that any unallocated ESOP shares revert to the founders, preserving their benefits.

Illustration: The Impact of Plough Back Clause

Assume no ESOP is allocated, and a trigger event requires the calculation of stakes on an as-if-converted basis. Without the Plough Back clause, the unallocated ESOP shares’ benefits are proportionately distributed among all shareholders. With the clause, the founders reclaim these benefits, thus preserving their original intent and stake.

Other key considerations include:

• Regulatory Compliance: Ensuring that all legal and regulatory requirements are met is crucial. Entrepreneurs should work with advisors and legal experts to maintain regulatory hygiene.
• Policy Creation: Developing a clear and transparent ESOP policy is essential. This includes defining the vesting schedule, eligibility criteria, and the process for exercising stock options.
• Investor Relations: It is important to communicate with investors about the ESOP plan and its benefits. This helps in gaining their support and avoiding conflicts later.

Conclusion

Creating an ESOP is a strategic decision that requires careful planning and timing. By allocating the ESOP stock pool from the beginning, entrepreneurs can avoid the pitfalls of post-investment dilution and ensure a smoother path to securing institutional investment. 

Additionally, including protective clauses in the SHA and focusing on regulatory compliance and clear policy creation can further strengthen the ESOP framework. 

With the right approach, ESOPs can significantly enhance a startup’s ability to attract, retain, and motivate top talent, ultimately driving the company’s success.

The post When Is The Right Time To Create ESOPs? appeared first on Inc42 Media.

Venture Capital (VC) has become a captivating force in the financial world. The fuel ignites groundbreaking startups, reshaping industries like ecommerce, fintech, edtech, and consumer tech among several others. 

Once a niche asset class, VC is now a driving force behind India’s booming entrepreneurial ecosystem. Indian startups raised staggering $42 Bn in 2021, according to Inc42’s “Indian Tech Startup Funding Report 2023”. Although funding winter and market correction dropped the funding levels to $25 Bn in 2022 and $10 Bn in 2023, India continued to maintain its position at the top three global startup ecosystems

This influx of capital has blurred the lines between VC and other private equity investments, attracting a more comprehensive range of market participants. However, as the VC landscape evolves, navigating its inherent risks requires strategic diversification and a prudent approach.

The High-Stakes Game: Unveiling VC Returns

The allure of VC lies in its potential for outsized returns. Stories of billion-dollar “unicorns” capture the imagination, hinting at the possibility of turning a modest investment into a fortune. 

But behind the glitz lies the reality – VC is a high-risk, high-reward game. Studies show a significant portion of VC investments underperform, with only a select few delivering those headline-grabbing returns. 

According to McKinsey’s review of private markets, VC funds saw a meagre 3% return through September 2023, experiencing negative returns for seven consecutive quarters. 

This data dashes the myth that VC is a guaranteed path to riches. Historically, VC returns haven’t consistently outperformed public markets, highlighting the importance of a well-constructed portfolio.

Finding Home Runs: Science Vs. Art Or A Collaborative Dance?

Within the VC community, two distinct philosophies guide investment decisions. The first is the scientific approach, advocating for investing in many startups based on probability. The logic is that a sizeable portfolio increases the odds of finding a “unicorn.” However, research suggests diminishing returns with this volume-based strategy.

On the other hand, the art-based approach emphasises classic venture investing principles. It identifies startups with strong teams, large addressable markets, clear scalability, a sustainable competitive edge, and perfect timing. Quality trumps quantity, and deep engagement and support can significantly enhance the success odds of promising companies.

These philosophies aren’t mutually exclusive. Perhaps the most successful VC firms embrace a collaborative dance between the two. Y Combinator and 500 Startups exemplify the scientific approach, backing many startups. Conversely, Sequoia Capital embodies the art-based approach and is known for its deep involvement with a select few companies. Ultimately, the key lies in balancing calculated risk and insightful judgment.

Building A Winning Portfolio: A Multi-Faceted Approach

Crafting a successful VC portfolio requires a blend of art and science. Quality should trump quantity. Like angel investors, VCs should focus on fewer, more promising companies. This concentrated approach allows for deeper engagement and support, potentially increasing the odds of success for their chosen ventures.

Don’t be blinded by technology. While innovative ideas are captivating, strong leadership and execution capabilities are crucial for transforming brilliant concepts into thriving businesses. Back visionary entrepreneurs who can navigate the complexities of building a sustainable enterprise. 

As Marc Andreessen, the renowned VC, famously said, “Software is eating the world… The best place to put your money is on the best people.”

Embrace diversification as a shield. Spreading investments across various sectors, industries, and regions is a prudent strategy to mitigate risks associated with specific market downturns. Currently, trending sectors like renewable energy, sustainable agriculture, and India-centric AI solutions offer exciting opportunities. 

Scalability, market size, and other factors should also be considered when making the fundamentally right decision. Ultimately, successful VC investing hinges on tailoring asset allocation to your individual risk tolerance and investment goals.

The Future Of VC: A Blend Of Strategies

As the VC industry evolves, a judicious blend of these strategies – quality focus, people-centric approach, diversification, and tailored asset allocation – will shape its future. This approach will drive innovation and economic growth and empower VCs to navigate the ever-changing landscape.

Emotional investing is a siren song for VCs. Chasing fads or trends without a clear investment thesis or a competitive edge can lead to overpaying, missing out on better opportunities, and facing fierce competition. 

Another pitfall is over-diversification, where investors spread themselves too thin across companies that must align with their strategy. This dilutes returns and limits their ability to influence the companies they invest in.

Be wary of unrealistic promises. Investments promising astronomical returns often mask significant risks. By exercising discipline, maintaining a well-defined investment strategy, and conducting thorough due diligence, VCs can avoid these pitfalls and position themselves for long-term success.

Final Thoughts: Orchestrating A Symphony Of Success

Adequate portfolio diversification is the maestro’s baton in the orchestra of successful VC investing. Understanding the inherent risks, implementing sound strategies, and avoiding common pitfalls empower VCs to navigate the exciting yet challenging world of venture capital. 

As the saying goes, “Don’t put all your eggs in one basket.” A well-designed VC portfolio, meticulously constructed and aligned with individual risk preferences and investment objectives, can significantly enhance the likelihood of superior returns. 

The future of VC lies in fostering innovation through calculated risks, strategic diversification, and a deep understanding of the ever-evolving market landscape.

The post Mastering Risk: Strategies For Effective Portfolio Diversification In Venture Capital appeared first on Inc42 Media.

With its booming internet user base of over 85 Cr, India presents an active ground for cybercriminals. A report by Armor Threat Resistance Unit estimates the dark web economy to handle over 2,400 sellers and a staggering 320,000 transactions annually. 

More often than not, these dark web users lure young people through social media scams or fake job advertisements, and make them a money mule. Promises of quick and easy money mask the sinister motives behind these seemingly harmless offers.

How Does The Dark Web Exploit Money Mules?

