Debts and their values to banks

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Built using pandas, numpy, matplotlib , scipy and statsmodel.api

In this project, I try to analyse how banks respond to debts that get labelled "uncollectable". "Uncollectable" debts are receivables, loans, or other debt that will not be paid by a debtor. Reasons for accounts uncollectible relate to bankruptcy or a refusal to pay by the debtor.
Banks implement different recovery strategies having varying costs. In this project I try to answer "does the extra amount that is recovered at the higher strategy level exceed the extra $50 in costs? In other words, was there a jump (also called a "discontinuity") of more than $50 in the amount recovered at the higher strategy level?"

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Acknowledgement

Datacamp has guided me to build this project