AI & RPA can assist NBFCs with quick decision-making: Sanjay Sharma, Managing Director of Aye Finance

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In an interview with TechGraph, Sanjay Sharma, Managing Director of Aye Finance said, “Technologies like AI and RPA can also assist NBFCs with quick decision-making.”

Read the complete interview:

TechGraph: Could you help explain how far Aye Finance has come since its existence? From when it began to where it is now?

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Sanjay Sharma: Aye is the only scaled, Pan-India player providing unsecured small-ticket business loans to a large credit-starved micro-enterprise segment. Aye has cracked this difficult-to-lend segment with its unique cluster-based credit appraisal approach & optimally digitized phygital model.

With over 60 Million micro-enterprises operating in India, this segment represents a vital engine for job creation and economic growth. Ironically these micro-entrepreneurs are excluded by strict hard collateral and formal documentation requirements, typically the primary deciding factors in the traditional credit risk assessment process.

In addition, customer perceptions have driven self-exclusion, leaving this critical sector reliant on informal lenders for their credit needs, often paying extorting interest rates that can reach up to 20% monthly.

A 2012 report by IFC says that this sector faces a credit gap of over INR 16 trillion. It was clear to us that India’s growth will not be complete without the advancement of this sector.

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We founded the company in 2014 as a platform to allow micro-enterprises in the country access affordable and customized credit solutions for their working capital and fixed capital needs.

We gave our first loan to a shoe manufacturer in the ladies’ shoe cluster of Delhi in 2014 and since then we have solved the credit challenges of over 4,50,000 grassroots businesses having disbursed over INR 5200 crores to the sector. Lending to micro enterprises has been a less traveled path for banks and financial companies and hence it is satisfying to have established an innovative paradigm of our lending approach.

TechGraph: How is Aye Finance utilizing its sectoral expertise and technology to solve the unsolved credit gap for micro-businesses and SMEs?

Sanjay Sharma: Aye has managed a leadership position in lending to the unbanked micro-entrepreneur sector having established an innovative paradigm of its lending approach which hinges on the advancement in data analytics and technology. Aye’s proprietary “Cluster-based credit assessment” methodology allows it to make robust lending decisions from insights derived from cluster-specific data points.

Detailed field research, which involved meeting over 300 micro-enterprises spanning 5 cities and 6 manufacturing industry clusters- lac bangles in Jaipur, brass casting in Aligarh, sports goods in Meerut, shoe-making in Agra, and shoes and garments in Delhi threw up the possibility of using a cluster-based underwriting methodology for credit assessment of these grassroots businesses. We also use a variety of credit assessment tools that focus on data analytics, customer profiling, and behavioral science for risk selection.

We have been the pioneers in developing AI and ML models to further ease the access of credit to this sector and have deployed advanced AI/ML solutions in most of our critical business processes. Our models predict critical customer behavior at a very granular level which has helped us improve our lending decisions, and brought improved efficiencies in our customer acquisition and collection processes, along with allowing us to offer customized solutions, as well as up-sell, offers to our target customer segment.

By leveraging the advancements in technology and through a deep-rooted understanding of various industry clusters across India, Aye has successfully enabled the inclusion of over 4,50,000 micro enterprises having disbursed over INR 5200 crores to them.

TechGraph: How is Aye Finance facilitating the entire finance process digitally?

Sanjay Sharma: Aye Finance has addressed the credit requirements of this sector by customizing its entire business model to the unique needs of this first-to-credit segment having small ticket loan requirements with no collateral to offer and limited tech experience.

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Sensitive to the sector’s limitation in accessing online platforms for credit and cognizant of the merits of adopting technology for cost efficiencies, we designed the ‘Assisted Fintech Approach’ to effectively solve the credit needs of the sector.

This hybrid approach was designed to achieve economies of scale by leveraging technology while delivering and servicing the loan as per the comfort of the grassroots businesses that have not yet fully embraced the internet for accessing credit. For managing the risk innovatively and radically reducing operating costs, Aye moved away from the traditional “people- and judgment-intensive” approach and designed its proprietary analytics-powered “Cluster-based Credit Assessment” methodology. This methodology draws insights from the cluster data points and corroborates them with risk scorecards to lend to the segment.

