{"id":18610,"date":"2025-01-10T10:57:38","date_gmt":"2025-01-10T08:57:38","guid":{"rendered":"https:\/\/www.intellias.com\/?p=18610"},"modified":"2025-12-03T10:12:00","modified_gmt":"2025-12-03T08:12:00","slug":"how-alternative-credit-data-can-increase-accuracy-in-credit-scoring","status":"publish","type":"blog","link":"https:\/\/intellias.com\/how-alternative-credit-data-can-increase-accuracy-in-credit-scoring\/","title":{"rendered":"How Alternative Credit Data Can Increase Accuracy in Credit Scoring"},"content":{"rendered":"

In the United States, where approximately 20% of adults<\/a> fall into the category of credit invisible<\/em> due to limited or no traditional credit history, the financial landscape is undergoing a significant transformation thanks to alternative data sources for credit scoring<\/p>\n

Lenders are leveraging alternative credit data to extend access to a wider consumer base, transcending the boundaries set by traditional scoring models. But it doesn\u2019t stop there. By incorporating alternative data into credit risk modeling, accuracy soars to new heights.<\/p>\n

In this article, we delve into the world of alternative credit scoring data, exploring its significance, sources, and applications to help you find out the following:<\/p>\n