Data Analytics

Custom Credit Scoring Modeling

ICAP CRIF has been active for more than fifteen years in the analysis of its clients’ databases (Data Analytics), focusing on the development of credit risk models on behalf of Credit Institutions, Telecommunications companies and, more generally, on the utilisation of historical debtor and client data for statistical purposes.

ICAP CRIF’s Analysts analyse an Organisation’s historical transaction and behavioural data on either individuals or businesses, using ICAP CRIF’s Data Science tools, and following modern protocols on data cleansing, transforming, training and constantly reviewing models.

ICAP CRIF fully meets the needs for credit cycle and client management predictive models, either for decision-making, or for risk rating to calculate regulatory capitals, or for the calculation of provisions according to IFRS9 accounting standard.

Risk.Profiler is the proposed solution for installing the models. However, Data Analytics services are independent of implementation technology, and support any Decision Engine the Organisation may use.

NPL Portfolio Analysis

To support decisions regarding Non-Performing Exposures and, in general, to manage arrears, ICAP CRIF analyses historical behavioural data, models the likelihood of meeting obligations or debt settlement schemes, and profiles debtors based on possible future trends

Profiling is accompanied by:

• An estimate of the monthly or yearly debt affordability;
• Application of automated rules resulting in either matching each debtor with a standardised debt settlement or final arrangement scheme (debt settlement products and their parameters), or in loan contract termination and liquidation of collateral.

Viability Classification & Recovery Index Algorithm

This algorithm ranks companies in terms of their degree of viability. It has been developed and validated using a statistical methodology based on ICAP CRIF commercial data. It can be adjusted as necessary to take advantage of debtors’ payment history and to incorporate dynamic features. The adjusted algorithm classifies debtors according to a recovery index indicating the expected recovery rate.

Predictive Financial Modeling

ICAP CRIF’s econometrics team develops predictive Financial Risks and, in general, Financial Random Variables models, taking into account the characteristics of the Greek Economy as derived from data of Greek businesses.

Inter alia, financial models are used for the assessment of a company’s turnover, future cash flows and value, considering Industry level trends and the Macroeconomic Environment. ICAP CRIF, thanks to the overall picture it has gained from its own database analytics, can offer high-value assessment services in the areas of Project Finance, Start-ups and crisis scenario simulations like the recent pandemic.