GonioLabs Consultancy – Predictive analysis for loan default

Mikael Lindstrand, gonioLabs, is contracted for an assignment “Analysts with legal expertise, development of model for predictive analysis, based on The Swedish Board of Student Finance's data storage”, June – December 2018. He will evaluate the potential of predictive analysis for loan default by analyzing the data storage capabilities for the task, potential hurdles and the relative strength of a series of artificial intelligent based algorithms.

More specifically, in IBM SPSS Modeler, develop predictive model based on The Swedish Board of Student Finance's (CSN's) data storage including an IBM Cognos database interface. The purpose of this business supporting tool is to get improved knowledge of borrowers at higher risk of default (financial insolvency) and thus constituting credit risk for CSN. With the enhanced knowledge, CSN can take earlier measures that benefit as well borrowers, CSN as the state property. The assignment requires the ability to capture and define the business requirements, methodology, mathematical knowledge, especially in statistics, ability to apply signal processing (including methods such as machine learning, artificial intelligence, neural networks, etc.) to develop and critically evaluate systems that meet the business requirements, including evaluation stability considerations. The legal competence facilitated an adequate interpretation of the regulatory framework during the method development. Workload approx. 50 percent.

Posted  2018-05-25  by  Mikael Lindstrand