The Customer Effect

Explainer: How neural networks are changing credit scores

  • Credit bureaus are increasingly using machine-learning technology to calculate credit scores.
  • This new method is said to provide a more balanced assessment of an individual's creditworthiness.
close

Email a Friend

Explainer: How neural networks are changing credit scores
A credit score has a major impact on a person's life. It’s the key to getting a car loan, a house or an apartment. The traditional way scores are calculated is a method called logistic regression, which means assigning a value to a number of factors in your financial life (for example, payment history, number of credit accounts, length of credit history) and weighing them. But credit bureaus are now looking into other ways to determine an individual's credit history beyond the result of a static formula. They’ve integrated machine-learning into credit scoring methods to get a more balanced picture of someone’s likelihood of defaulting on a debt. But it's more complex that that -- we break down the method.  The basics This technology essentially integrates machine-learning into the credit-scoring process. There are multiple tools: NeuroDecision technology is a tool developed by credit bureau Equifax. Other credit bureaus, including Experian, are also reportedly exploring similar ideas. The technology is modeled on neural networks in the human brain, so it can assess the interrelationships between the different factors rather just spit out a number based on a static formula. “Each attribute can have multiple weights,” said Peter Maynard, svp of enterprise analytics for Equifax.  It allows you to better or more accurately predict the person's likelihood to default.” The process Artificial neural networks mimic the way the human brain works, so a non-human has the ability to think through the data and assess patterns. So the machine has the ability to process the data like a human. Perhaps an individual with a historically poor payback record made improvements over time -- a machine-learning tool may be able to take those details into consideration. “A neural network more closely mimics the way humans think and reason, whereas linear models are more dogmatic — you’re imposing structure on data as opposed to letting the data talk to you,” said Eric VonDohlen, chief analytics officer at the online lender Elevate, in an interview with American Banker. The traditional method has been popular because of the ability to provide specific explanations to customers, Maynard said. By contrast, neural networks have been seen as a “black box” due to the inability to understand how the decisions were determined. What’s new with Equifax’s tool is the ability to find specific reasons to explain why someone is declined credit. “The algorithm Equifax created allows full transparency into how each consumer is scored,” he said. The implications There can be biased outcomes depending on the human that inputs the data. Some industry watchers are concerned that the use of machine learning to analyze financial data can generate biased results. How the data is fed into the system and the instructions that are given to the machine are important factors contributing to biased outcomes, said Kevin Petrasic, partner at international law firm White & Case. "The program can have the very powerful capability to model itself over time and turn into something it wasn’t originally programmed to do," he said. "It may come to the conclusion that loans to people in a particular zip code aren't good credit decisions, or people who hang out in a certain social network are not good credit risks because of whatever associations they have with people in that network." Equifax doesn't share these concerns -- for now. Maynard said its product was vetted to meet regulators’ standards, including those of the through regulators including the Office of the Comptroller of the Currency, the Federal Reserve and the Consumer Financial Protection Bureau. “Currently, we do not have concerns, said Maynard. “First, the sample of data used to build the model is algorithm agnostic, meaning we use the same sample of data for both logistic regression and neural nets. Second, we follow our rigorous compliance and model governance processes to review and approve the model for use.”

0 comments on “Explainer: How neural networks are changing credit scores”

The Customer Effect

How are consumer habits and spending changing due to economic turbulence?

  • Economic turbulence is changing consumer spending.
  • 66% of people say that the current economic situation is making them reconsider how much they put aside for their emergency fund, while others are pushing away travel plans and dipping into their 401k.
Rabab Ahsan | April 27, 2023
The Customer Effect

22% of Americans think ‘net worth’ only applies to wealthy people

  • American consumers are more aware of celebrity net worth than their own.
  • Younger consumers, those heading towards retirement, and women are the most likely to not keep track of their net worth.
Rabab Ahsan | April 20, 2023
The Customer Effect

Trouble in paradise: How layoffs are affecting consumer relationships

  • The recent wave of layoffs is impacting consumers’ relationships.
  • 80% of those who were laid off themselves would consider leaving their spouse if they got laid off, too.
Rabab Ahsan | April 14, 2023
The Customer Effect

Quick Take: Scrutinizing the impact of inflation on consumers’ finances

  • Troubles in finance paradise continue. With passing months these anxieties have been growing and are reflected in other parts of customers’ financial habits as well.
  • With rising inflation, how are increasing rents, embedded finance, & layoffs affecting consumers' financial anxieties?
Rabab Ahsan | April 05, 2023
The Customer Effect

The White House is proposing an increase in the capital gains tax. What will non-white groups gain?

  • The White House is proposing a hike in capital gains tax as part of a deficit reduction plan.
  • The taxation system in America needs another look, so far the balance has been tipped in the favor of investors and white households. Will the capital gains tax rebalance the scales?
Rabab Ahsan | March 15, 2023
More Articles