About Leaseplan

The Dutch company LeasePlan Corporation is a leading provider of fleet management services worldwide. It operates in two large and growing segments: Car-as-a-service (CaaS) for new cars and the high quality used car market. It has 1.8 million vehicles under management in over 30 countries.

Credit Decisioning

Improved Credit Risk Management

LeasePlan uses ACTICO’s technology for implementing credit rating models which are used as part of the credit decisioning process. The software not only shortens the credit decisioning process, but it also makes the risk management team less dependent on IT department’s support. Before ACTICO’s implementation, it used to take months to roll out new rating models and now these updates are completed in days or in some cases, even hours.

Avoiding risks in the credit decisioning process

Centralization of Rating System

LeasePlan was looking for a new rating system to avoid risks in the credit decisioning process. The legacy system was a decentralized solution used within various subsidiaries. This made the process of deploying new models very cumbersome and time-consuming.

Objectives

  • Efficient and effective credit decision in seconds
  • Globally standardized, rating models
  • Implementation and maintenance of models by risk management department
Solution

Implement, Execute and Adapt Rating Models

Following a comprehensive vendor selection process, LeasePlan opted for ACTICO Rules to implement, execute, and adapt rating models. The software scored particularly high on its user-friendliness: new rating models are not programmed, but implemented using the intuitive graphical modeler. Benefits include:

  • Ease of use of for credit risk managers
  • No need of support by IT department
  • Ease of change management: rating models can be updated within days or even hours
  • A more robust credit scoring system, given interfacing functionality with credit bureaus and other external data sources
IMPACT

Flexible, Efficient and Robust

Credit risk managers without any programming skills can adapt the models with ease. At the same time, external information is imported via interfaces from credit bureaus and other external data sources, making the credit decisioning process more robust.

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Automation in the Credit Risk Assessment Process

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