EVIS delivers services to transform your data to information.

Do you need help in building, validating, improving, and monitoring your credit-scoring system. Also in other cases, such as credit card fraud detection, CRM and related areas where you have to deal with large amounts of data, we can help you sift and uncover the gold nuggets in your data banks.

Banks, investment companies, and credit card societies receive thousands of credit applications every day from individuals and business clients, so they need a system that can help them grant or refuse requests. Automatic systems are used for evaluating credit worthiness, especially by banks and investment companies. One of the reasons for doing so is the regulatory policy that was established by the Basel Committee of central banks. A detailed prescription of how credit risk should be calculated can be found here.

Credit-Scoring Systems

That's why most banks employ credit-scoring systems that estimate the risk based on some variables and a manually tuned set of rules. The term “credit scoring” describes the statistical methods used to classify possible creditors into two classes of risk: good and bad. The rules embedded in the credit-scoring systems are usually based on a client's debt ratio, assets, credit history, and so on and so forth. Once you have these rules, do you ever wonder whether these 'golden rules' are really golden? Do you update them regularly to reflect the changing market? And if so, how do you determine whether these new rules actually perform better than the old ones? Do you keep a constant track on them, constantly comparing them to the old rules to see if you've made any improvements? Read more...

Other examples in banking

So far, we have focused on credit-scoring systems, but there are several other popular application areas for Data Mining, such as: Fraud detection - Fraud is enormously costly. By analyzing past transactions that were later determined to be fraudulent, banks can identify patterns Detect and predict accounting fraud Detect credit card fraud Card marketing - By identifying customer segments, card issuers and acquirers can improve profitability with more effective acquisition and retention programs, targeted product development, and customized pricing. See also CRM

• Card marketing - By identifying customer segments, card issuers and acquirers can improve profitability with more effective acquisition and retention programs, targeted product development, and customized pricing. See also CRM
• Cardholder pricing and profitability - Card issuers can take advantage of data mining technology to price their products so as to maximize profit and minimize loss of customers. Includes risk-based pricing
• Predictive life-cycle management - Data mining helps banks predict each customer’s lifetime value and to service each segment appropriately (for example, offering special deals and discounts).