Development of a Digital Model for Customer Credit Limit Decisions: Identification of Impact of Macroeconomic Indicators on Credit Risk Assessment
Thesis title: | Development of a Digital Model for Customer Credit Limit Decisions: Identification of Impact of Macroeconomic Indicators on Credit Risk Assessment |
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Author: | Van Gessel, Pia |
Thesis type: | Diploma thesis |
Supervisor: | Tyll, Ladislav |
Opponents: | Wahnschaffe, Peter |
Thesis language: | English |
Abstract: | A solid credit risk management in corporations is key to minimize financial risk. Due to the fourth industrial revolution, credit risk management processes change from manual proceeding to automation with credit scoring showing high potential for advanced analytics. This thesis analyzed the importance of considering macroeconomic indicators within a credit scoring model. The research methodology based on two surveys with credit risk communities and a statistical analysis including a correlation and regression analysis proved the importance of the external information within a credit scoring model with differences among the analyzed regions. Despite that, further statistical testing is suggested to identify a set of the most relevant macroeconomic indicators once the underlying credit scoring model is further developed. |
Keywords: | Credit Scoring ; Industry 4.0; Credit Risk Management ; Macroeconomic indicators; Automation |
Thesis title: | Development of a Digital Model for Customer Credit Limit Decisions: Identification of Impact of Macroeconomic Indicators on Credit Risk Assessment |
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Author: | Van Gessel, Pia |
Thesis type: | Diplomová práce |
Supervisor: | Tyll, Ladislav |
Opponents: | Wahnschaffe, Peter |
Thesis language: | English |
Abstract: | A solid credit risk management in corporations is key to minimize financial risk. Due to the fourth industrial revolution, credit risk management processes change from manual proceeding to automation with credit scoring showing high potential for advanced analytics. This thesis analyzed the importance of considering macroeconomic indicators within a credit scoring model. The research methodology based on two surveys with credit risk communities and a statistical analysis including a correlation and regression analysis proved the importance of the external information within a credit scoring model with differences among the analyzed regions. Despite that, further statistical testing is suggested to identify a set of the most relevant macroeconomic indicators once the underlying credit scoring model is further developed. |
Keywords: | Industry 4.0; Macroeconomic indicators; Credit Risk Management ; Credit Scoring ; Automation |
Information about study
Study programme: | Ekonomika a management/International Management |
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Type of study programme: | Magisterský studijní program |
Assigned degree: | Ing. |
Institutions assigning academic degree: | Vysoká škola ekonomická v Praze |
Faculty: | Faculty of Business Administration |
Department: | Department of strategy |
Information on submission and defense
Date of assignment: | 19. 11. 2017 |
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Date of submission: | 13. 5. 2018 |
Date of defense: | 14. 6. 2018 |
Identifier in the InSIS system: | https://insis.vse.cz/zp/63908/podrobnosti |