Advancements in the Last 10 Years

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Over the last 10 years, through the use of technology, the role of underwriting financial products has become incredibly more automated and scalable.

Whenever you apply for a financial product — such as a credit card, loan, or mortgage — your application typically goes through a stage known as underwriting. During the underwriting process, the financial institution is looking at different characteristics of the customer. These typically include age, income, employment, and financial requirements. These criteria help them decide whether to approve the application and what rate they will charge.

Underwriting has moved away from the old process of being scrutinized by a bank manager on a case-by-case basis with that person making the decision. Listed below are some of the ways that underwriting has progressed significantly in the last decade.

The Use of Point Scoring for Underwriting Financial Products

Whenever a customer fills out an online application, that data can be evaluated against a lender’s preferred scoring system.

“With so many products like loans and credit cards, you can sometimes enter your details and get an instantaneous decision. What happens in between is that your data is scored against thousands of data points by that lender,” explains David Beard, founder of price comparison company LendingExpert.

“A lender or credit card provider might have 8,000 or 10,000 rules included in their scorecards. They’ll factor in things such as age, income, gender, residential status, and credit score. This is usually built-in using software or APIs. The lender will be collecting previous historical data. In this way, they have a good idea of whether a certain demographic is a better type of customer or is more likely to pay back on time.”

“Everyone might be given a point if they are a certain age or live in a certain area. Overall, a lender might say anyone that scores above 500 will be approved. If they decide they want to accept more risk, they can lower the score. Alternatively, if they want to be more risk-averse, they can up the score.”

Automated Credit Scoring

Credit scoring is certainly not new, but nowadays it’s astonishingly automated. Through the use of credit reference agencies or bureaus, a credit card provider or mortgage lender is able to pay $1 or $2 to a bureau and get real-time data on a customer.

This information typically includes how many other loans or forms of credit they’ve been applying for. It can also include how many debts they have outstanding. All this data will help the vendor make an informed decision.

Credit scoring is also very much based on numerical values and credit scores. This makes them easy to factor into the overall score and automate decision-making.

Using Social Media as a Factor When Underwriting Financial Products

Credit card processors have started factoring social media and email accounts into underwriting for many years. Neither of these tools was available a decade ago.

Whether evaluating the basics — such as Facebook, Gmail, or Linkedin — this provides an effective way to confirm that an individual is who they say they are. Moreover, it helps verify that the applicant is employed at the place they have claimed. This process can be automated, too. It’s not only useful for confirming names, locations, and employment, but it is hugely beneficial for fraud prevention.

Recent Use of Artificial Intelligence

The real art of good underwriting these days is to incorporate artificial intelligence (AI) into decision engines. Rather than having to constantly update scorecards, providers should be able to get real-time information of which customers are repaying on time and defaulting. They then feed this data back into their underwriting process. Essentially, the system “learns” and gets “smarter.”

Overall, the use of AI should make the underwriting process more effective, lower default rates, and maximize profits for suppliers.

The underwriting of financial products has truly progressed in the last 10 years. Going forward, we can expect that breakthroughs in AI, machine learning, and blockchain will have the biggest impact to scale processes and operations for companies in the financial space.

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