From the beginnings of General Motors Acceptance Corporation to the introduction of the Diner’s Club charge card, the history of credit has been filled with game-changing innovations.
Today, new innovations in tech are continuing to shape the consumer credit industry – and with U.S. consumer debt sitting at $13 trillion, these changes could play a role in impacting how consumers access credit both today and in the future.
THE MODERN CREDIT LANDSCAPE
Today’s infographic comes to us from Equifax, and it gives a snapshot of modern credit as well as a perspective on how new technologies such as trended and alternative data are changing the landscape.
It’s the second part of our ongoing three-part series on credit:
Interestingly, how this scoring works is not at all static – and new technology is being applied to increase accuracy as well as open credit up to more consumers throughout society.
TRADITIONAL CREDIT SCORING
The modern numeric credit score emerged in 1989, and it uses logistic regression to make informed decisions on a consumer’s creditworthiness.
The scoring model is made up of five distinct categories:
|Payment History||35%||Are scheduled payments made on time?|
|Debt Burden||30%||Includes multiple factors such as number of accounts with balances, amounts owed, and debt-to-limit ratio.|
|Length of Credit History||15%||Average age of accounts and age of oldest account.|
|Types of Credit Used||10%||What type of credit is used? (i.e. revolving, installments, etc.)|
|New Credit Requests||10%||Hard new credit inquiries can hurt scores.|
But this model does have its limitations. For example, traditional credit scores give a snapshot of credit rather than showing how the “big picture” of a person’s credit is changing. Further, current scores can also can be inhibited by a lack of data, resulting in an inaccurate representation of a person’s credit.
TECH TO THE RESCUE
On a global basis, the data universe is doubling every two years – and this abundant new resource is revolutionizing consumer credit.
Instead of looking at a snapshot of a credit score, it’s possible to analyze the direction, velocity, tipping points, and magnitude of changes in a consumer’s credit history to get a bigger, more accurate picture. This is called trended data, and it can offer up to 20% improvement in predictive performance.
Credit history is important, but there are increasingly other sources of data that can provide a view of a consumer’s creditworthiness. Alternative data taps into information on property ownership, wealth, how customers pay everyday bills, and other data sources to provide a more well-rounded picture.
Technology has given consumers unprecedented access to their credit data – and in the meantime, new science behind neural networks is being implemented to give even more sophisticated scoring capabilities.