- Acceptance rate
- Credit risk
CRIF is able to provide connectivity needed to access to bank accounts.
Consent needed is acquired in two different ways: recurring and one-time access
CRIF downloads and analyzes each bank account transaction of income and expenses
Then, a proprietary categorization algorithm classifies the transactions into a specific category
CRIF Score is entirely based on current account information and on the categorization of banking descriptions performed by ML and developed using Advanced Analytics techniques. It’s a 3 digit score and indicates the probability of default.
CRIF has developed an analytics suite of structured insights from unstructured data. Insights and KPIs are then integrated to assess customer portfolio in terms of risk monitoring as well as KYC and cross-up selling strategies.
- Improve acceptance rate
- Reduce credit risk
- Increase evaluation accuracy
- +90% categorization accuracy for better customer profiling
- +50% GINI Credit Score of current account transaction data
- +10% loans disbursed while keeping the same risk level