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Handling Smurfing Through Big Data

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Big Data Analytics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 654))

Abstract

Money laundering is a worrying term for every country’s economy these days. Leading economists of all major developed and developing economies are concerned to devise methods to prevent it. The economy of a country is weakened by the impact of money laundering. Networks created between various banks in different countries facilitate online money transfer, which is turning the process of money laundering into digital money laundering. This promotes money launderers to perform wired transactions from anywhere. People involved in the process of money laundering are efficiently using online banking as their weapon. Evading the anti-money laundering agencies is becoming easier for them because of having online bank accounts. Such people are misusing technology. Therefore, it is restricting one’s own country’s economic progress. But with the help of recently developed technologies, we are able to prevent such illegal activities. Scrutinizing all the transactions and investigating them manually at financial intelligence units are cumbersome tasks because petabytes of transactions are taking place each day. Advanced technologies like Big Data enable us to detect the suspicious customers possibly involved in money laundering. In this paper, we have proposed a methodology using big data to detect smurfing; based on which, suspicious people involved in money laundering may be identified and appropriate action can be taken against them.

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Authors and Affiliations

  1. Department of Computer Engineering, Netaji Subhas Institute of Technology, New Delhi, India

    Akshay Chadha & Preeti Kaur

Authors
  1. Akshay Chadha
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  2. Preeti Kaur
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Correspondence to Akshay Chadha .

Editor information

Editors and Affiliations

  1. Jagan Institute of Management Studies, New Delhi, Delhi, India

    V. B. Aggarwal

  2. Department of Computer Science, University of Delhi, New Delhi, Delhi, India

    Vasudha Bhatnagar

  3. Microsoft Innovation Centre, Sri Aurobindo Institute of Technology, Indore, Madhya Pradesh, India

    Durgesh Kumar Mishra

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Chadha, A., Kaur, P. (2018). Handling Smurfing Through Big Data. In: Aggarwal, V., Bhatnagar, V., Mishra, D. (eds) Big Data Analytics. Advances in Intelligent Systems and Computing, vol 654. Springer, Singapore. https://doi.org/10.1007/978-981-10-6620-7_44

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  • DOI: https://doi.org/10.1007/978-981-10-6620-7_44

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6619-1

  • Online ISBN: 978-981-10-6620-7

  • eBook Packages: EngineeringEngineering (R0)

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