Effective Credit Scoring with Self-Developed Decision Support
Company Size
11-200
Region
- Europe
Country
- Denmark
- Estonia
- Finland
- Norway
- Sweden
Product
- STATISTICA
Tech Stack
- Logistic Regression
- MARSplines
- Boosted-trees
- Data Mining
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Data Mining
- Analytics & Modeling - Predictive Analytics
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
Use Cases
- Fraud Detection
Services
- Software Design & Engineering Services
- System Integration
About The Customer
Folkia, established in Norway in 2006, operates in Sweden, Finland, Denmark, and Estonia. The company specializes in providing short-term loans and aims to offer economical and effective financial services to its customers. Folkia's primary focus is on selecting the right customers to minimize credit risk and ensure financial stability. The company collaborates with consulting firms and utilizes advanced software tools to develop customized solutions for its credit scoring needs. With a commitment to innovation and efficiency, Folkia continuously seeks to improve its decision-making processes and maintain a competitive edge in the financial services industry.
The Challenge
Folkia, a company providing short-term loans, faced the challenge of accurately selecting customers to minimize credit risk. The company needed a robust credit decision support system to improve its credit scoring model. The existing methods were not sufficient to discriminate effectively between good and bad customers, leading to potential financial risks. Additionally, maintaining and updating the system was cumbersome, requiring manual changes and extensive data structuring. Folkia aimed to develop a more efficient, accurate, and easy-to-maintain system to enhance its credit decision-making process.
The Solution
Folkia developed a customized credit decision support system in collaboration with the consulting firm Aregab, utilizing STATISTICA software from StatSoft. The software's powerful data management and analytical capabilities, including data mining, enabled the creation of multiple models using different statistical methods such as logistic regression, MARSplines, and boosted-trees. These models were tested against each other to determine the most effective one. The system's graphical presentation at every step, from selection to testing, simplified the process and enhanced efficiency. The completed score model effectively rated customers by credit risk, allowing Folkia to make informed decisions and treat high-risk customers differently. The system's easy maintenance and quick development, facilitated by the alliance with Aregab, further contributed to its success.
Operational Impact
Quantitative Benefit
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