The dark web thrives on anonymity, and cryptocurrencies like Bitcoin, with their decentralised and pseudonymous nature, become the perfect tool for these fraudulent transactions. 

Money mules are then used to syphon these illegal funds – unaware of the criminal activity. They are then tricked into transferring money received in their accounts to other destinations, effectively laundering the stolen funds.

The consequences for money mules can be severe. They face legal repercussions, including money laundering charges and frozen bank accounts. Their credit scores can plummet, impacting their financial future for years to come.

Combating Money Mule Fraud 

Combating this threat requires a multi-pronged approach. Indian law enforcement agencies are actively working to track down money mules and disrupt dark web activities. The Enforcement Directorate (ED) has been particularly vigilant in cracking down on cryptocurrency-based money laundering, as evidenced by their recent actions. 

Public awareness campaigns can also play a vital role. Businesses in the cybercrime and fraud prevention space, like ours, and Financial Institutions have been educating people about the dangers of online scams and the importance of safeguarding personal financial information online can help prevent them from falling prey to money mule recruitment. 

Law enforcement agencies also continue their efforts to dismantle these operations and bring perpetrators to justice. Only through a collaborative effort can we curb this growing threat.

How Can Technology Help In Detecting And Preventing This?

The anonymity of the dark web, coupled with India’s growing internet user base, creates a breeding ground for money mule scams. Individuals can protect themselves by understanding the methods employed by criminals and the risks involved.  

Additionally, technology can play a vital role in detecting these illicit transactions, and prevent them from scaling. 

Machine Learning (ML) Algorithms: Financial institutions can implement ML algorithms trained on historical transaction data. These algorithms can identify suspicious patterns, such as sudden spikes in transactions, frequent transfers to unknown accounts, or activity inconsistent with user profiles. Real-time alerts can flag such transactions for further investigation, potentially uncovering potential money mule activity.

Link Analysis: Advanced analytics can map connections between accounts involved in suspicious transactions. This allows investigators to identify networks of money mules and trace the flow of illegal funds.

Behavioural Biometrics: This technology analyses a user’s digital behaviour patterns, such as typing speed or mouse movements. Deviations from established patterns during account creation or transactions, such as application familiarity or copy-pasting information, could indicate potential fraud or impersonation, a tactic sometimes used to recruit money mules.

Social Network Intelligence: Cross-referencing information from social media platforms against user data can help verify identities and uncover inconsistencies. For instance, inconsistencies between a user’s online persona and financial activity could raise red flags.

Enhanced KYC Processes: Financial institutions can implement stricter KYC procedures, including stricter verification of identity documents, employment status, and the source of funds.

By harnessing the power of technology, fostering collaboration, and empowering individuals with knowledge, we can significantly disrupt the operations of money mules and their role in Dark Web criminal activities.

The post Money Mules And The Dark Web: A Growing Threat In India appeared first on Inc42 Media.

In today’s hyperconnected world, financial institutions (FIs) find themselves on the front lines of an ongoing battle against financial fraud. According to the RBI’s annual report 2022-23, the number of frauds reported by banks has risen sharply, from 7,263 in 2020-21 to 13,576 in 2022-23. 

With technology evolving rapidly, cybercriminals continually devise new and sophisticated methods to breach security systems and exploit vulnerabilities. This digital setting carries significant risks, as data breaches not only lead to substantial financial losses but also cause lasting damage to reputation and erode customer trust. 

Against this scenario, regulators worldwide, including India, have introduced stringent guidelines to combat money laundering and financial fraud. Despite these efforts, the complexity and frequency of fraudulent activities continue to pose challenges for Indian banks. 

We need to examine the current practices adopted by Indian banks to prevent financial crimes and manage fraud risks, focusing on the role of AI and machine learning in monitoring transactions and ensuring compliance with regulatory guidelines effectively.

The Fallout of Data Breaches

A data breach may have far-reaching consequences, including permanent loss of consumer confidence in affected businesses. A research study by Centrify found 65% of data breach victims said they no longer trusted the company that was at fault. 

According to Forbes, 80% of consumers in developed countries will abandon a business if their personally identifiable information is compromised in a security breach. This level of distrust can have far-reaching implications. 

In addition, IDC projected that by 2019, 70% of major multinational corporations with origin in the US and EU would face substantial cybersecurity attacks targeting commodity distribution, which means that these breaches could have a huge financial impact. 

A March 2020 study by FTI Consulting further highlighted the seriousness of the situation, revealing that companies expect a 9% decline in global annual revenue due to data privacy crises.

Role Of AI-Led Compliance Tools

Despite the growing threat of financial fraud, FIs must plan a journey towards a secure and customer-centric future. Investing in innovative technologies, such as AI-powered fraud detection and e-KYC solutions, presents a promising pathway forward. 

These advanced tools enhance data security, streamline the customer onboarding processes and synchronise personalisation efforts.

Enhancing Security With AI-Driven Fraud Detection Systems

One strong line of defence against online fraud is systems for identifying fraudulent activities powered by AI. These systems detect suspicious patterns and anomalies that may indicate fraudulent activity by analysing massive datasets in actual time using powerful algorithms. 

Financial institutions can protect their assets and the personal information of their customers from possible dangers by employing proactive detection and continuous monitoring.

Streamlining Customer Onboarding With E-KYC Solutions

Efficient and automated onboarding is possible with the help of AI-driven e-KYC solutions, which also guarantee adherence to regulations. Financial institutions can onboard new clients quickly and securely with these tools by automating identity verification processes and cross-referencing customer information against comprehensive databases. 

This ensures that due diligence is not compromised. By simplifying processes, we can increase operational efficiency and provide a better experience for customers. This will hopefully lead to their continued loyalty and satisfaction.

Driving Personalisation And Engagement through Data Insights

In addition to improving safety protocols, AI and ML open up new channels for interacting with and tailoring to individual customers. These tools help financial institutions better understand their customers’ wants and needs by filtering through mountains of data, such as their purchase history, online habits, and demographics. 

With this information in hand, FIs can create more meaningful connections with their customers, increase satisfaction, and win their loyalty through targeted marketing campaigns, personalised product recommendations, and specific offers.

Employing Innovation For A Secure And Customer-Centric Future

To sum up, the importance of AI-led compliance tools in improving transparency and customer-centricity within the financial ecosystem cannot be overstated. As FIs confront the evolving threat landscape, investing in innovative technologies is not just a matter of necessity but a strategic necessity. 

By adopting AI and ML-powered solutions, FIs can navigate the complexities of modern finance with confidence, safeguarding both their interests and those of their valued customers. In doing so, they pave the way for a secure, transparent, and customer-centric future in the digital age.

The post How AI & ML Are Shaping The Future Of Fraud Prevention In Financial Services appeared first on Inc42 Media.

In an era where data is king, the sports prediction industry has experienced a profound transformation fueled by data-driven personalisation. No longer are predictions based solely on gut instincts and intuition. 

