The rise of AI: Can it be a boon for MSMEs?

Touted as ‘India’s growth engine’, the Micro, Small and Medium Enterprises (SMEs) play an instrumental role in India’s economic development and add to the country’s entrepreneurial spirit. MSMEs account for approximately 6.3 crore businesses in India which contribute heavily towards job creation and economic growth. According to the Ministry of MSME's annual report, MSMEs are responsible for around 30 per cent of India's total GDP and provide jobs to over 110 million people. Given that the majority of these MSMEs operate on a micro and small scale, most of them are unserved or underserved when it comes to availing credit facilities, owing to very few formal creditors at the grassroot level. 

As per the report ‘BLinC Invest MSME Lending Report 2022’, currently, the formal lending sector which includes Banks and NBFCs cater to less than 15 per cent of the total credit demand of MSME and there is a huge credit gap of Rs 25 trillion in the MSME sector that can be potentially addressed effectively through use of data and new technologies such as Artificial Intelligence and Machine Learning  models. 

Credit challenges for a modern-day MSME 

Access to finance is a key obstacle to the growth of MSMEs in emerging markets. Moreover, the traditional lending processes are time consuming and extremely scrutinising. To ensure systemic stability and protection against the same, there is a strong necessity to streamline the credit process.  

Owing to the nature, scale and size of businesses, micro and small players often need timely and small ticket working capital loans for short tenures to keep their operations afloat. However, conventional lending institutions often shy away from servicing the needs of this sector. Hence, a major section of these businesses turns towards informal lending sources, which are unregulated and charge exorbitant interest rates and charges that add to the burden of a MSME borrower. In absence of a reliable credit score, collaterals, or being new to credit, often render the MSME borrower to fall in the vicious cycle of informal lenders, thereby adversely impacting the operations.  

How AI & ML are transforming the financial services industry? 

Productive technology tools like AI can effectively address sectoral challenges for MSMEs to avail lending through a quicker and improved onboarding process. This includes faster decision-making, better credit underwriting at reduced costs, improved risk management, enhanced compliance, fraud detection, credit monitoring, debt recovery, and more. For example, bank statement analyzers based on AI/ML assess operational data from a bank statement and translate it into intelligent data that can be tailored for each lender. 

Automating the entire loan sanctioning and disbursement process, from the review of documents to credit bureau checks, etc. aids in achieving significant cost optimization, besides removing biases in the application evaluation process. Analyzing the creditworthiness of the applicants based on their digital footprint also helps lenders, not just to source loan applications digitally but also to extend the loan amounts to eligible applicants. 

Fintechs changing gears for MSMEs 

Fintechs have emerged as the new change-enablers in the country’s MSME space. Leveraging emerging technologies such as AI, ML and Big data, FinTechs are bringing an instrumental transition for the unserved MSME businesses. 

To understand how FinTechs are enhancing their capabilities to support the credit needs of MSME borrowers, let us look at how they are changing the game: 

Improved risk assessment: AI and ML algorithms can analyze a borrower's credit history, financial statements, and other data points to assess their creditworthiness accurately. This can reduce the risk of default and enable lenders to offer loans to MSMEs that may not have been eligible for credit in the past. 
Customized loan products: AI and ML algorithms can use data from a borrower's financial history and behavior to offer personalized loan products that suit their specific needs. This can assist MSMEs access credit lines that is tailored to their business requirements. 
Faster & cost-effective loan processing: AI and ML algorithms can seamlessly and quickly analyze large amounts of data to evaluate a borrower's creditworthiness thus reducing the time taken to process loan applications. This can be particularly beneficial for both the entities i.e., MSMEs who require urgent funds to finance their business operations and for the lender to cut-down the cost of servicing a customer. 

As more and more businesses transact digitally, their digital footprints expand thereby creating voluminous data to identify patterns and extract relevant actionable insights. With the assistance of AI and ML, crude and complex data is being modeled innovatively to create efficient workflows and drive decision-making. 

Conclusion 

Digitisation and automation, followed by collaborative efforts between NBFCs and various FinTech companies, are narrowing down the credit gaps to the largely unserved and under-served MSMEs. Powered by AI and ML and fueled by data, digital lending is now being revamped through innovative and collaborative models that are highly scalable as well accessible. With these technologies, fintech players are remodeling the finance ecosystem and making the MSME lending space more inclusive. 

Views are personal. The author is MD, Poonawalla Fincorp