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MPC as a fraud detection and anti-money laundering (AML) tool

Fraud, money laundering and other financial and economic crimes are difficult to combat. Every year, millions of citizens and thousands of businesses in the EU fall victim to fraud. Money laundering is also how criminal organisations finance themselves.

In order to trace financial crime more effectively, it is essential that organisations be able to share information and data with one another. At the same time, the privacy of ordinary citizens or businesses must not be violated. How can an organisation combat fraud and money laundering without violating privacy? Via privacy by design.

building up anonymised databases 

 At TNO, we work on different forms of privacy by design. Multi-Party Computation (MPC), is one of these: a smart way to jointly analyse data without having to reveal them. Cryptographic techniques ensure that several parties can analyse data together and draw conclusions, all without ever being able to see each other’s data. With MPC, absolutely no data is revealed, only conclusions based on that data.

Whitepaper: 'Finally, a privacy-friendly way to harness data'.

Discover how to harness data for fraud detection while safeguarding privacy.

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Fraud detection must be improved

Fraud has a large impact on Dutch society. It has a disruptive effect and costs the government, businesses and citizens a lot of money. Furthermore, fraud often has an impact on the more vulnerable members of society because money does not end up where it should. During the COVID-19 pandemic, we have also seen the misuse of government subsidies for companies. In order to detect fraud more effectively, more information must be exchanged between both companies and governmental parties.  

Fraud detection without infringing privacy

On the other hand, recent court rulings have shown that combining information can quickly lead to a breach of privacy for citizens. MPC offers possibilities to gain very specific insights from the data of these parties without exchanging sensitive data. Moreover, this technique ensures that only analyses agreed upon beforehand can be carried out. This prevents the improper use of personal data. 

anti-money laundering (AML)

TNO is working with several Dutch banks to implement MPC as a form of collective anti-money laundering (AML). Annually, hundreds of billions of euros are laundered worldwide, of which an estimated 16 billion takes place in the Netherlands. Although banks and other financial institutions work hard to detect money laundering activities, a large amount remains under the radar. It is estimated that less than 1% of criminal cash flows are seized.

Detecting suspicious money flows with MPC

A major challenge is that criminals often use successive transactions through multiple banks. Each bank therefore sees just one piece of the puzzle and has to pass on possible money laundering activities to financial investigation services on the basis of incomplete information. This leads to a large number of reports with high chances of a false alarm. Cooperation between banks is therefore very valuable when it comes to improving anti-money laundering (AML). MPC allows banks to jointly detect suspicious cash flows without sharing personal data or other sensitive data.

Want to know more about fraud detection with MPC?


  • Discover how you can use data in a privacy-friendly way.  
  • Find out how MPC can improve fraud detection by securely linking the data.
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Contact

Dr. Daniël Worm

  • Multi-Party Computation
  • Privacy-Enhancing Technologies
  • Cryptography. Cybersecurity

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