Data scientists use various forms of AI ingesting historical and present data to predict future data.

Challenge

Improve the efficiency of credit evaluation of aircraft financing

The aim of this project was to demonstrate the possibilities offered by combining business process management and data-driven dynamic case management.

Solution

A demonstrator was built that shows the added value and optimization potential of non-linear processes applied to the existing evaluation and credit approval for aircraft financing.

Instead of running through a credit process in a linear way without taking into account the framework conditions (e.g. credit amount and KYC), this solution enables a dynamic credit process that defines the individual functional steps as cases, automates them where possible, and only displays the steps required for a specific situation. The demonstrator was developed within 4 days with 6 additional employees.

Outcome

Generating savings of 50-60% of working time. In addition, the customer service representative is dynamically guided through the process, so that the knowledge required for processing can be reduced without reducing the complexity or standardizing the process.

Data Science Application

The demonstrator is based on the process engine Camunda and implements classical business process management and case management, combining them with statistical and Bayesian models for the optimal process combination in a credit process.

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Testimonial

Karsten Hohensee: Dominik proved to be a truly original scientist, actively moving organizations’ perspectives towards innovative and trendsetting, but also feasible solutions. Being open to different views and very internationally driven, Dominik searches for alternative routes, bringing in his brilliant analytical skills combined with his pleasant, interesting, and open-minded nature. He has inspired me personally, but also our organization in multiple ways. Always ahead of his time, he has been one of the wittiest personalities I have met in a professional setting.