The MSME sector in India suffers from many barriers in the path of year-on-year growth. One of these major barriers is the lack of access to credit. But with the introduction of artificial intelligence to the financial sector, the conditions are expected to change soon.

There have been many questions raised regarding the fairness of the credit model in India. Especially when it comes to providing credit to SMEs, there is an acute lack of fairness on the part of both banks and non-banking financial institutions (NBFCs). The current algorithm-based models that dictate lending decisions hamper the growth of smaller businesses, whereas enterprise-grade businesses are able to access credit easily.

How AI will Bring About Financial Inclusion

Instead of depending only on the financial history of the borrower, AI-based models take into account a large number of aspects. These include spending style, all possible income sources, social media reach, etc. amongst others. So, by using this cutting-edge model, a much clearer picture of the borrower’s financial situation can be gauged.

As per a 2022 report by McKinsey & Company, AI-powered credit scoring can lead to a 10-15% increase in loan approval rates for underserved borrowers. This can significantly benefit the MSME sector in India, where a large portion of businesses lack a traditional credit history.

According to a 2023 report by the Federation of Indian Micro and Small & Medium Enterprises (FISME), the MSME credit gap in India is estimated to be around ₹25 lakh crore (US$312.5 billion).

A 2022 PricewaterhouseCoopers (PwC) report suggests that AI-powered lending platforms can potentially bridge up to 25% of the global MSME credit gap.

The Potential of Alternative Data Sources

A 2021 study by CRIF India, a credit information bureau, revealed that 80% of Indian MSMEs lack a formal credit history. This highlights the importance of alternative data sources for AI-based credit scoring. Beyond financial history, AI can leverage alternative data sources to provide a more holistic view of an MSME’s creditworthiness. This includes:

• E-commerce transactions: Analyzing purchase and sales data on e-commerce platforms can reveal valuable insights into a business’s operational efficiency and customer base.
• Supply chain data: Understanding an MSME’s position within its supply chain can indicate its stability and potential for growth.
• Social media sentiment: Analyzing online reviews and social media engagement can provide insights into a business’s reputation and brand awareness.

Increased Efficiency and Transparency

AI can also speed up the entire process of scrutinizing fiscal movement right up to the final step of issuing credit. This is largely beneficial for SMEs, because in many cases, even if a small business is worthy of credit, it can still take them a long time to receive it.

Furthermore, AI-based models can provide reasoning behind every credit decision taken. This transparency can build trust with borrowers and allow them to understand the factors influencing their loan approval or rejection.

Fairness and Mitigating Bias

As per a report by the Reserve Bank of India (RBI), MSME loan disbursements grew by 12% year-on-year in the first half of 2024. This indicates a positive trend in MSME lending even before widespread AI adoption. However, to further boost growth, fairness and transparency are the most important factors within the AI-led process. While there may be prejudices towards gender, race, or religion in other lending models, with the help of AI, these biases can be reduced or even eliminated altogether. This will ensure that loans are granted based on an objective assessment of an MSME’s financial health and not discriminatory factors.

However, it’s crucial to ensure that the AI models themselves are built and trained on unbiased data sets. Regular audits and monitoring are necessary to prevent algorithmic bias from creeping into the lending process.

Roadblocks Still Exist

While we are still at the beginning stage of introducing AI-based systems to banks and NBFCs, there are many aspects to take care of before they can become a widespread phenomenon. From training employees to personalization, and most importantly trust, the Indian financial landscape is not fully ready for this change.

But, early signs of change are already visible. Lending to MSMEs has already increased in 2024, and the government is also pitching in. The interim budget announced a whopping INR 22 crore for lending to the MSME sector, a massive 40% increase from last year.

With the introduction of AI, this budget can be utilized in the most efficient and inclusive way possible. This will finally allow many businesses to break the glass ceiling and compete with enterprise-grade businesses.