Experian launched a new product which will give lenders an unprecedented view into consumer behavior over time across all three credit bureaus.
The company explained that while traditional credit gives lenders a glimpse into credit during a single moment of time, Experian’s product will add a deeper layer of insight. The company’s aim is to provide lenders with consumer credit behavior over time, helping them expand into new risk segments and better tailor their offerings to meet consumer needs.
The new product, Trended 3D, provide lenders with up to 7% increase in predictive performance compared to models which use only traditional attributes.
“While trended data has been shown to provide additional insight into a consumer’s credit behavior, lack of standardization across different providers has made it a challenge to gain those insights,” said Steve Platt, Experian group president of decision analytics and data quality.
“Trended 3D makes it easy for our clients to get value from trended data across all three credit bureaus in a consistent manner, so they can make more informed decisions across the credit life cycle and, more importantly, give consumers better access to lending options,” Platt said.
Experian explained that while two people may have similar balances, utilization and risk scores, but their paths to that point could be substantially different. Trended 3D will allow lenders access to a 24-month history of five credit report fields: balance, credit limit or original loan amount, scheduled payment amount, actual payment amount and the last payment date.
Here are some of the insights Experian’s trended credit product gives access to:
- Changes in balances over time
- Migration patterns from one tradeline or multiple tradelines to another
- Variations in utilization and credit limits
- Changes in payment activity and collections
- Balance transfer and debt consolidation behavior
- Behavior patterns of revolving trades versus transactional trades
Trended 3D utilizes machine learning in order to evaluate behavioral data and recognize patterns that may have previously gone undetected.
