Regulatory Analytics – Predictive & Dashboarding

Due to the increase in the volume of banking transactions on the one hand and the need to control and analyze financial and banking information on the other hand, the need for infrastructures to analyze scattered banking information in standard and integrated formats is required more than ever.
Therefore, CIIC Company, using its banking experience and data mining knowledge, has designed the banking business intelligence system.
This system can cover the needs of the banking community in the following areas:

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NGREG FEATURES

Banking risk management

The risk management process in this system includes identifying, evaluating and prioritizing the risks of the bank It is based on the Basel committee recommendations. Risk management includes credit, market and operational risk.

Credit scoring

This system is able to calculate the numerical score of customers based on analytical statistical information and customer information (personal information, transactions, employment status and financial behavior). The customer’s credit score report generated by this system can be the basis for giving loan to her/him.

Fraud detection

This system can detect frauds based on defined rules and patterns. The patterns can be learned by artificial intelligence and data mining algorithms. Detectable frauds by this system can be in different areas like deposits, loans, electronic banking and impersonation

Banking soundness indices

In order to check the status of banks and financial institutions and ensure the correctness of the performance and health of the departments different methods have been proposed. One of the most efficient and famous methods is the use of CAMELS indicators are in the field of assessing the bank’s situation in various fields. These indices examine the bank’s situation in six different areas, which include Capital adequacy, Asset quality, Management, Earnings, Liquidity, and Sensitivity to risk.