Digital lending with AI and ML: a boon for unserved SMEs and microenterprises

Digital lending with AI and ML: a boon for unserved SMEs and microenterprises

It’s critical to reward business travellers after Covid-19. Employees will be able to network more and so be more productive as a result of this. From the company’s standpoint, it will assist them in strengthening their customer relationships while also allowing them to develop their reputation. Additionally, it aids in staff retention as well as overall corporate success.

According to current research, Asia is the fastest-growing business travel destination. India, for example, is witnessing an increase in business travel and will be among the top five business travel markets by 2022. It will be fascinating to observe how corporations and online travel agencies (OTAs) respond to these new trends in order to create a win-win scenario for everyone.

Many digital lending platforms have sprung up in India in recent years because of the increased accessibility of cellphones and the internet. Microfinance is a rapidly expanding industry. According to several assessments, India’s microfinance business has the potential to develop at a CAGR of 40% by 2025. The government is also eager to boost this industry in order to ensure inclusive growth.

indian startups are leveraging tech to bridge the gap in smes lending

This prompted the government to promote banking digitalization, prompting fintech to hurry to fill the holes, notably in the digital lending area. India is now not just one of the world’s fastest-growing economies but also one of the world’s major fintech hubs. According to BLinC Investment Management’s newest analysis, the fintech industry’s total market size has expanded to USD 31 billion. India is predicted to have around 6,000 fintech companies, with 16 per cent of them engaging in lending.

There is a rising need to ease the lending process in order to preserve systemic stability and safeguard SBMs from abuse. Because of the nature and size of their operations, small merchants frequently require small-ticket working capital loans for short periods of time to stay afloat. Traditional lending institutions, on the other hand, avoid this market. As a result, a large number of these shops turn to unofficial loan sources.

artificial intelligence applications for lending and loan management | emerj artificial intelligence research

They are often vulnerable to loan sharks – the so-called sahukars – rather than traditional lenders like as banks or NBFCs, due to a lack of collateral, a trustworthy credit score, or being new to credit (NTC). Taking out loans with exorbitantly high-interest rates adds to the vicious cycle.

Fintechs have emerged as game-changers in the micro-credit landscape in this country. Fintechs are bringing about a transitory shift in microlending, thanks to developing technologies like AI, machine learning, and big data. New-age fintech models are developing a robust digital lending ecosystem to bridge the credit gap for micro-entrepreneurs based on the assumption of a data-driven digital footprint.

User-generated data is collected in a variety of contexts, including bank accounts, shopping patterns, GST returns or statements, and lifestyle aspects, including cab use, movie viewing, and applications we use on a daily basis. When a micro-entrepreneur, for example, sells or buys anything online, the transaction leaves a trace. For tax filing, invoice data for digital purchases are automatically submitted to the GST system.

As more consumers and small companies deal online, their digital footprints grow, providing a wealth of data from which to identify trends and extract actionable insights. Complex and unstructured data is being modelled innovatively with the help of AI to develop efficient workflows and drive decision-making. AI can effectively address sectoral challenges to improve lending efficiency by providing a faster and improved onboarding process, better credit underwriting at lower costs, faster decision-making, improved risk management techniques, fraud detection, enhanced security and compliance, credit monitoring, and debt recovery, and so on.

For example, AI/ML-based bank statement analyzer technology evaluates operational data (such as debit and credit transactions, transfers, and end-of-day balances) from a consumer’s bank statement and converts it into intelligent data that can be customized for each lender.

Automating the whole loan disbursement process, including document verification and credit bureau checks, has resulted in considerable cost savings, in addition to eliminating biases in the application process.

impact of digital lending on small & medium enterprise growth - finezza blog

In addition, integrating with partners to provide real-time KYC and validation of client profiles based on government data has sped up the process, making it smoother and more accurate. Calculating applicants’ creditworthiness based on their digital footprint enables businesses to not only obtain loan applications digitally but also to provide them with the appropriate loan amounts.

To offer credit to the broader unserved and under-served portions of society, digitization and automation, followed by joint efforts between credit bureaus and other fintech, are becoming the new standard.

Digital lending is being redefined through collaborative models that are highly scalable and accessible to the bottom of the pyramid, thanks to technology and data. Of course, all of this vital information should be used with extreme caution and with the agreement of the users to ensure that their privacy is not threatened. Fintech is aiming to reshape the microfinance ecosystem so that urban and rural MSMEs have equal access to financing and India becomes a more inclusive country.

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