OTP Bank

Statistical modeling used to identify hidden predictors in loan applications, reduce defaults and increase capital reserves

Published on 15-Apr-2013

"We have no intention of changing our software, as we have been highly satisfied with all aspects of the solution. Simply put, our daily operations would be impossible to solve satisfactorily without IBM SPSS software." - Tamás Tóth, head of analysis and modeling, Credit Approval and Risk Management Division, OTP Bank

Customer:
OTP Bank

Industry:
Banking

Deployment country:
Hungary

Solution:
BA - Business Analytics, BA - Predictive Analytics, Big Data & Analytics, Big Data & Analytics: Transform processes, Smarter Planet

IBM Business Partner:
Clemtentine Consulting

Overview

OTP Bank has played a defining role in the Hungarian banking sector for more than 60 years and has operated as a multifunctional commercial bank since 1989. It is a member of the OTP Group, which provides universal financial services through several subsidiaries

Business need:
The bank wanted to improve the speed and efficiency of its mortgage, loans and lease application processes, and make accurate, evidence-based decisions more rapidly than the competition.

Solution:
Every bank wants to grant loans to as many applicants as possible, but not at the expense of loan defaults. OTP Bank uses a sophisticated statistical modeling and predictive analysis solution to foster sound business decisions on the evaluation and approval of mortgage and loan applications, ensuring adequate capital reserves.

Benefits:
The IBM solution helped significantly contributed to the increase in the bank’s capital reserve, reduce loan defaults and increase the accuracy of revenue forecasts.

Case Study

OTP Bank has played a defining role in the Hungarian banking sector for more than 60 years and has operated as a multifunctional commercial bank since 1989. It is a member of the OTP Group, which provides universal financial services through several subsidiaries. In Hungary, traditional banking operations are performed by OTP Bank, while specialized services, including car leasing, investment funds and insurance, are developed and offered by the group’s subsidiaries. OTP Bank embarked on international expansion in the early 2000s and now has subsidiaries in eight other European countries. In addition to Hungary, it is the market leader in Bulgaria and Montenegro. Annual profitability in the last few years has been between 150 and 300 billion Hungarian forints. Based in Budapest, the bank employs about 8,000 people in Hungary, and OTP Group as a whole has a staff of 30,000.

The Opportunity
OTP Bank offers a wide range of financial services for both retail and corporate banking, such as mortgages, loans and investment and fund management. It wanted to improve the speed and efficiency of its mortgage, loans and lease application processes, and make accurate, evidence-based decisions more rapidly than the competition.

What Makes It Smarter
Every bank wants to grant loans to as many applicants as possible, but not at the expense of loan defaults. OTP Bank uses a sophisticated statistical modeling and predictive analysis solution to foster sound business decisions on the evaluation and approval of mortgage and loan applications, ensuring adequate capital reserves. Analyzing hundreds of key performance indicators such as income or revenue, cash flow and credit obligations from numerous data sources, the bank can paint a comprehensive picture of every applicant, whether retail or corporate. It uncovers patterns and predicts risks associated with each applicant. As a result, the bank can quickly identify and approve those with low risks, accurately assessing borrowers’ credits to develop more precise revenue forecasts.

Real Business Results
• Significantly contributed to the increase in the bank’s capital reserve by reducing loan defaults
• Reduced loan defaults with increased accuracy of predictive models, pinpointing low-risk applicants and high-risk accounts
• Increased the accuracy of revenue forecasts by predicting the impact of changes in loan payments as well as fluctuations in the finance industry

For more information
Please contact your IBM representative or IBM Business Partner. Visit us at ibm.com/spss.

To learn more about OTP Bank, visit www.otpbank.hu.

Products and services used

IBM products and services that were used in this case study.

Software:
SPSS Modeler

Legal Information

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