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janelu9 / Aml

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README

Anti-money laundering

Dedect relationship between 'a' and 'e' even 'f', 'g', 'h', etc by tracing through payments with similar amounts and identifying payment chains from the transaction data. It is a pattern graph search problem.

For example:

id accname Event_Dt Tx_Amt Cntpty_Acct_Name
5068 a 2020-01-01 20.0 b
5069 a 2020-01-02 300.0 b
5070 a 2020-01-03 180.0 b
5071 b 2020-01-03 40.0 c
5072 b 2020-01-03 500.0 c
5073 b 2020-01-04 10.0 c
5074 b 2020-01-03 150.0 d
5075 c 2020-01-04 50.0 e
5076 d 2020-01-04 150.0 e

You can run spark-submit --files build_functions.cp37-win_amd64.pyd Aml.py in windows environment or spark-submit --files build_functions.cp37-x86_64-linux.so Aml.py on linux platform to get the payment chains seem like money laundering.

1

id chain_id src dst amount depth accname Event_Dt Tx_Amt Cntpty_Acct_Name
5068 0 a e 200.0 3 a 2020-01-01 20.0 b
5070 0 a e 200.0 3 a 2020-01-03 180.0 b
5071 0 a e 200.0 3 b 2020-01-03 40.0 c
5073 0 a e 200.0 3 b 2020-01-04 10.0 c
5074 0 a e 200.0 3 b 2020-01-03 150.0 d
5075 0 a e 200.0 3 c 2020-01-04 50.0 e
5076 0 a e 200.0 3 d 2020-01-04 150.0 e

Same 'chain_id' indicates these transactions belong to a complete chain. Field 'depth' shows the length of the chain. Enjoy it ! 🤗

References

[1] Zaharia M, Chowdhury M, Franklin M J, et al. Spark: Cluster computing with working sets[J]. HotCloud, 2010, 10(10-10): 95.

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