Credit grantors in Georgia were introduced to the new version of the Creditinfo Predictor scorecard (CIP) on 8th January 2013. The upgraded score using the rich positive data in Creditinfo Georgia will further improve credit risk decisions.

CIP models have been running in Georgia for more than 18 months and are continuously reviewed and fine-tuned. The new model utilized the growing maturity of the positive data in the credit bureau and achieved an increase in the predictive power of 16 %. The big advantage of the model is the orientation on different components of the customer payment behavior. It includes not only the negative payment behavior but rewards individuals with good payment history of their credit contracts.

The model also includes in specific variables for the country which makes the scorecard perfectly suited to the Georgian market.

Alexander Gomiashvili, General Manager for Creditfinfo Georgia, “ It is very important for subscribers to know that we are regularly improving the CIP scorecard, I am very pleased with the results and we are seeing more and more lenders identify it as an essential component of their lending process”

We are presenting here the main components of the scorecard to show you what made the scorecard strong and predictive:

Components of CIP Score and approximate makeup:

• 40% Payment behaviour
  Bills paid on time increases the score while the late payments decrease the score.
• 15% Length of Credit history
  It usually reveals after some months if a customer is able to repay his credit.
• 30% Structure and utilisation of financial facilities
  CIP scores can be improved by paying off debt and lowering the credit utilization ratio. The use of Fast Loans can also lead to a lower score.
• 10% Searches for Credit
  Credit inquiries, which occur when consumers apply for a credit card or loan (revolving or otherwise), can hurt CIP scores, especially if done from different subscribers.
• 5% Personal Demographic Information

How to use the bureau score

The CIP score and risk rating is widely used by the credit grantors to improve the effectiveness and efficiency in assessing the credit risk. CIP delivers 3 types of outputs which helps the credit grantors to decide on the risk of an applicant or an existing client:

• Credit score and probability of the default
• Risk grade with 9 grades ranging A to E
• Reason code

If the customer is scored with a low score, the credit grantor always sees why the customer is of higher risk by looking at the reason codes.

Creditinfo Predictor can be applied in several ways: used on its own, combined with the internal score, or as a part of a risk management cycle.