Aye ensured the lowest unit cost of loan origination for business lending in India by building these processes on a cloud-based android CRM platform that integrates the loan origination, assessment, disbursal, servicing, and collection processes allowing for improved accuracy levels and turnaround times.

Aye has also developed predictive AI/ML models to effectively control delinquencies and maintain the quality of its asset book. The effectiveness of its tech-powered assessment tools and collection algorithms is evident when one looks at our NPA levels which have remained below industry levels right since inception. The successful implementation of this hybrid approach delivered profits for Aye Finance within 4 years of commencing operations.

TechGraph: How is technology transforming the NBFC industry? Do you think the trend had taken hold even before the pandemic-induced disruptions?

Sanjay Sharma: Abundant innovation and rich technology advancement in the BFSI sector have brought about a broad spectrum of benefits ranging from fraud and risk management, to decreased costs, and improving the inclusion of the excluded sector into the formal economy.

The adoption of Artificial Intelligence and machine learning models, big data analytics, and blockchain technologies by fintech players have allowed for customized products and services and radically transformed customer experiences. With AI-ML combined models, the ‘one size fits all approach has almost ceased to exist.

Now, NBFC lenders can adopt a personalized approach to underwriting by incorporating segment-definitive guidelines, empowered by alternative data sources, and applying scorecard-based credit decisions.

Technologies like AI and RPA can also assist NBFCs with quick decision-making. Further, technologically-advanced NBFCs can revolutionize the manual, time-consuming, human judgment-based underwriting process to provide instant, real-time approvals.

As for the pandemic-induced disruptions, the BFSI sector had been leveraging technology even before the pandemic struck the world, but there is no denying that COVID did accelerate the rate of adoption as well as the extent of innovation creating agile business models with technology at its core. And the players that have a “digital-first” approach have the advantage to create scalable sustainable businesses.

TechGraph: What are the new trends in the NBFC industry?

Sanjay Sharma: RBI policy to facilitate collaboration between banks and NBFC and provide funds to the priority sector at affordable cost has improved the flow of credit to the unserved and underserved sectors of the economy. In the co-lending model, banks and NBFCs make joint decisions regarding lending to an enterprise. It’s expected to be a mutually beneficial move for all parties involved, including the borrower.

However, NBFCs usually cater to a segment that traditional large-scale financial institutions don’t consider their typical borrowers, but this new model can help the segment reach a wider audience. Simply put, it can be a win-win situation for all when organized and executed correctly. This is currently one of the biggest trends in the sector.

TechGraph: How do you see technologies, namely Artificial Intelligence and Machine Learning, with regard to their relevance across the NBFC? What does the future look like?

Sanjay Sharma: Undeniably, technology has been a game-changer for the sector. With an increase in interest and investment in the NBFC segment, technology has now become the cornerstone for smooth operations.

Aye Finance’s ML journey began in September 2018 when Google chose us as one of the ten startups for their flagship program Launchpad Studio. After 6 months of being mentored by experts from Google, in March 2019, we set up our in-house Data Science and AI department (DSAI).

We have created a robust strategy to gradually embed effective data-driven decision-making, using better insights and predictive AI/ML models and optimum intelligent automation across all business functions amenable to positive interventions/disruptions. Considering the pace at which technology is evolving and how the NBFC players are integrating it into their business, it’s safe to say that the future will be a tech-powered one for NBFCs.

TechGraph: What is the roadmap for Aye Finance going forward?

Sanjay Sharma: This year should see us once again demonstrate our ability to grow our loan book, improve the credit quality of the portfolio and deliver profits for our shareholders. We will continue our focus on AI-driven automation that will enable quicker scaling up and enhance efficiency. The focus on team engagement that we resolutely followed even through the years of disruption, will continue to ensure a motivated and high-achieving workforce.

We also want to create and integrate more end-to-end data pipelines for most data flows within the organization, improve the features of our product offerings and expand our reach to include a larger population of underserved grassroots businesses into the folds of formal financing.

In the last eight years, we have institutionalized a mission to excel at serving micro businesses through an engaged and achievement-oriented team. We drive for optimal profits while balancing it for lasting social impact. This year will help us build momentum in this journey.

Krishna Mali
Krishna Mali
Founder & Editor of TechGraph.

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