Lending businesses comprise an essential part of a country’s financial system. As the name suggests, their business is framed around credit to different entities such as individuals, businesses and even other lenders.
Since the inception of AI, the finance industry has been among the most impacted ones in different aspects. At one end, it makes credit analysis and prediction seamless and on the other hand, adaptation of artificial intelligence and automation causes a huge shift in employment opportunities in the finance sector.
Major banks and NBFCs act as the primary lending businesses in India and in 2026, things aren’t the same as a decade before! Check out the trends of the impact of AI on lending businesses in India.
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Top 3 ways in which AI impacts lending businesses in India
The impact of AI on different industries is different in magnitude.
Software and IT companies have experienced a huge shift in terms of acquiring the right talent who are skilled in harnessing the maximum potential of AI but for lending businesses the impact has been less noticeable but impactful.
Here are the aspects which are directly impacted by AI’s integration with lending businesses.
Assessment of Credit History
We all are aware of our good old credit scores which are managed by agencies like CRIF, TransUnion CIBIL, Experian and several others. Earlier lending businesses could reject your credit request if your credit score was below a certain limit.
With AI’s integration into this old-school system, credit history can now be studied in 10 times more detail, decoding your history along with more indepth markers such as regularity of payments, patterns of default in payments, most frequent default made and several others.
This brings out more insights than just credit score and improves decision making of a lending business, reducing loan defaults and enhancing profits through interest income.
Predicting Credit Behaviour of Customers
As AI brings out in-depth insights about an individual’s credit history, predicting their credit discipline becomes easier and accurate. If an individual has a credit history of say 15 years, predicting the period of their payment defaults and any associated patterns becomes possible thus, enabling better decision making and enhanced safety net for lending businesses.
Enhanced Customer Support
Customer support related tasks can be automated easily in 2026 through AI chatbots. As many NBFCs and banks have already started a gradual shift to integrating AI with their customer support systems, not only this makes resolutions faster but also promotes effective utilisation of manpower.
Thus, a customer support agent would only need to interfere when a situation is significant enough for human attention, saving both time and costs.
How will AI shape the future of lending businesses?
With this shift in the landscape of lending businesses, there are certain changes you can expect from 2026 as discussed below.
Automation of Tasks
Repetitive tasks can be easily optimised and automated through integration of AI. Such tasks include sending reminder calls and messages for upcoming payments to customers, entertaining requests such as loan foreclosure and loan settlement and asking for feedback on regular intervals.
For example, recently Poonawalla Fincorp automated its payment reminder calls by replacing its manpower with AI-based software, responsible for reminding customers about their EMI due date and asking them to maintain their account balance.
This acted as an early reminder for customers to avoid EMI bounce charges and helps the company recover its loan amount from customers
Upcoming Changes in Job Market
Since AI integration offers a speedy resolution to 80% customer queries and questions, lending companies tend to cut costs to enhance their profit margins. Investing in AI software rather than manpower is up to 60% cheaper, thus there is a huge shift in the job market as well.
Employees involved in repetitive tasks such as those mentioned above would be at the highest risk of losing their job to AI but the story will be opposite for Software and IT companies. The companies supporting this infrastructure would require a skilled workforce to deploy such agents which support lending businesses.
Ease of comparisons for Consumers
Customers can leverage AI tools to compare different lenders on different aspects. These can include factors like certain charges, rate of interest, repayment conditions and many others.
AI tools can help summarise documents and can help the customer focus on what matters. This is especially useful for people with limited knowledge who can use tools like Perplexity and ChatGPT to make an educated decision.
Key Takeaway
Lending businesses support a country’s growth ecosystem. Individuals gain leverage to invest in assets such as real estate or liabilities such as investing in a vehicle, thus supporting their needs plus, lending businesses support other businesses for their investment and working capital needs.
The integration of AI can improve repayment rates and recovery from customers through a deeper analysis of credit behaviour of an entity.
Alongside this, lending businesses can automate certain customer support related tasks which can reduce the turn-around-time of queries of customers.
Moreover, customers can leverage AI to compare different lenders and can understand the terms and conditions associated with a loan in a much clearer way using modern day AI tools.
In 2026, as you own a business, it’s time for your business’s growth story to reach potential investors and Pure Value Global helps you with its valuation services with more than 15 years of experience; ring us at +91 9311505553 or write to us at info@purevalueglobal.com today!