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Fighting Money Laundering with Python and Open Source Software

Level:
intermediate
Room:
north hall
Start:
Duration:
30 minutes

Abstract

In this talk proposal, we will discuss how to detect the chain of fraudulent transactions and help the investigation agencies by providing useful insights to fight money laundering with the help of Python programming language and packages.

TalkTBD - Multiple Tracks

Description

In this talk proposal, we will discuss the chain of fraudulent transactions and help the investigation agencies to fight money laundering with the help of Python programming language and packages. The working of the proposed solution is described below Step 1: The investigation officer obtains data of suspicious accounts across banks. Step 2: Using Benford’s Law the accounts data will be checked for possible fraud and marked for further analytics. Step 3: The account details will also be matched with Politically Exposed Persons(PEP), Relatives and Close Associates (RCA), and Sanctions Data. If a match is found then it increases the probability of possible money laundering. Step 4: Generate graphs showing the links between transactions of different bank accounts for step 2 and step 3. Step 5: Apply Graph Machine Learning techniques and graph algorithms to identify the fraudulent chains between depositor and receiver accounts. Step 6: Find a correlation between transactions and bank accounts to form a fraudulent chain. Step 7: Generate results in the form of reports and interactive visualizations Step 8: Verify the result for genuineness and false positive rate. Step 9: Keep track of all the activities and tasks executed from steps 2 through 8. Step 10: Generate a report for step 9 in a human-readable and understandable form.

The application has been developed using Scipy, numpy, pandas, matplotlib, NetworkX, Altair, scikit-learn, and Dash packages.

The participants will learn about a new use case of python in crime investigation.


The speaker

Gajendra Deshpande

Gajendra Deshpande

I am Gajendra Deshpande and I am using Python since 2013 for academic research and development activities. I develop prototypes and applications in Natural Language Processing, Machine Learning, Cyber Security, and Web applications using Python and its ecosystem. I am working as a faculty of Computer Science and run a start-up in cyber security. I am an active member of the PyCon India community and served as program committee lead for PyCon India 2021. I have presented approximately 80 talks, 20 Workshops, and 15 posters across the globe at prestigious conferences like PyData Global, PyCon APAC, PyCon AU, EuroPython, DjangoCon US and Europe, SciPy India, SciPy USA, PyCon USA, JuliaCon, FOSDEM, and several other Python and FOSS conferences. I have helped Python and FOSS Conferences by reviewing the talk and tutorial proposals, mentoring first-time speakers, participating in the discussions, and organizing the events.


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