Analytics for Credit Risk Modeling
Make Better Lending Decisions
As consumer habits and practices continue to evolve, traditional credit score data is not enough when attempting to build more accurate credit risk models. Achieve far more successful lending decisions by incorporating de-identified data, outlining the income & spending behaviors of prospective borrowers throughout their everyday lives.
Create More Powerful Credit Risk Models
Key Features
Understand how cash flow, ACH, direct deposits, NSFs and late fees can assist in building robust credit models and enable less risky lending decisions.
Save Time
Easily import a representative, normalized, de-identified alternative dataset on borrowers' spending behavior
Find Signals
Detect nonlinear relationships between spending and credit default
Manage Risk
Improve default and delinquency prediction
Lend Efficiently
Grow your lending base by lending smarter
Geo-location
Filter data by city, state, zip code or region, where available
Credit Scoring Models You Can Count On
Data Analytics for Credit
With near real-time data, Envestnet | Yodlee Data Analytics helps you to make better lending decisions by incorporating actual account information into your credit risk models.
Our de-identified user data gives you a representative view into how millions of consumers are managing and spending their money. Learn how Envestnet | Yodlee’s data can help you build better credit risk models. Contact us today.