There was a time when applying for a loan meant carrying thick files, photocopies of documents and waiting days, sometimes weeks, for an answer. Today, the lending experience is beginning to look very different. Thanks to artificial intelligence (AI), many lenders are now approving loans faster, cutting paperwork and making borrowing smoother than before.
But this shift is not just about speed. Behind the scenes, lenders are using technology to better understand borrowers, reduce fraud and improve access to credit, especially for people who may have been overlooked by traditional systems.
The lending industry has long depended on manual checks. From document verification to credit assessment and approvals, most processes involved several layers of human intervention. This often slowed things down.
Now, AI is helping lenders simplify many of these steps.
“Traditionally, loan processing was manual, document-intensive, and dependent on manual judgement. There were multiple touchpoints for verification, underwriting, and approval,” said Vineet Venugopalan, Chief Information Officer (CIO) at SMFG India Credit, a well-known NBFC (Non-Banking Finance Company).
He explained that AI is helping lenders across the entire lending cycle — from customer onboarding and credit checks to fraud detection and risk monitoring.
“Several processes are being executed digitally with minimal manual intervention. This has significantly reduced approval timelines while improving consistency and operational efficiency in decision-making,” Venugopalan said.
In simple terms, what once took days can now happen within minutes.
One common question borrowers may have is: how does AI decide who gets a loan?
The answer is more detailed than many realise.
Earlier, loan approvals depended heavily on income documents and credit scores. While these still matter, AI-based systems now look at a wider picture.
“AI-led systems look at different signals to assess the borrower’s ability to repay in addition to income and credit scores,” Venugopalan said.
For instance, lenders may examine bank transaction patterns, spending habits, cash flow consistency and repayment behaviour to understand whether a person can repay a loan on time.
The system also tries to answer key questions: Is the loan application genuine? Can the person repay? Will repayments happen on time?
These insights are drawn by comparing borrower information with patterns learned from thousands of earlier customers.
However, Venugopalan stressed that AI does not make decisions on its own.
“AI does not function in isolation. Lending decisions are guided by pre-defined credit policies, regulatory requirements, and internal risk frameworks,” he said, adding that human oversight remains critical.
For regular borrowers, the biggest benefit is convenience.
“Loan applications that previously took several days or longer can now often be processed within minutes through digital onboarding and automated verification systems,” Venugopalan said.
This means less paperwork, fewer branch visits and quicker approvals.
AI is also helping lenders expand access to credit. Borrowers with little or no formal credit history, such as self-employed individuals or first-time borrowers, may find it easier to be assessed through alternative financial signals.
At the same time, digital lending is becoming more personalised. In some cases, lenders can recommend products based on a borrower’s financial profile and needs, making the process more relevant and customer-friendly.
Even as digital lending becomes smarter, experts say caution is necessary.
One key concern is algorithmic bias. If AI models are trained using incomplete or skewed data, some borrowers may face unfair outcomes or exclusion.
“There is a need to maintain a balanced approach between automation and human judgement,” Venugopalan said.
He also pointed to growing concerns around data privacy and cybersecurity, especially as lenders increasingly rely on digital information and automated systems.
Another challenge is transparency. Sometimes, highly advanced AI systems can make it difficult to explain why a particular loan was approved or rejected.
That is why industry experts believe strong governance, regular monitoring and human intervention will remain important.
AI may be changing the way loans are processed, but it is not replacing people entirely. Instead, it is helping lenders make faster and better-informed decisions while improving the customer experience.
For borrowers, this could mean one thing: quicker loans, easier access and fewer paperwork headaches.
Yet as technology takes a bigger role in lending, the balance between innovation and trust may ultimately decide how successful digital lending becomes in the years ahead.