Today, predictive analytics and sophisticated algorithms are revolutionising how sports enthusiasts engage with their favourite teams and matches, igniting a new era of interaction and connection. 

The demand for accurate sports predictions is soaring, driven by financial stakes and emotional investments. As the sports industry increasingly turns to data-driven decision-making, artificial intelligence (AI) and machine learning (ML) have become pivotal tools. These technologies are redefining the prediction landscape, offering unparalleled accuracy and insights. 

Artificial Intelligence and Machine Learning In Sports Prediction

AI and ML are branches of computer science focused on building systems capable of performing tasks that typically require human intelligence. AI encompasses a broad range of capabilities, including problem-solving, speech recognition, and visual perception. Machine learning, a subset of AI, involves the use of algorithms and statistical models to enable computers to improve their performance on a task with experience.

In the context of sports predictions, ML algorithms are particularly valuable. These algorithms analyse vast datasets to identify patterns and trends that might not be immediately apparent to human analysts. 

For example, by processing historical game data, player statistics, and even social media sentiment, ML models can predict the outcomes of games with remarkable precision. Techniques such as neural networks, decision trees, and clustering play crucial roles in enhancing the predictive power of these models.

The use of AI and ML in sports prediction is not entirely new, but their role has become increasingly pivotal. Early applications were limited by computational power and data availability. 

However, advancements in technology and the exponential growth of data have now made it possible to build more sophisticated and accurate models. These technologies are now integral to the operations of many sports analytics firms, betting companies, and professional sports teams.

Ethical Considerations And Regulatory Frameworks

As with any powerful technology, the use of AI and ML in sports prediction brings ethical considerations to the forefront. One of the primary concerns is privacy and data protection. The datasets used for training predictive models often contain sensitive information about players, teams, and even fans. Ensuring this data is handled responsibly is crucial to maintaining trust and integrity in the industry.

Moreover, the use of AI and ML should be transparent and accountable. This includes being open about the methodologies used in creating predictive models and ensuring that these technologies are used in a manner that is fair and unbiased. 

Regulatory frameworks are beginning to emerge to address these issues, providing guidelines on data usage, algorithmic transparency, and accountability. However, as the technology evolves, these frameworks will need to be continuously updated to keep pace with new developments.

Future Trends And Developments

The future of sports prediction technology is poised for exciting advancements. AI and ML will continue to evolve, incorporating more sophisticated techniques and broader datasets. 

One anticipated development is the integration of virtual reality and augmented reality in sports analytics. These technologies can provide immersive experiences and real-time data visualisation, offering deeper insights into game strategies and player performances.

Another growth area is the adoption of more advanced neural networks and deep learning models, which can process and analyse data at an even more granular level. This will enhance the ability to make accurate predictions not only about game outcomes but also about individual player performances and injury risks.

However, the adoption and scaling of these emerging technologies come with challenges. One significant hurdle is the need for massive amounts of high-quality data, which can be expensive and time-consuming to collect. Additionally, there is the challenge of integrating new technologies with existing systems and ensuring that they are user-friendly and accessible to a broad range of stakeholders in the sports industry.

The integration of AI and ML in sports prediction marks a transformative shift in the industry. These technologies offer a level of precision and insight that was previously unattainable, influencing decision-making at all levels. 

As we look to the future, the potential of these technologies is vast, promising continued advancements and new applications that could redefine the landscape of sports analytics. However, with this potential comes responsibility. 

Ensuring ethical use, protecting privacy, and maintaining transparency will be critical as we navigate this evolving landscape. By addressing these challenges proactively, the sports industry can harness the power of AI and ML to drive innovation and success, paving the way for a future where data-driven insights enhance every aspect of the game.

The post Emerging Technologies In Sports Prediction: AI, Machine Learning, And Beyond appeared first on Inc42 Media.

In the last decade, ‘fintech’ has been the most quintessential buzzword in finance; evolving everything from traditional banking to payments, credit, savings, remittances, and insurance. It’s leading the charge in digitising and empowering the entire financial services ecosystem.

Family offices in India have been the custodians of intergenerational wealth management. A report by Empaxis states that an estimated 300 family offices collectively have an average AUM of $30 Bn as of 2023. 

The total wealth management market in India reached $429.1 Bn in 2023. This reflects a significant share of the wealth that family offices manage against the total wealth management market in the country.

However, as custodians of substantial assets, these private entities have traditionally been characterised by meticulous manual processes, extensive paper trails, and a reluctance to embrace technological advancements. 

This is where a change is imperative for family offices to modernise their operations or risk being left behind in an increasingly digitised world. Family offices are still in the nascent stages of determining the most effective systems for their daily operations.

As the Ernst and Young report rightly reflects, with the immense variety of tools and platforms available, navigating this landscape can be overwhelming, especially with the barrage of options from the sell side. 

For family offices, integration goes beyond mere aggregation of tools; it’s about unifying functionalities to provide a comprehensive view. This entails more than a conventional dashboard as a PwC Report states that family offices require dynamic, participative platforms that can keep up with their evolving needs. 

Strategising The Path Forward 

Would you believe that the implementation of a single robust platform can revolutionise family office operations, potentially saving up to 60% of time spent on routine tasks?

The adoption of technology among family offices follows a U-shaped curve, with initial resistance giving way to gradual acceptance and eventual habit formation. Technology remains a key factor, necessitating a shift in behaviours and habits but realising these efficiency gains requires a concerted effort towards intent and behaviour change.

In addition to providing a holistic view of portfolios, platforms must facilitate collaboration, information sharing, and timely execution of routine tasks on a daily, weekly, and monthly basis. 

These functionalities are essential for fostering efficiency and transparency within family offices. Family offices view themselves as businesses, necessitating the adoption of professional platforms tailored specifically to their needs. These platforms should streamline operations while accommodating the unique complexities of family office management.

Disparate systems persist due to their familiarity and ease of operation. Rather than complete reinvention, the solution lies in marrying familiar interfaces with modern backend systems, ensuring a smooth transition to digitalisation. 

Family offices are eager to embrace new platforms, provided the process is seamless, quick, and requires minimal intervention.

High turnover rates pose a challenge for family offices, as new team members must navigate steep learning curves. Platforms designed with user-friendliness in mind can mitigate this barrier, ensuring continuity even amidst personnel changes. 

As family offices grow in size, complexity, and jurisdictional reach, virtual platforms become indispensable for preserving institutional knowledge and ensuring continuity across generations. 

As the saying goes, “Tomorrow is a very different picture”, family offices that embrace change today will emerge as resilient institutions capable of navigating the complexities of tomorrow’s wealth management landscape. 

The number of family offices is expected to reach about 1000 from 300, as per Empaxis. If 60% of the time spent by family offices is refrained from routine tasks, it is evidently indicative that family offices will take ownership of a significantly substantial amount of the total wealth management in the country. 

