The Use of Machine Learning and Transaction Data for Credit Risk Assessment

Development of a novel solution that predicts credit risk for a bank. The goal is to obtain more accurate credit risk assessment by using machine learning and transaction data.

Brief information

School:

Business

Status:

Completed

Period:

26.11.2020 - 31.05.2021

Overview

Development of a novel solution that predicts credit risk for a bank. The goal is to obtain more accurate credit risk assessment by using machine learning and transaction data.

Facts

Type of project

Forschung

Internal organisations involved
  • Institute of Financial Services Zug (IFZ)
Funding
  • Private / Stiftungen

Persons involved: internal

Project manager
Member of project team
  • Jakob Dambon