EOS KSI selected STATISTICA to optimize its debt collection process
Company Size
1,000+
Region
- Europe
Country
- Czech Republic
- Germany
- Romania
Product
- STATISTICA Data Miner
- STATISTICA SAL
- STATISTICA Standard
Tech Stack
- Data Mining
- Statistical Analysis
- Sequence, Association and Link Analysis
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Digital Expertise
- Productivity Improvements
Technology Category
- Analytics & Modeling - Data Mining
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries
- Finance & Insurance
- Professional Service
Applicable Functions
- Business Operation
- Quality Assurance
Use Cases
- Process Control & Optimization
Services
- Software Design & Engineering Services
- System Integration
- Training
About The Customer
EOS comprises a group of companies active around the world in debt collection. It has 49 subsidiaries and affiliates in more than 20 countries, with the company’s head office located in Hamburg, Germany. The EOS Group has more than 20,000 customers and offers its services to companies of all sizes, from renowned joint-stock companies that trade on the stock exchange to mid-sized and small companies. For example, EOS offers customized services for large insurance companies, banks, credit card issuers, leasing companies, public service companies, industrial and trading companies, publishers, and freight companies. EOS is one of the leading debt collection companies in Romania. Their core business areas are debt collection and debt purchase.
The Challenge
EOS sought user-friendly software that would “score” debts—in other words, a tool to assess the success of each step of the collection process. The required tool would need to serve internal decision-making processes, e.g., in the sense of deciding whether to go to court over debtor disputes, or whether it should collect a debt during a specific phase of the process, or skip a step, etc. In light of changes in the global—and, thus, also the Czech—market that are driving companies to retain their customers, a new system of procedures is coming about that brings with it the need to keep a debt out of the courts for as long as possible. This requires an advanced modeling tool that is capable of automating required processes in a suitable manner according to company needs, one that is quick, efficient, and reduces workload. EOS has found that all of these needs are met by a combination of STATISTICA Data Miner, STATISTICA SAL (Sequence, Association and Link Analysis), and STATISTICA Standard software. EOS has found that these tools from StatSoft CR together provide a suitable solution due to a favorable combination of user-friendly environment, acquisition cost, and requirements for implementation into its existing system.
The Solution
For maximum efficiency and successful debt collection processes, the EOS Group’s Czech branch, EOS KSI Česká republika, s.r.o., had been using its own collections software, which met the company’s needs. However, due to recent initiatives to increase the success of the collection process, the company decided to extend its system by adding a tool to assess the quality of collection steps using statistical data available in the internal system. Software installation was performed in house by EOS employees with minimal need for supplier support. Implementation included training and subsequent practical application and knowledge transfer during the creation of the first data mining model. STATISTICA is currently being used as a tool for assessing the likelihood that debt collection will be successful for selected EOS clients. The process begins with preparation of data such as type of client, nature of debt, debtor, region, and information on available contacts. The software then automatically processes the data based on models that have been developed and helps EOS decide on the future of each debt, for example, regarding the best way to contact the debtor. The overall likelihood the debt will be collected successfully is also valuable. STATISTICA has been integrated into the collection process in a suitable manner, not only through the scoring of debts, but also by uncovering new linkages in the process, the knowledge of which enriches the company’s expert rules.
Operational Impact
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