By integrating robust platforms and fostering a culture of collaboration and innovation, family offices can not only enhance their operational efficiency but also strengthen their position as key players in India’s evolving financial ecosystem.

The post The Missing Platformization In The Family Office Space appeared first on Inc42 Media.

As a nation, India is taking huge strides digitally. This is obvious from independent research reports estimating that the digital economy of India will contribute nearly 20% from 8% currently to its GDP by 2030.

Among other technologies, the cloud has played a big role in enabling and accelerating the digital economy and forecasts from analyst firms indicate a monumental shift towards embracing public cloud services. 

Research firm IDC, for example, predicts that the public cloud services market in India will reach a mammoth $17.8 Bn by the year 2027, growing at an impressive CAGR of 22.9% from the year 2022 till 2027.  

However, despite the growing adoption of cloud, many Indian organisations are still grappling with common concerns centred around cost, risk, and security.

The Cost-Risk-Security Imperative

Often it has been observed that though the cloud promises enhanced flexibility and responsiveness many organisations in India remain apprehensive about migrating from traditional data centres. This reluctance often stems from perceived costs and risks associated with cloud adoption.

Contrary to conventional beliefs that on-premises data centres offer superior security, cloud providers can deliver superior security measures that ensure round-the-clock data protection while adhering to stringent industry and regulatory standards. Through robust service level agreements (SLAs), organisations can gain greater control over their applications and data and mitigate the risks of unauthorised data access. 

Cloud service providers invest heavily in state-of-the-art security infrastructure, employing a team of cybersecurity professionals dedicated to staying ahead of evolving threats. This expertise translates to a higher level of security compared to what many businesses might be able to achieve on their own, especially for smaller organisations. 

Cloud providers have sophisticated security monitoring systems in place that can detect and respond to security threats in real time. These systems analyse network traffic for suspicious activity, identify potential vulnerabilities, and automatically trigger security protocols to mitigate threats. 

This continuous vigilance provides a significant advantage over relying solely on in-house security personnel. Cloud infrastructure is also scalable, allowing resources to be provisioned and de-provisioned rapidly. In the event of a cyberattack, cloud providers can quickly isolate affected systems and scale up resources to maintain service and business continuity. 

This redundancy and scalability mitigate the risk of downtime and data loss associated with data centre breaches. 

There is also a misconception that on-premise solutions are inherently more cost-effective. This hypothesis is far from the truth.   A comprehensive evaluation of the total costs reveals hidden costs such as maintenance, upgrades, security, and performance optimisation.  

In this context, cloud migration, when viewed holistically, emerges as a financially prudent choice, offering potential cost savings and operational efficiencies that transcend traditional infrastructural limitations.

Tailoring Cloud Solutions To Unique Organisational Needs

For organisations attempting to move to the cloud, a one-size-fits-all approach in the adoption process is impractical. Hence, collaboration with cloud providers is crucial for organisations contemplating migration. 

They must choose their path towards the cloud meticulously: these should encompass upgrades, optimisation, and modernisation. Each component must be tailored specifically towards meeting the unique needs of each organisation. This is imperative for a successful cloud migration. 

Within the cloud landscape, Software as a Service (SaaS) has emerged as a preferred deployment model for new applications, with companies expressing a preference for scalable, subscription-based solutions. 

In the above-quoted IDC study, SaaS was the largest component of the overall public cloud services market. The SaaS model helps organisations with access to best practices, which previously was the prerogative of large enterprises. 

This enables and empowers organisations of all sizes to drive efficiency and innovation. The SaaS model also enhances cost savings, supports a flexible workforce, eliminates implementation and maintenance costs, and provides improved collaboration capabilities. 

Hence, for organisations in India aiming to enhance efficiency and agility, SaaS has emerged as a preferred deployment model. The IDC study previously quoted identifies SaaS as the largest component of all public cloud services markets. 

The Value Of Hybrid Cloud Management

With hybrid clouds being the norm rather than the exception, maintaining visibility and control across disparate environments can be difficult. Businesses struggle to monitor performance, ensure compliance, and optimise resource utilisation. 

Managing separate tools and processes for on-premises and cloud resources increases complexity. Siloed operations make it difficult to achieve consistent automation and orchestration across the entire IT ecosystem. 

The integration of different environments introduces new security concerns. Businesses need robust security measures that seamlessly integrate across both cloud and on-premises infrastructure. 

Hybrid cloud management solutions bridge the gap between on-premise and cloud environments, by offering a consolidated view of all IT resources, both on-premise and in the cloud. 

This enables businesses to monitor performance, manage deployments, and automate workflows across their entire hybrid infrastructure. By offering standardised tools and processes for managing cloud and on-premise resources, hybrid cloud management solutions streamline operations. 

This translates to increased efficiency, reduced operational costs, and faster time to market for new services. Additionally, by providing a holistic view of resource utilisation across the hybrid environment, businesses can identify and eliminate inefficiencies. 

This leads to optimised resource allocation, reduced cloud costs, and improved return on IT investments. 

The Importance Of FinOps

Cost is also one of the major considerations for evaluating the benefits of a cloud-driven process. Hence, cloud governance is important as left unchecked, cloud costs can spiral out of control. Here is where FinOps can play a vital role. 

FinOps isn’t a product or software; it’s a cultural and operational shift that fosters collaboration between finance, IT, and business teams. It emphasises continuous optimisation of cloud costs by providing a framework for informed decision-making. 

Cloud costs are tracked and allocated transparently to specific teams or projects. This fosters a sense of ownership and encourages responsible cloud resource usage. 

Cloud spending is also aligned with business objectives. FinOps helps identify opportunities to leverage cost-effective cloud services while ensuring optimal performance and value for the business. 

More importantly, FinOps is an iterative process. Costs are continuously monitored, analysed, and optimised through regular reviews and adjustments to cloud resources and pricing models.

Over some time, organisations adhering to FinOps principles can identify and eliminate wasteful spending on underutilised resources or poorly optimised configurations. By leveraging the cost-saving features of cloud providers and implementing right-sizing strategies, businesses can significantly reduce their cloud bills. 

Teams are empowered to understand their cloud usage patterns and make informed decisions about resource allocation. This promotes collaboration and eliminates finger-pointing when it comes to cloud bill management. 

FinOps also equips businesses with data-driven insights into their cloud spend. This allows for better forecasting, budgeting, and selection of the most cost-effective cloud services and pricing models based on evolving business needs.

In Conclusion

In the cloud migration journey, selecting the right cloud service provider is critical. Factors such as customer references, flexibility, integration capabilities, support services, robust security, certifications and compliance frameworks must be meticulously evaluated. 

For instance, products or platforms enabling cloud-certified Enterprise Information Management applications as managed services in private or public clouds can be extremely effective in cloud-based migrations. These platforms offer a seamless transition path for organisations seeking enhanced security, reduced TCO, and improved operational resilience.

