OTP Bank Serbia Builds Prediction Model Based on IBM SPSS Modeler

Enterprise Background

Founded in 2007 with 700 employees, OTP Bank Serbia provides cross-border online financial services and ATM systems for retail and banking industries. OTP Bank Serbia's banking group has subsidiaries in nine European countries and employs about 30,000 people.

Cetko Okiljevic, Chief Executive of OTP Bank Serbia's Ventilation Department, commented: "The current trend in the banking industry is to use more advanced and sophisticated statistical analysis tools for risk assessment." In the OTP Group within its Hungarian headquarters, we have seen significant benefits of implementing IBM SPSS Modeler risk management.


Challenges

OTP Bank Serbia has always relied on the process of risk modeling based on spreadsheets, which requires a lot of time and resources, and must extract the database from the company's center, and then make the process manual through the bank's analysts, thus greatly increasing the risk of human error. It also means analysts spend a lot of time on low-level data processing rather than focusing on providing valuable decisions.


Solution

Serbia-based OTP Bank Serbia has found a single and standard process to establish a risk prediction model, which is a more effective solution. By using the IBM SPSS Modeler to establish a prediction model, not only can the data in the database be collected directly and analyzed more quickly and easily, but also more detailed data can be drilled, such as automatically generating credit risk scorecards and risk prediction. This means that we can do more sophisticated analysis in order to correctly assess the risk appetite of investors in the face of changes in the global financial environment, as well as competition from other financial institutions, giving the bank a foothold in the wealth management market.


Benefits

  • Scorecards created using IBM SPSS Modeler software help banks assess credit risk and decide whether to offer products such as loans to the customer. In the future, its applications can also be extended to other evaluations.
  • It eliminates the spreadsheet-based process and automatically generates credit risk scorecards and establishes accurate risk models by predicting and analyzing them based on the IBM SPSS Modeler software. More complex models are built to enable decision makers to execute decisions more quickly.
  • IBM SPSS Modeler analysis software helps organizations identify visual trends and patterns in this area, such as customer analysis, which can have a profound impact on business performance. It can compare optimal decisions under different circumstances, such as estimating potential threats and opportunities to expected returns and jobs, better planning budgets and predicting available resources, and assessing asset-liability risks to meet regulatory requirements. Through extensive analysis and application, enterprises can decide strategy and adjust tactics to achieve business goals.


Relevant Cases:

  1. Insurance Company Builds the Telemarketing Response Prediction Model Based on SPSS Modeler
  2. Raiffeisen Bank International AG – RBI Adopts IBM SPSS Modeler Software Solution
  3. InSites Consulting Corp. Establishes the Sentiment Dictionary Based on IBM SPSS Modeler
  4. Direct Wine Conducts Differentiated Marketing Based on IBM SPSS Modeler

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