Bank risk analysis with machine learning

Detta är en Kandidat-uppsats från Högskolan i Halmstad/Akademin för informationsteknologi

Författare: Viet Vu; Mariaguadaloppe Farah; [2021]

Nyckelord: ;

Sammanfattning: Nowadays, the time and resources needed to get an accurate estima-tion of a client’s ability to pay back a loan has gone up. With theamount of data complexity it involves to do the credit risk analysis, the machine learning technique has been used to ease the process.To help a bank institute get a better insight into their client’s eco-nomic state. The thesis is to present a model that could help themfind interesting information using machine learning.With many clients having nonlinear income and expenses, it madethe machine learning algorithm of choosing, in this case, Linear Re-gression, very hard to predict an accurate output, the next month’ssalary. However, interesting relations between trends and the datahave been found.

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