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Building a Financial Case-Based Reasoning Prototype from Scratch with Respect to Credit Lending and Association Models Driven by Knowledge Discovery

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Credit lending can be seen as a challenging task due to many available procedures such as the cash flow analysis and scoring methods. Using Case-Based Reasoning (CBR) and knowledge discovery to support and gain comparison and risk assessment of loan cases are demonstrated in this paper. The knowledge discovery of a credit data set was made with open source algorithms using Waikato Environment for Knowledge Analysis (WEKA). Building a prototype from scratch can be seen as an interesting task when considering the full CBR methodology especially with heterogeneous input data schemes.

Jürgen Hönigl

Jürgen HöniglJürgen Hönigl

Jürgen Hönigl has studied computer science at the Johannes Kepler University (JKU) in Linz, Austria. He finished his study in 2008. Afterwards he mainly worked with Objective-C to develop apps. The research field of Case-Based Reasoning was chosen for his doctoral thesis with a direction towards financial reasoning. He participated within three research projects as an employee of the JKU in the area of geographic information systems and retrieving data by using web services. He is currently on leave to publish and work on his thesis.


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