Gender differences in debt collection

Sammanfattning: From the perspective of debt collectors, the goal of debt collection processes is to maximize the chances of a debt being repaid, while minimizing the time to repayment taking place. The purpose of this thesis is to investigate what measure that is most commonly leading to debt being repaid within 30 days. Against a background of males being overrepresented among debtors in terms of the share of the population in Sweden, the purpose has also been to use data analytics methods to explore whether the measures from debt collection companies affect males and females differently and how they affect them. Finally, the purpose has furthermore been to explore whether existing data provided by the debt collection company Visma can be used to optimize the debt collection process so that the debtors' time in it becomes as short as possible. The report has found that invoicing seems to be the measure most strongly associated with debt resolvance, suggesting that this measure is an important tool for debt collection agencies. The report has found that the measures affect males and females differently, which may be related to gender differences in attitudes to financial risk. Furthermore, it has been shown that it presumably is possible to create prediction models to know which debtors will be able to pay their debt. These models should be divided by gender as males, tend to take more risks. Lastly, machine learning and other modern tools, such as Open banking, should be used to optimize the debt collection process.