Personal Finance

Data Science Close the Gap Between Borrowers and Lenders

Many borrowers in America cannot get a loan due to credit issues. They are viewed as risky, making the lender think they will not receive loan payments on time – or at all.

And, often, many people turn to alternative methods of financing for the money they need, which leads them to predatory terms. What if there was a middle road, though, that helped both the “risky” borrower and the lender? There is – it’s called data science.

Traditionally, lenders take a specific set of parameters to measure a credit applicant’s financial risk. This typically includes things like credit score and credit report items. If a borrower does not meet specific criteria for these parameters, they are denied financing.

Often, this is unfair for the borrower because the credit report and score do not tell everything or take everything into account. For example, an applicant may be young and has not established credit yet. This does not mean that they can’t or won’t repay the loan. It simply means that their credit does not yet reflect their ability or likelihood of doing so. Unfortunately, it’s hard to get credit without credit, so this makes it difficult for young borrowers.

There are also applicants who have never had to apply for credit before or haven’t in a long time because they have had the financial means to take care of everything without using credit. It isn’t exactly fair to be completely responsible with your finances yet still be turned down for credit.

And there are other people whose credit reflects a tough time in their lives. Maybe they got divorced or their spouse passed away. Or maybe they had an unexpected illness that led to more hospital bills than they could pay at once. Having a rough time doesn’t necessarily indicate that they will not repay a loan. It simply means that they had a rough time – something everyone goes through from time to time.

With this traditional method of determining an applicant’s risk, it’s not just the borrower missing out. Lenders are also missing out on many borrowers who will repay their loans. And the economy, as a whole, suffers because the money that could be being spent isn’t.

While it’s understandable and necessary for lenders to find borrowers that have a high likelihood of repaying their debt, the traditional way of determining this likelihood doesn’t always work. This is where data science comes into play.

Data science provides a way to look at more than what a credit report says. In moments, it can dig into things like bank accounts to determine how long they’ve been open and how often the balance is negative. It can also look at things like social media and other sources that can provide a more comprehensive look at the borrower, opening the door to many worthy borrowers who do not meet traditional requirements.

Financial consultation with data science companies, like Cane Bay Partners, also helps lenders customize loan products for the borrowers. When lenders can offer loan types with terms that suit the customer, it increases the likelihood that the customer can repay and that the lender gets their money back.

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