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Researchers build model to predict which delinquent credit card holders will pay up

15 mai 2015

The efficient collection of outstanding debt from defaulted credit-card accounts is mission-critical for many financial institutions. University researchers, quoted by finextra.com,  say that they have found a way to predict which delinquent credit card accounts will repay outstanding balances that is up to 50% more accurate than the scoring systems currently used by banks.

Naveed Chehrazi from the University of Texas and Thomas Weber from École Polytechnique Fédérale de Lausanne in Switzerland worked with a major credit card issuer to build their ‘Dynamic Collectability Score’.

The score ranks delinquent account holders based on factors such as size of outstanding balance, mortgage status, past payment history, credit score, and external factors such as the performance of the stock market and the national unemployment rate.

The score continually adjusts as new data comes in, making it more accurate than other systems, says Chehrazi. „Each action that’s taken — from a collection phone call that goes unanswered to a partial payment that the bank receives — is factored in to revise, up or down, that person’s likelihood of future payment.”

Currently banks have trouble working out who will pay back debts, say the researchers, usually involving third party collection agencies and selling the debt for pennies on the dollar.

Being able to accurately predict who will pay back makes it easier to know which accounts are worth spending money on — whether sending them to a collection agency or filing a lawsuit — based on the likelihood of repayment and the amount they can expect to recover.

Another benefit of the model is its ability to help banks work out their credit risk requirements, or the amount of money they need to have in reserve to cover future unpaid accounts.

Says Chehrazi: „The credit card collection problem is very complicated. And current bank internal scoring systems are surprisingly poor in predicting repayment behavior, given the amounts that are at stake.”

Researchers concludes that the dynamic collectability score (DCS) method can be viewed as the backbone of collections optimization. In contrast to standard bank-internal scores, the DCS reflects the actual repayment probability conditional on a repayment threshold, a collection horizon, and scheduled account-treatment actions.

Download the full report here: „Dynamic Valuation of Delinquent Credit-Card Accounts”

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Anders Olofsson – former Head of Payments Finastra

Banking 4.0 – „how was the experience for you”

So many people are coming here to Bucharest, people that I see and interact on linkedin and now I get the change to meet them in person. It was like being to the Football World Cup but this was the World Cup on linkedin in payments and open banking.”

Many more interesting quotes in the video below:

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In 23 septembrie 2019, BNR a anuntat infiintarea unui Fintech Innovation Hub pentru a sustine inovatia in domeniul serviciilor financiare si de plata. In acest sens, care credeti ca ar trebui sa fie urmatorul pas al bancii centrale?