As India marches towards a cloud-centric future, organisations must overcome their traditional biases. The cloud, with its promise of improved security, enhanced data protection, and operational efficiencies, is poised to become the standard backbone for businesses across industries.

The post Embracing A Cloud-Driven Future appeared first on Inc42 Media.

In today’s marketplace, which is rapidly changing, the concept of brand loyalty in the traditional sense has seen a rapid transformation. 

Businesses can no longer rely solely on brand recognition to retain customers. As consumer behaviour and expectations evolve, trust and personal connection with those selling the product become central to building long-term relationships and customer success. 

According to a recent survey, there’s a notable decline in consumer trust toward brands, with 55% of consumers not trusting brands as much as in previous years. This trust erosion extends to scepticism towards traditional advertising and a greater reliance on recommendations from friends and family​. 

Furthermore, especially amongst Gen Z consumers, a reported 79% stated that it’s crucial to trust the brands they purchase from. 

Today, we will examine why brand loyalty is fading and how businesses can adapt to this change. We will explore effective strategies for companies to implement to enhance trust and improve overall customer retention. By embracing the techniques in this comprehensive guide, businesses can better navigate the complexities of modern consumer relationships and secure a competitive edge. 

The Changing Dynamics of Consumer Loyalty” The landscape of brand loyalty is undergoing a significant transformation. Today’s consumers rely more on peer recommendations and online reviews rather than traditional advertising or brand reputation. 

Customer choices today are shaped by review choices, with 60% of shoppers considering the quantity & quality of reviews when making purchasing decisions. A shift has negatively impacted traditional brand loyalty, posing challenges for businesses. 

To adapt, companies must adjust their strategies to align with evolving consumer behaviours. With interpersonal interactions and peer opinions wielding more influence, companies need to prioritise authentic connections and transparency to remain relevant. 

Understanding The Customer Journey

Comprehending the customer’s purchasing journey is the cornerstone of fostering brand loyalty. Once the touchpoints between the customer and the organisation are identified, efforts can be made to streamline the experience seamlessly. 

The initial interaction, often termed the Golden Moment, holds immense significance as it shapes the entire relationship. Whether through a website visit, social media engagement, or face-to-face encounter, this first touchpoint must captivate the customer and mirror the brand’s values.

Research indicates that approximately 80% of consumers exhibit increased spending tendencies when their experiences are personalised and exceed expectations, underscoring its significance. This aspect gains further importance, considering that 68% of customers are inclined to switch to competitors if they perceive a company’s indifference towards them. 

Effective communication serves a dual purpose: it addresses queries, guides customers through the purchasing stages, and lays the groundwork for trust and satisfaction, which is pivotal for sustained engagement.

Additionally, it is paramount to understand the factors that influence purchase decisions throughout the journey, such as online presence, reviews, and peer opinions.

Fostering Customer Engagement

In today’s dynamic marketplace, effective strategies for customer engagement are indispensable. Brands must harness the power of social media, email, messaging apps, and personalised communication to establish deeper connections with consumers. Fostering two-way engagement lies in facilitating real-time feedback and ongoing dialogue through social listening.

For example, Coca-Cola has adeptly utilised social media platforms to engage with customers, particularly during promotional campaigns and for customer service purposes. Platforms like Twitter and Facebook serve as arenas for customer interaction, especially during events like the Super Bowl, where customers can vote on campaign outcomes, enhancing their sense of involvement.

One powerful way to engage customers is by offering them opportunities to actively participate in shaping the brand experience. Audio-Technica, a leading innovator in transducer technology, exemplifies this approach through its ‘Annual fan design contest “for its ATH-M50x headphones. 

Here they invite brand loyalists and customers to submit designs and actively participate in the selection process, fostering a sense of community while creating a unique and personalised experience for its customers, creating buzz and excitement around the brand. 

Customer engagement initiatives are crucial to nurturing emotional connections and trust, which are foundational elements in cultivating customer loyalty. Adopting a multi-channel approach that ensures consistent support and product availability across various channels—whether online, in-app, or in-store—facilitates a seamless purchasing experience. This consistency mitigates customer frustration and abandonment, reinforcing the brand’s commitment to convenience and reliability.

Exceptional Post-Sales Service

As they say, the proof is in the pudding.

The actual test of an organisation’s commitment to its customers comes into play post-sales. 

Good post-sales support entails prioritising swift responses to customer inquiries and promptly addressing concerns. 

Establishing a robust grievance resolution mechanism showcases the brand’s dedication to customer satisfaction. 

Moreover, surpassing customer expectations through proactive service checks, supplementary support, or implementing loyalty programs that incentivise continued patronage can significantly enhance customer satisfaction. These exemplary practices contribute to the perception of reliability and attentiveness, thereby solidifying a positive brand image. 

Brands that nail their post-sales support transform their customers into vocal advocates, catalysing organic growth through powerful word-of-mouth endorsements.  

 Implementing Loyalty Programs And Incentives

When effectively tailored to different customer segments, loyalty programs can be powerful marketing tools designed to enhance customer retention and boost engagement and loyalty. 

The design and execution of these programs should focus on providing value through a variety of incentives such as rewards, special events, and exclusive offers. Brands need to maintain regular communication to keep their customers informed and engaged. 

For instance, research indicates that members of loyalty programs generate 12-18% more revenue growth per year than non-members. Furthermore, Businesses with loyalty programs find that these members account for 45% of their sales, and members who redeem personalised offers spend 4.5 times more annually​ than other customers. 

When these incentives align with their target audiences’ needs and preferences, businesses can create a sense of belonging and appreciation among their customers. 

Loyalty programs then create a personalised approach that encourages repeat purchases while strengthening the emotional connections with the brand, leading to long-term success. 

Continuous Feedback And Adaptation

Learning and evolving are two essential components for unlocking long-term success, integral to an organisation’s culture and leadership ethos. It involves actively gathering customer insights through various channels, such as feedback surveys, social media platforms, and direct communication channels. Social listening plays a crucial role, enabling businesses to effectively understand customer sentiments, perceptions, and evolving needs.

Addressing customer grievances requires agility and responsiveness. Well-designed systems, processes, and authority matrices are imperative to facilitate prompt and effective resolutions while monitoring broader trends that may necessitate systemic changes. 

Brands that proactively adjust based on this feedback can significantly enhance the overall customer experience, showcasing their commitment to customer satisfaction.

Continuous refinement of products and services in response to customer input is vital to maintaining relevance and improving loyalty, providing a competitive advantage in the market. 

Embracing a culture of learning, adaptation, and customer-centricity enables organisations to stay agile and resilient in an ever-evolving business landscape.

To Sum Up

In essence, achieving customer loyalty and retention demands more than just isolated efforts. It necessitates adopting a carefully crafted, holistic strategy that includes engaging loyalty programs, exceptional post-sales service, and a robust feedback mechanism. 

To thrive in a rapidly evolving market, businesses must adapt to deliver a seamless, personalised customer experience across the entire journey, not just at the point of sale. 

