The Role of Disruptive Technologies like AI & ML in Digital Lending

The Financial institutions are constantly evolving their businesses. They are continuously changing to adapt to regulatory changes, respond to competitive environment, and keep up their focus on preparing for the future. One of the keys of preparing for the future is Digital transformation. Financial services have always been adopting digital capability to make it a competitive advantage. This is the newest chapter in the Indian FinTech industry’s growth story. It has revolutionized the way we lend and borrow forever.

Getting a loan used to be a tedious, time-consuming process with multiple documents followed by lengthy approval process and long disbursement turnaround time. Now, the digital adoption has made it possible to make it an entirely paperless process, and the money is in the borrower’s bank account by reducing the turnaround time from days to hours. And with MSMEs thirsting for a reliable source of quick financing, the Indian digital lending market is on a fast growth track.

But the expeditious growth of digital lending is not limited to the Indian financial markets. The global digital lending platform market size was valued at $ 7.04 billion in 2022 and is expected to register a compound annual growth rate (CAGR) of 26.5 percent from 2023 to 2030.

Digital Adoption – The Customer’s Accelerated Journey
Over the past few years, with smartphones and increasing access to the internet, customers are increasingly adopting digital financial services and financial services are able to execute direct to consumer businesses. The pandemic has accelerated the adoption rates making India the world’s largest FinTech centre. To keep up with this accelerated demand, banks, NBFCs, and digital lending platforms are empowering themselves with disruptive technologies including Artificial Intelligence (AI) & Machine Learning (ML).

There were already established solutions in place to identify potential fraud and reduce the risk of lenders. But artificial intelligence and machine learning makes it possible to balance customer experience and at the same time manging the fraud risk. Despite placing numerous checks and balances to reduce lenders’ risk, we can now offer our customers quick access to financial products and a seamless user experience.

The Role of Artificial Intelligence & Machine Learning
The financial services have always had a rich consumer data and insights repository. AI & ML has enabled them to apply advanced analytics and find the hidden patterns to get invaluable insights into customer behavior, and patterns. Not only do they process data at an incredible speed but also do so with greater accuracy.

AI/ML can effectively address procedural challenges and design an efficient lending process with quick and improved onboarding, better credit underwriting, reduced costs, faster decision-making, improved risk management techniques, fraud detection, enhanced security and compliance, credit monitoring, debt recovery, and customized service.

Simply put, AI/ML adoption is no longer a choice for digital lending services. Almost every player in the

industry is trying to establish a direct-to-customer business model. To do so safely, we must develop new digital interfaces with the correct checks and balances.

Reducing Risk & Improving Fraud Prevention
Another vital aspect of using AI/ML in digital lending is combating the risk of fraud. Even if one identifies the control points in a digital lending process, placing too many checks can ruin the consumer experience. So, what can AI/ML do?

•Secure our lending transactions while allowing speed and convenience to customers.

•Quick document verification at the source.

•Rapid response to red flags in customer behavior patterns.

•Reduce false positives in the system to limit the risk of fraud.

Digital financial service providers can open new possibilities by deploying alternate data with AI/ML. Alternate data can offer the right inputs to an AI-enabled system, so it can perform an advanced objective analysis of the data. Biometric face recognition and video KYC can play a vital role in preventing identity fraud. Empower your KYC with face-match technology for better accuracy and speed. Another prominent use case of AI/ML in digital lending is voice biometrics. It enables better compliance and reduces the risk of fraudulent applicants.

AI/ML may be touted as disruptive technologies, but they hold the key to the future of lending services. AI-led digital lending services will not only help financial institutions reduce the risk of fraud but also drive a more integrated lending experience for customers worldwide

Intelligent use of alternate data with AI/ML in digital lending can help lenders design a credit journey that verifies information from the source and does not rely on credit scores alone. Leverage the right technology to identify and authenticate customers, reduce friction, and risk in the onboarding process, and build a smooth customer experience.

Influencing the Digital Lending Industry
AI/ML can not only improve business prospects for banks, NBFCs and independent businesses offering digital lending services. It can also enable the lending industry to promote equitable lending:

•Empowering micro-financing services for MSMEs.

•Automate internal services and improve customer focus.

•Streamlining & automating operational processes to reduce time and cost.

•Design a new-age credit scoring process optimized for individual situations.

When it comes to fraud prevention, financial services must stay one step ahead of fraudsters. AI/ML may be touted as disruptive technologies, but they hold the key to the future of lending services. AI-led digital lending services will not only help financial institutions reduce the risk of fraud but also drive a more integrated lending experience for customers worldwide.