Aye Finance pilots Generative AI model for image-based underwriting of trading businesses

NEW DELHI, March 4, 2026 /PRNewswire/ — Aye Finance, India’s leading provider of business loans to the underserved micro-scale MSMEs, has completed a pilot that uses the predictive capability of Gen AI technology, which will enhance its formal credit to the trading businesses in tier 2 and beyond cities. The cutting-edge solution developed in-house utilises Generative AI and Machine Learning (ML) models to estimate business sales directly from images of store premises and other parameters. This significantly reduces the ‘cost-to-serve’ for the micro-enterprise segment.

Aye Finance is the first NBFC to have received equity investment from Google Capital in 2018. It set up its Data Science and Artificial Intelligence Unit in 2019 and has successfully deployed many customised ML models at key processes across the customer lifecycle. This optimizes the unit economics and allows inclusion of a larger population of the grassroots businesses.

The newly developed system serves a critical segment of trading stores by transforming their unstructured data—specifically, store images—into actionable financial insights. It is built on Aye Finance’s extensive internal datasets and is rigorously tested for consistency.  

By using a Multimodal Large Language Model (MLLM) integrated with proprietary ML models, the solution provides a reliable estimate of monthly sales of a garment store or a grocery store using store images as input.

This breakthrough innovation significantly reduces reliance on subjective individual judgment, ensuring a more standardised and fair income estimation process. By automating these complex components of underwriting, Aye is now able to process applications with unprecedented speed with high levels of consistency in underwriting. This opens up the possibility of extending this methodology to other sectors and industries beyond trading by Aye.

“Our leadership in lending to the underserved segment of micro MSMEs has been rooted in superior operational efficiency,” said Mr Sanjay Sharma, Managing Director, Aye Finance Ltd. “This GenAI integration builds on our established efficiency. By automating income estimation through Generative AI, we will substantially reduce manual fieldwork with an accelerated, data-driven system that increases both the speed and the reliability of our credit decisions. Aye has demonstrated that lending to micro-enterprise business is a rewarding opportunity, when illuminated by our advanced, technology supported lens.”

For 60 million micro-entrepreneurs in India’s tier 2 cities and beyond, the lack of formal accounting records and ‘paper trails’ has traditionally been a barrier to credit. As a Middle-Layer Non-Banking Financial Company (NBFC-ML), Aye Finance has been successfully solving the credit challenges of the sector since 2014 and offers tailored working capital and expansion loans, typically secured against working assets or property. The company recently closed a successful IPO, raising INR 1050 crores and further strengthening its capital base.

About Aye Finance Ltd

Aye Finance is a non-banking financial company – middle layer (“NBFC-ML”) focused on providing loans to micro-scale “MSMEs” across India. Aye offers a range of business loans for working capital and business expansion needs, against hypothecation of working assets or against security of property to customers across manufacturing, trading & service sectors. Aye is among the leading non-banking financial companies (“NBFCs”) providing business loans to the largely underserved micro-scale enterprises in India, with 586,825 active unique customers across 18 states and 3 union territories and with assets under management (“AUM”) of ₹ 60,276.22 million, as of September 30, 2025. Aye offers small-ticket business loans with an average ticket size (“ATS”) on disbursement of ₹ 0.18 million to micro enterprises. The lenders’ expertise in underwriting business cash flows of a variety of business clusters has enabled it to maintain stable credit costs and allowed the Company to profitably scale up operations.

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