By prioritising genuine connections and continuous innovation driven by customer feedback, companies can set new standards in customer loyalty and building trust, positioning themselves as leaders in customer retention.

The post Rethinking Brand Loyalty: Strategies For Building Trust And Retention appeared first on Inc42 Media.

Gone are the days when people used to aspire to stick to conventional job profiles because it was believed that such job profiles were more “risk-free”. Though they were able to achieve some kind of stability in pursuing these careers, they offered scope for growth and resulted in a lack of creativity. Today, things have changed to a great extent.

Technology has paved the way for the mushrooming of many new fields such as digital marketing, cloud computing, cybersecurity, blockchain development, artificial intelligence, to name a few, that were unheard of, even ten years ago. 

There was a time when people were terrified that technology would replace humans, but now, people have learned to leverage technology to their advantage. And those who are doing a great job at it are earning the perks of it too, which include flexible work schedules, higher pay, better career growth opportunities and in some cases, remote work.     

Ten years ago, if someone had said that a person in India would work remotely for an American company without facing the hassle of relocation, no one would have believed it. Similarly, there are many trends that might seem too far-fetched to become a reality now but can become commonplace in the future. Let’s have a look at these trends that will develop over the next ten years:

Spotlight On The Trends

Here are five trends that are going to be the centre of attention in the next ten years:

Smaller Organisations Are Going To Be The Next Big Thing In IT

Unlike large organisations, small businesses are going to be far more resilient to the changing work landscape and will be able to adapt quickly to changes in market demands. Bigger organisations and enterprises may struggle with getting rid of their old, obsolete processes because of bureaucratic delays. The key is for small and large organisations to collaborate to keep up with the times and further innovation.

Hierarchy Will Eventually Become Obsolete

Everyone is going to have a say and be their own boss. Hierarchy, which has been disappearing slowly anyway, will eventually disappear as the concept of leadership itself evolves. Everyone is going to be a leader in their own right, which means that micro-management will also not continue to be a problem. This will result in a more empowered workforce.

Emerging New Role Of A Culture Setter

The role of the culture setter is going to be a new role in the upcoming years; this person will be responsible for shaping the culture of the organisation. It will be their responsibility to ensure that the company and its employees are abiding by the codes of ethical, professional, and moral conduct. With their involvement, employee engagement rates can improve, and employees will be more productive too. 

Employee Well-Being Will Be At The Core Of It All

Health is going to be at the forefront and the companies will pay a great deal of attention to their employees’ health. They will finally understand that productivity is tied to the employees’ physical and mental well-being. As a result, companies can offer better health policies, conduct awareness programs, and be a partner in their employees’ healthcare journey. 

AR And VR For Socialising

The future is likely to be largely remote. As a result, socialising and ice-breaking activities will take place in a virtual environment with the involvement of augmented and virtual reality [AR and VR]. 

These technologies are capable of creating an immersive environment where face-to-face interactions are conducted virtually but have the same impact as real-world interactions. Interactive team-building games and VR social events will be commonplace. 

These trends overall, are going to take the world by storm, and completely change the dynamics of industries as a whole. The only way that an employee can stay relevant is to keep up with the change and embrace the future of work. 

It takes much more than money to keep employees satisfied and productive. Once employers understand the importance of work-life balance and mental health, they will automatically be one step ahead.

What Will The Future Of Work Look Like?

A recent report by PwC titled ‘Workforce of the future: The competing forces shaping 2030’ imagines that the future work world will be divided into four categories based on colour.

The Red World is where innovation is key. Companies are fiercely competitive, motivated by a desire to be at the forefront of technology and product development. The Blue World is governed by massive businesses that prioritise efficiency, scalability, and stability. Work is structured and managed according to typical corporate hierarchies, with an emphasis on maximising shareholder profit. 

In the Green World, companies take on a greater social and environmental responsibility. There is a strong emphasis on sustainability, ethical practices, and community well-being. Organisations in this world prioritise long-term societal benefits over short-term gains, and employees are engaged in meaningful work that aligns with their core inner values. 

The Yellow World values uniqueness and human-centric methods. It is distinguished by a commitment to social cohesiveness, well-being, and work-life balance. Companies throughout the world value the human components of work, such as creativity, teamwork, and personal fulfilment. Employees are driven by a sense of purpose and aim to make a positive difference.

The Bottom Line: Be Prepared For All Kinds Of Change

The report underlines the need for both prospective employers and employees to adopt a dynamic approach to fit into this new work world order. Change is already happening and it is accelerating at an unprecedented rate.

So adapting to change should have begun already via upskilling, accepting that automation and the use of AI will be a part of the deal, and focusing on building a mature conversation about the future.

The post The Future Of Work: Analysing Trends For Careers In The Next Ten Years appeared first on Inc42 Media.

In the fast-paced world of startups, success hinges on more than just a groundbreaking idea or a talented team. It requires a deep understanding of the target audience and their needs. 

In today’s competitive landscape, where consumers have endless options at their fingertips, building products that resonate with customers is paramount. This is where user research comes into play. 

By gathering insights directly from users, startups can tailor their offerings to meet market demands effectively.

Understanding Your Target Audience

At the heart of any successful startup lies a profound understanding of its target audience. Identifying the pain points and preferences of potential customers is essential for crafting products or services that truly add value. 

Techniques like user personas and customer journey mapping can provide invaluable insights into user behaviour and preferences, helping startups align their offerings with customer needs from the outset.

Product-Market Fit

Achieving product-market fit is the holy grail for startups, signalling that they have found the sweet spot where their product meets a significant market need. User research plays a pivotal role in validating product-market fit by enabling startups to gather feedback from users early and often. 

Whether through MVP testing or user interviews, startups can iterate on their offerings based on real-world insights, increasing their chances of success. For instance, companies like Airbnb and Dropbox attained product-market fit by actively listening to their users and adapting their offerings accordingly.

Competitive Analysis

Understanding the competitive landscape is crucial for startups looking to carve out their niche in the market. By conducting thorough competitive analysis, startups can identify opportunities and threats, as well as areas where they can differentiate themselves. 

Techniques like SWOT analysis and feature benchmarking can provide startups with a comprehensive understanding of their competitors’ strengths and weaknesses. User research complements this analysis by uncovering user preferences and pain points, enabling startups to tailor their offerings for maximum impact.

Iterative Design And Development

In today’s dynamic market, success often depends on the ability to adapt quickly to changing user needs and market conditions. Adopting an iterative approach to product design and development allows startups to incorporate user feedback throughout the process, ensuring that their offerings remain relevant and valuable. 

The Human Centred Design (HCD) approach with its emphasis on flexibility and collaboration, is particularly well-suited for this purpose, enabling startups to iterate rapidly and efficiently.

Human-Centred Design Principle

At the core of effective user research lies the principle of human-centred design. By placing users at the centre of the design process, startups can create products that are intuitive, enjoyable, and ultimately more successful. 

