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AI for Borrowers: 6 Things to Know Before Applying

When applying for Buy Now Pay Later in India, know that AI lenders analyze more than just your CIBIL score. They scrutinize your digital footprint, bank habits, and even the device you use to make a decision in minutes.

TrustyBull Editorial 5 min read

Why AI in Lending Changes Everything for You

Did you know that some lenders can decide on your loan application in less than three minutes? This speed is possible because of Artificial Intelligence (AI). When you apply for a service like Buy Now Pay Later in India, you are probably not dealing with a person. You are dealing with an algorithm. This changes the rules of borrowing completely.

In the past, a loan officer would look at your application and your CIBIL score. They might use their judgment to approve or deny your request. Today, an AI system looks at hundreds, sometimes thousands, of data points about you. This includes your online behaviour, your shopping habits, and even how you fill out the application form.

This is not science fiction. It is happening right now. Understanding how these AI systems think is critical. Your financial future could depend on data you did not even know lenders were looking at. This new world of lending requires a new approach from you, the borrower.

The 6 AI-Driven Factors You Must Check Before Applying for Buy Now Pay Later in India

Before you hit 'submit' on that next application, pause. Your success depends on understanding what the AI is looking for. Here are six crucial things to consider.

  1. Your Digital Footprint is Your New Resume

    Lenders now look beyond your credit report. They analyze your digital footprint. This includes your public social media profiles, the apps on your phone, and your online payment history. An AI might see frequent posts about job loss as a risk. On the other hand, a stable online presence and timely online payments for utilities can be a positive signal. Before you apply, review your public profiles. Ensure your utility and mobile bills are paid on time through digital channels.

  2. Alternative Data Matters More Than Ever

    Many Indians have a thin credit file. This means they do not have a long history of taking loans or using credit cards. AI lenders solve this by using 'alternative data'. This is information like:

    • Your mobile phone recharge history
    • Regular payments for subscriptions
    • Your monthly electricity and gas bill payments
    • Your educational background
    Consistent, on-time payments for these services tell an AI that you are a responsible person, even without a formal credit history. Ensure your name and address are consistent across all these accounts.

  3. The Speed of Your Application Can Be a Red Flag

    This might surprise you. AI systems can track your behaviour while you fill out the application form. If you rush through the pages, make many corrections, or copy and paste information into personal fields like your name or PAN, it can be flagged as suspicious. This behaviour mimics that of fraudsters who use stolen data. The simple advice is to slow down. Read every field carefully and type your information accurately.

  4. Your Bank Account Habits Are Under a Microscope

    If you grant a lender access to your bank statements, its AI will perform a deep analysis. It looks for more than just your balance. It checks for a stable monthly income, a healthy average balance, and bounced cheques or ECS debits. Frequent small cash withdrawals or payments to gambling sites are major red flags. To improve your chances, try to maintain a healthy average balance for at least three months before applying for credit.

  5. The Device You Use to Apply Sends Signals

    The phone or computer you use for your application tells a story. An AI can check the device model, its operating system version, and even the battery level at the time of application. An old, outdated operating system might suggest you are not careful with security. Applying with a very low battery level has been shown to correlate with desperate behaviour, which lenders see as high-risk. Always apply from a trusted device with an updated OS and a decent amount of battery life.

  6. Rejecting an Initial Offer Can Hurt You

    Some BNPL services and loan apps give you a pre-approved offer instantly. It might be for a smaller amount than you wanted. Many people reject this offer and try to apply for a higher amount. This can be a mistake. The AI might interpret this as you being over-leveraged or a higher risk. This can lead to a complete rejection. It is often smarter to accept the smaller initial offer. Use it responsibly and pay it back on time. This builds trust with the lender’s AI, making it easier to get a larger amount next time.

The One Thing Most Borrowers Forget About AI Lenders

The most important difference between a human and an AI lender is the lack of emotion and negotiation. You cannot explain a difficult month or a personal emergency to an algorithm. It does not understand context. It only understands data.

An algorithm doesn't care about your story. It only cares about your data points. If the data says you are a risk, you are a risk.

This means you must be proactive. You cannot fix a bad data profile after you get rejected. You have to build a positive financial and digital history before you need the money. The computer is always watching, so your everyday habits matter more than ever.

Is AI Making Lending Fairer in India?

This is a complex question with no easy answer. On one hand, AI has the potential to make credit more accessible. It can help people without a CIBIL score get their first loan, promoting financial inclusion. An algorithm does not have human biases against someone's name, gender, or neighbourhood.

However, AI can also create new problems. The algorithms are only as good as the data they are trained on. If the historical data contains biases, the AI will learn and amplify them. There is also a lack of transparency. If an AI rejects you, you often get a generic reason, not a specific explanation. This can be frustrating and makes it hard to know how to improve your profile.

The Reserve Bank of India has introduced guidelines to make digital lending safer and more transparent for borrowers. You can read about these regulations on their official website. Knowing your rights as a digital borrower is essential. For more details, refer to the RBI's Guidelines on Digital Lending.

Ultimately, AI is a tool. It is making the process of getting credit faster and more data-driven. For borrowers, this means your entire digital life is now part of your financial identity. Managing your data well is just as important as managing your money.

Frequently Asked Questions

How does AI decide my Buy Now Pay Later (BNPL) application in India?
AI systems in India analyze hundreds of data points for BNPL applications. This includes your traditional CIBIL score, but also alternative data like utility bill payments, your digital footprint on social media, your bank transaction history, and even your behaviour while filling out the application form.
Can I get a loan from an AI lender with a low CIBIL score?
Yes, it is possible. AI lenders often use 'alternative data' like your rent payments, mobile recharge history, and online shopping habits to assess your creditworthiness. If you have a strong, positive history with this alternative data, you may get approved for a loan even with a low or non-existent CIBIL score.
What is a 'digital footprint' in a loan application?
Your digital footprint is the trail of data you leave online. For a loan application, this can include your public social media profiles, your online shopping and payment history, the apps installed on your phone, and your location data. Lenders use this information to build a more complete picture of your lifestyle and financial responsibility.
Why was my online loan application rejected instantly?
Instant rejections are usually from AI-driven systems. Your application was likely rejected because your data profile triggered one or more of the AI's risk rules. This could be due to a low credit score, inconsistent information, a negative digital footprint, poor banking habits, or even behaviour flagged as suspicious during the application process.