Submitted by Rachel Gardner on Tue, 04/04/2023 - 16:13
A team led by Professor Nic Lane has been announced as joint winner of a prize to drive ‘innovation in privacy-enhancing technologies that reinforce democratic values’ for its work on tackling international money laundering.
The announcement came at the second UK-US Summit for Democracy on 30 March 2023. The prize challenges innovators on both sides of the Atlantic to build solutions that enable collaborative development of artificial intelligence models, while keeping sensitive information private.
Most of the world's data is inaccessible for machine learning – however, these new methods are making such data available in a safe manner. This will be a game changer for many high impact domains.
Professor Nic Lane
Driven by a shared priority to employ data to help solve critical global challenges in a manner that supports US and UK commitments to democratic values and the fundamental right to privacy, the challenges focused on developing privacy-enhancing technologies (PETs) solutions for two scenarios: forecasting pandemic infection and detecting financial crime.
A team led by Professor Lane (pictured right) was named joint winner in the financial crime category. Their challenge was to develop a privacy-preserving solution to help tackle the challenge of international money laundering.
Xinchi Qiu (pictured left), a PhD student in Professor Lane’s lab, said: "We developed an end-to-end privacy-preserving federated learning solution to detect potentially anomalous payments, leveraging a combination of inputs from a number of financial institution and different banks. Our project aims to develop a method that can utilise all the inputs from different institutions while protecting the original data."
Professor Lane said: "Right now, machine learning with federated and other privacy preserving methods are niche. But in the near future they will be the norm. Most of the world's data is inaccessible for machine learning – however these new methods are making such data available in safe manner.
"This will be a game changer for many high impact domains that are currently starved of sufficient data, such as health, finance and legal. Our solution shows how this can be done effectively for money laundering, but our methods can migrate to these other domains."
- Read the full story (adapted from a press release from the Centre for Data Ethics and Innovation) on the Cambridge University website