Principles like empathy and usability guide startups in understanding user needs and preferences, leading to products that resonate with their target audience. 

Companies like Apple and Google have long embraced user-centred design, resulting in products that have revolutionised their respective industries.

Conclusion

In today’s hyper-competitive startup landscape, user research is not just a nice-to-have—it’s a necessity. By understanding their target audience, validating product-market fit, analysing the competition, and embracing iterative design principles, startups can increase their chances of success significantly. 

By prioritising user research and adopting a customer-centric mindset, startup founders can position their ventures for long-term growth and sustainability. It’s time for startups to listen to their users, iterate relentlessly, and build products that truly make a difference in people’s lives.

The post Creating Customer-Centric Startups: A Guide To Effective User Research Strategies appeared first on Inc42 Media.

In the annals of military history, the evolution of warfare has been characterised by seismic technological innovations. From the tanks to the rise of Unmanned Aerial Vehicles (UAVs), each decade has witnessed the launch of new combat assets, and even more amidst the changing socio-political contours. 

In fact, in recent years India has showcased its likeness to enhance domestic defence capabilities, in line with the broader ‘AtmaNirbhar Bharat’ initiative.

The pronounced shift towards becoming a more self-reliant defence market becomes more evident, against the notable uptick in defence spending which stands at a staggering INR 6.21 Lakh Cr for the 2024-2025 interim budget. 

Supporting this growth is the recent rise in drones, which have quickly surfaced to the top by challenging the dominance of traditional heavy armour and posing as a major strategic advantage that has empowered the army in more ways than one.     

High-Definition Surveillance Boosting Military’s Decision Capabilities

In the age of nuanced military operations, the adoption of drones presents the capacity to offer high-definition surveillance. This has been a game-changer and has opened the door to enhanced situational awareness and informed decision-making. 

Equipped with sophisticated EO/IR camera sensors, the new drones allow for unparalleled visual clarity and detail, and this helps in the identification of potential threats, and enemy movement. 

Having recognised the value of high-surveillance drones, the Indian Armed Forces is actively seeking domestically produced drones to enhance the ISR capabilities. 

At the same time, these drones can help the Indian military in conducting assessments of tactical situations with unmatched precision to safeguard the lives of personnel on the frontlines. 

With the accurate monitoring of sensitive areas, they can plan their operation with greater accuracy, and also reduce the risks and increase the chance of success and survival. 

Additionally, the footage captured by these drones will allow the military to enhance their training by analysing these real-life situations, which will in return improve the effectiveness of operations.

Enhancing The Power Of Military 

While the role of medium and large drones is significant in increasing the conventional capabilities in ISR, directing artillery fire, and conducting post-strike assessment, at the same time, the power of small and micro drones cannot be overlooked. 

In various tactical situations, micro drones can be used to pinpoint the location of insurgents, which facilitates their neutralisation. In addition, destructive drones which are designed to carry explosive payload and engage targets with accuracy can help reduce collateral damage. 

Drones have become an indispensable asset for gathering intelligence and tracking and monitoring terrorist groups. They can not only operate in dangerous areas but can also provide real-time intelligence which allows the armed forces to immediately respond and take swift measures. 

Furthermore, drones embedded with an advanced camera and constant presence help in strengthening border surveillance, protecting the country from any illegal crossings and unauthorised attempts.    

Expanded Reach And Remote Monitoring 

In contested environments and complex terrains, traditional air force carriers may not be viable solutions, against which advanced Aerial Defence systems emerge to be promising. 

These modern drones leveraging AI capabilities, and autopilot features allow for autonomous navigation and operation in GPS-denied areas. Also, the AI-embedded sensor suite goes a long way in enabling real-time object identification, classification and tracking.      

With continuous innovation in the airframe material, payload, weight, deployment, range and ease of use, these advanced drones are proving to be valuable in harsh environmental conditions, as they keep the performance optimal and ensure longevity.

As the contours of warfare continue to change, there are times when the mission also needs to be altered, and in such cases, these drones coordinate through mesh networking and swarming algorithms which provides seamless communication to adapt to mission changes.

Final Thoughts  

The revolutionary impact of drone technology on India’s defence capabilities is undeniable. The aerial systems help in offering unprecedented capacity in surveillance, intelligence gathering and remote operations, while also enhancing situational awareness by allowing precision targeting. 

As the country moves on building its defence capabilities, the integration of domestic Aerial Defence systems presents an opportunity to foster independent growth for the defence sector. 

The post The Rise Of Drones In Modern Warfare – What More To Look For? appeared first on Inc42 Media.

The most significant transformation that swept India Inc. over the past decade perhaps is the rise of a dynamic startup ecosystem driving innovation across sectors. With over 1.28 lakh startups in April 2024, compared to just 450 in 2016, India proudly hosts the world’s third-largest startup ecosystem. 

Thanks to digitalisation efforts and supportive government policies, this ecosystem in India is ready to witness YoY growth of 12-15% in the coming years, contributing significantly to the country’s GDP.

India Startup Ecosystem: An Overview

The startup landscape in India is thriving, thanks to the growing entrepreneurial spirit showcased by the young generation, especially Gen Y and Z. Currently India is home to 110+ unicorns, 5,000+ angel investors, 1,400+ venture capitals and 1,100+ private equity firms. There are 1,200+ incubators and accelerators engaged in various support and training through workshops and mentorship programs, while also helping these entrepreneurs identify new investors, partners and customers.  

Backed by several success stories, this ecosystem in India has seen a surge in venture capital investment over the past decade, involving several local and international investors. 

However, during 2023, exits from investments surged by almost 1.7 times to $6.6 Bn, as investors aimed to provide liquidity to Limited Partners (LPs) amidst a high-interest-rate environment. Crossover funds contributed close to 65% of overall exits. It is important to note that public market sales dominated the exit landscape, comprising nearly 55% of the total exit value.  

Demographics Grow Wider

As per the industry estimates, the startups have spread across over 670+ districts of the total 806 in India. Major cities like Bengaluru, Hyderabad, Chennai, and Pune host a large pool of tech graduates and have become talent hubs, making them the favourite destinations for VCs and tech giants. 

However, data reveals that around 50% of these companies now operate in tier 2 and tier 3 cities, demonstrating the viability of their operations in these areas. Developments in infrastructure, availability of talent, and lower cost of living are making these destinations attractive to the new age entrepreneurs. 

The sector is upbeat in terms of gender neutrality as well, with about 48% of them having at least one woman director.

Skill-Force To Propel The Economic Engine

With 66% of India’s population under 35 and a significant number of them being STEM graduates, Indian startups are at a greater advantage compared to their peers globally. Over the past decade, these budding entrepreneurs have served as the catalyst of the country’s economic growth propelling its ambitions to become the world’s third-largest economy in the next 3-5 years. Already, the 1.25 lakh startups in India have created over 1.3 Mn jobs, alleviating the concerns over brain drain and redirecting the country’s talent to diversified sectors in the country. 

