India has millions of small and micro-businesses without access to the financial system. Gurgaon-based Aye Finance aims to help such companies unlock massive business opportunities while creating a transformative social impact.
Founded in 2014 by Sanjay Sharma, Aye Finance strives to transform the micro-enterprise financing in India through innovations that enable effective credit underwriting while keeping a tight check on the asset quality. The startup leverages the most relevant technology to facilitate better financial inclusion and serve micro-enterprises across the country holistically.
“By providing inclusive finance at an affordable price to this ‘missing middle’, we have powered the economic transformation of over 2.6 lakhs micro-enterprises using world-class automation and data sciences to solve this problem that was considered intractable,” shared Sharma in an interaction with Analytics India Magazine.
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Aye uses artificial intelligence to drive non-linear growth, enhance efficiency and profitability through digitalisation and embed state-of-the-art data-driven decision-intelligence across all key business processes.
“We have developed and deployed advanced AI/ML solutions in most of our critical business processes in a short span of time. Some of our models to predict critical customer behaviour at a very granular level is unique and not even envisioned by any other players in the market to the best of our knowledge,” said Sharma.
“To contribute to the disadvantaged society has been on my sights since I started working 35 years back,” said Sharma. To fulfil this, he left a lucrative job at a leading housing finance company in UAE and returned to India.
This was a time when the MFI companies were battling the aftermath of the Andhra microfinance crisis. Sharma studied the market and took this opportunity to set up a new age finance company focusing entirely on lending working capital to micro-enterprises.
At the time, this sector was facing a credit deficit of INR 16 trillion. The resilience of the industry, despite the funding challenges, got him thinking about a solution to address the credit challenges of the sector, including thin files and lack of credit history.
He explored the possibility of using a cluster-based underwriting methodology for credit assessment of these grassroots businesses based on the field notes collected from meeting over 300 micro-enterprises across five cities and six manufacturing industry clusters. Building on the opportunity, Aye gave its first loan to a micro-entrepreneur in the ladies’ shoes manufacturing cluster of Delhi in March 2014.
Since then, the company has expanded its footprint to 210 branches across India and have allocated over 2,60,000 business loans to Indian micro-enterprises.
The company uses exploratory and prescriptive analytics on the customer base extensively. Aye uses bespoke AI/ML models to predict credit risk and conversion propensity of potential customers to offer loans.
“For Aye, the term cloud landed quite early in 2015 when we hosted our front line business application on AWS. The entire onboarding experience was great, and we were impressed with the ease of scalability,” he said.
Now cloud computing is extensively used to manage cloud resources and cost. “The autoscale and load balancing feature helps us to maintain smooth usage across applications. With features like serverless architecture, Kubernetes, and Lambda the cloud offers, it’s quite easy to maintain frontend, backend and middleware applications,” he added.
The data science and AI stack at Aye consists of a comprehensive data lake and AI/ML model development platform built primarily on Python. The data lake accommodates all types of structured and unstructured data, and the modelling platform communicates with the data lake for all the data needs.
“We use containerisation and APIs to serve these models to other business-facing software applications used in the organisation,” he said.
Sharma said they use various AI and ML models custom-built for their products and processes to predict all the events of interest throughout the customer lifecycle. The practice has helped to improve customer acquisition, collection, customising up-sell offers, etc.
“Several projects involving computer vision and speech recognition are in the pipeline to expand our AI portfolio by a large extent. These will bolster all our key business processes like underwriting, customer management, and collection even further and give us a significant competitive edge,” he further added.
Aye has managed a leadership position in lending to the underserved micro-entrepreneur sector in a short period. “Our innovative solution leverages data insights on industry clusters and uses process automation to bring unexpected economies to our business,” said Sharma.
Since its inception in 2014, Aye has grown from a single city to over 210 cities across 18 Indian states and has served over 2,60,000 grassroots businesses — disbursing over INR 3800 crores.
“Our revenues have been growing at an equally rapid scale. Compared to the financial year 2018-19, our revenue for the last financial year doubled to INR 410 Crores,” he added.