I have seen how artificial intelligence is slowly changing the way digital lending works in India. It started with using automation for simple, monotonous tasks. Now, artificial intelligence is moving into every part of the lending process. This includes checking credit, managing risk, catching fraud, understanding customers, and making lending feel more personal.
The bigger change is not just that more lenders are using AI, but how they are starting to think about the technology. Instead of using AI simply to make back-office work faster, lenders are increasingly using it as an intelligent layer to help them make better decisions about who to lend to.
This gives lenders an edge. It lets them look at large amounts of data very quickly, identify patterns that others might miss, and respond to changes in customer behaviour. This enables lenders to make more informed decisions on credit eligibility, risk assessment, and customer needs, while also creating a much smoother and more personalised experience for people borrowing money.
Moving beyond traditional credit assessment
I believe artificial intelligence can change how we decide if someone is eligible for a loan. Old ways of lending usually look at a list of money and personal details. Artificial intelligence allows lenders to look at bigger and more varied sets of data. This helps them see how people actually behave and gives a picture of a borrower’s money situation.
This is a deal for people who do not have a long credit history. By looking at how people spend money and move funds, rather than just old credit scores, artificial intelligence helps lenders see if a person can actually pay the money back.
We should not let artificial intelligence make every single choice alone. Artificial intelligence works best when it helps people on lending teams. It should help them sort through data and point out things that need an eye.
Making risk management more predictive
Artificial intelligence is also changing how lenders handle risk and fraud. Digital lending creates a mountain of data every day. It is getting too hard for people to catch every risk just by using manual checks or simple rules.
Machine learning models can scan these datasets to find anomalous behavior. These models can spot fraud tricks and can also see if people are starting to struggle with their payments. This lets lenders act before a problem happens rather than just waiting until they lose money.
Understanding customers and enabling personalisation
There is another chance to use artificial intelligence for customer profiling. Every borrower is different. They have ways of spending, different amounts of cash, and different needs. A “one-size-fits-all” plan does not work for everyone.
Artificial intelligence can help lenders look at how people use money to understand groups of customers. These insights help lenders decide on the loan sizes, how to engage with customers and what payment options to offer.
Making things personal is about more than suggesting a loan. It is about making the whole journey feel right. It means talking to customers at the time and helping them stay on track with payments. For lenders, this builds trust and long-term relationships instead of just finishing one loan and moving on.
Responsible AI must remain central
As artificial intelligence takes a role in money decisions, we have to be careful. Lending decisions change lives and affect how people use money. We cannot just care about speed and efficiency.
Lenders must be very careful about how they use data. They have to think about privacy, being honest, and making sure artificial intelligence is not biased. Even a smart model can fail if the data it learns from is wrong or unfair.
We still need humans in the loop. This is especially true for cases that need a person to understand the full story. Lending teams must be able to check what the artificial intelligence says and step in when something looks wrong.
Building the right AI infrastructure
The next step is not just testing ideas. Lenders need to build the foundation for using artificial intelligence across their operations. To do this, you need data systems, safe technology, and people who are responsible for how the models act. Artificial intelligence cannot add value if it is built on top of messy data or outdated ways of working.
I also expect to see Generative AI and Agentic AI helping with customer service, paperwork and collections. These will only work well if they fit into the way a company already works.
From AI adoption to competitive advantage
A competitive advantage does not come from just having more AI features. It comes from using intelligence to solve real problems for customers while keeping their trust.
Lenders who have data, good tech and smart human oversight will be the ones who make the best decisions, manage risks well, and treat customers right.
The future of lending is not about replacing people with machines. It is about using technology to help people do their jobs better. The real goal is to build a lending world that’s fast and smart but also honest and focused on the person borrowing the money.
The author is Amit Bansal, Co-founder, VimanoTech.
Disclaimer: The views expressed are solely of the author and ETCIO does not necessarily subscribe to it. ETCIO shall not be responsible for any damage caused to any person/organization directly or indirectly.