Government Schemes To Spur Innovation

Recognising the pivotal role of startups in driving economic growth and job creation, the government has launched a number of initiatives to foster innovation and entrepreneurship. Programs like Startup India, Standup India, and Atal Innovation Mission provide growing companies with vital resources such as funding, mentorship, tax benefits, and regulatory support. Projects like SAMRIDH and Chunauti support innovative startups addressing societal challenges, while Digital India Bhashini aims to enhance digital accessibility in Indian languages. Schemes like SIP-EIT, MGS, and CGTMSE offer diverse credit and lending facilities, empowering MSMEs and startups across sectors.

Some of the other notable initiatives to encourage startups include the $1.4 Bn Fund of Funds for Startups (FFS), States’ Startup Ranking, National Startup Awards, National Startup Advisory Council, the $115 Mn+ Startup India Seed Fund Scheme (SISFS), the mentorship portal MAARG, Startup India Investor Connect, Bharat Startup Ecosystem Registry, among others. These initiatives have catalysed this very ecosystem in India, leading to significant growth and job creation.

Building The AI Startup Era

Considering the relevance of artificial intelligence (AI) in today’s technology landscape, the government has embarked on an India AI Mission to support the AI ecosystem in India, with $267 Mn earmarked for AI-related startups. 

AI has taken centre stage in the government’s digitalisation programs with a focus on inclusive growth across sectors like healthcare, agriculture, education, and smart cities. The Indo-German collaboration with a focus on AI startups as well as AI research and its application in sustainability and healthcare is a ground-breaking step in this line. 

India is also collaborating globally for ethical AI, emphasising the importance of fairness, transparency, and accountability in AI development. Global tech majors like Google, Microsoft, Meta, and NVIDIA have been engaging with Indian ecosystem partners to develop the best AI-based solutions to address the country’s emerging needs.  

To sum up, the future looks highly promising for Indian startups as they are empowered with the right technology skills, necessary funds and infrastructure to drive their vision forward. With clear vision and supportive policies from the government, they can elevate the country’s status as a global leader in innovation and entrepreneurship.

The post A Decade Of Growth In India’s Startup Ecosystem And Future Prospects appeared first on Inc42 Media.

Over the past year, Generative AI has gained prominence in discussions around Artificial Intelligence due to the emergence of advanced large multimodal models such as OpenAI’s GPT-4, Google’s Gemini 1.5 Pro etc. 

Across verticals, organisations have been actively exploring Generative AI applications for their business functions. The excitement around the technology, and its vast untapped potential, is reflected in a prediction by Bloomberg that the Generative AI will become a $1.3 Tn market by 2032.

Insurance is one of the key sectors where Generative AI is expected to have a revolutionary impact – enhancing operational efficiency and service delivery and elevating customer experience. 

From automating claims processing to predictive risk assessments, let us take a deeper look at some of the Generative AI use cases that will redefine InsurTech in the years ahead.

Automated And Efficient Claims Settlement

Lengthy and complex claims settlement processes have long been a pain point for insurance customers. Generative AI addresses this by streamlining the claims process through seamless automation. 

AI analyses images or other visual data to generate damage assessments. It can extract and analyse relevant information from documents such as invoices, medical records and insurance policies – enabling it to swiftly determine the validity of the claim, as well as the coverage, and expedite the settlement. 

This serves to improve process efficiency, reduce the administrative burden on staff, and significantly boost customer satisfaction.

Optimised Underwriting And Streamlining Risk Assessment

Underwriting is another key area where this technology can create immense value for insurance firms. With their ability to analyse vast amounts of data, Generative AI models build comprehensive risk assessment frameworks that enable them to swiftly identify patterns and highlight potential risks. 

It automates the evaluation of a policy applicant’s data, including medical and financial records submitted, to determine the appropriate coverage and premium.

Leveraging AI, underwriters are empowered to better assess risks and make more informed decisions. By reducing manual effort, minimising the possibility of human error, and ensuring both accuracy and consistency in risk assessment, Generative AI is poised to play a pivotal role in optimising underwriting processes.

Empowering Predictive Risk Assessment 

Generative AI’s ability to process and analyse complex data is immensely valuable in terms of building capabilities for predictive risk assessment. 

Analysing real-time and historical data, and identifying emerging patterns and trends, the technology enables insurers to develop more sophisticated models of risk assessment that factor in a wide range of parameters – past consumer behaviour, economic indicators and weather patterns, to name a few. 

These models allow insurers to assess the probability of specific claims, for instance, those related to property damage, or automobile accidents. Moreover, the predictive capabilities of Generative AI help insurers offer more tailored coverage and align their pricing strategies with a dynamic environment.

The ongoing risk monitoring and early detection of potential issues that the technology facilitates can also prove highly effective when it comes to fraud prevention. Through continuous analysis of data streams, AI identifies subtle changes and anomalous patterns that might be indicative of fraudulent activity. 

This empowers insurers to take proactive measures to identify possible fraudsters, prevent fraud and mitigate potential losses.

The robust predictive risk assessment capabilities offered by Generative AI thus serve to strengthen insurer’s business models, secure their services against fraud and other risks, and enhance customer trust and confidence in the coverage provided.

Unlocking Personalised Customer Service

In a digitally driven world, personalisation has emerged as a powerful tool to effectively engage customers and elevate their overall experience. By analysing vast amounts of consumer data, including interactions across the insurer’s digital touchpoints, Generative AI gains insights into consumer behaviour and preferences which enables it to personalise future customer service interactions.

For instance, analysing customer profiles, historical data, and various other factors, AI can make personalised policy recommendations, tailored to an individual customer’s specific needs, circumstances and risk profile. 

Simulating human-like conversation with near-perfection, Generative AI can also engage with customers across an insurer’s support channels, resolving queries and providing guidance or making recommendations based on their requirements. 

The personal touch that Generative AI brings to customer engagement, as compared to other more impersonal digital interfaces, coupled with the valuable tailored insights and offerings they provide, will go a long way towards helping insurers build long-term relationships with policyholders.

Charting a Responsible Course With Generative AI In Insurance 

The outlook for Generative AI across sectors looks bright, and insurance is no exception to the trend. Insurance firms that embrace the technology, and effectively integrate it into their operations, will certainly gain a significant competitive advantage through providing innovative solutions, streamlining processes, and maximising customer satisfaction. 

This optimism however must be tempered with an acknowledgement of concerns by industry stakeholders, and the public at large, around data privacy and the ethics of AI-driven decision-making. 

Given that insurance is a sector heavily reliant on sustained consumer trust, leaders need to address these concerns and chart a course towards responsible AI adoption to truly reap the benefits of the technology and usher in a bold new era of insurtech.

The post Generative AI’s Game-Changing Impact On Insurtech appeared first on Inc42 Media.