This is the machine learning model and presentation that won runner up at Cornell Tech's 2016 Fintech Hackathon

We based our dataset on PKDD'99 Discovery Challenge data set.

Relations within the accounts:

• relation account (4500 objects in the file ACCOUNT.ASC) - each record describes static characteristics of an account,
• relation client (5369 objects in the file CLIENT.ASC) - each record describes characteristics of a client,
• relation disposition (5369 objects in the file DISP.ASC) - each record relates together a client with an account i.e. this relation describes the rights of clients to operate accounts,
• relation permanent order (6471 objects in the file ORDER.ASC) - each record describes characteristics of a payment order,
• relation transaction (1056320 objects in the file TRANS.ASC) - each record describes one transaction on an account,
• relation loan (682 objects in the file LOAN.ASC) - each record describes a loan granted for a given account,
• relation credit card (892 objects in the file CARD.ASC) - each record describes a credit card issued to an account,
• relation demographic data (77 objects in the file DISTRICT.ASC) - each record describes demographic characteristics of a district.

• You can find the datasets here
• You can find our proto.io here
• You can find my twitter here for any suggestions!