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AI and Data Analytics Drive Efficiency in Money Laundering Detection

BIS Innovation Hub and Lucinity Pioneer New Techniques

BIS Innovation Hub Turns to Tech for Money Laundering Detection

The BIS Innovation Hub has discovered that innovative technologies, including artificial intelligence (AI) and data analytics, are more effective at detecting money laundering networks. This finding comes as traditional rule-based methods have been found to be inadequate.

Rising Costs of Financial Crime Compliance

The lack of effective detection methods is becoming increasingly costly, with financial crime compliance costs ballooning. According to a study by Lexis Nexis, these costs surged by approximately $60 billion, reaching a total of $274 billion from 2020 to 2022.

BIS Innovation Hub and Lucinity Initiate Project Aurora

In an attempt to find new solutions to this growing issue, the BIS Innovation Hub’s Nordic Centre and Lucinity, an Icelandic AI SaaS company, launched Project Aurora. This proof-of-concept experiment used a comprehensive synthetic dataset mimicking domestic and international payments data. It incorporated privacy-enhancing technologies to keep sensitive information secure, while allowing the use of machine learning and other analytics tools.

Project Aurora: A Novel Approach to Money Laundering Detection

Project Aurora trained algorithms using synthetic datasets to identify patterns indicative of money laundering activities across different institutions and countries. The project evaluated different scenarios of data monitoring, including isolated, national, and cross-border cases. It also experimented with various models of collaborative analysis, such as centralised, decentralised, and hybrid approaches, both at the national and cross-border levels.

Effective Behavioural-Based Analysis Techniques Revealed

Upon completion, the BIS Innovation Hub found that employing advanced analytics and technologies in a behavioural-based analysis approach was far more effective in detecting money laundering networks. Unlike the conventional rules-based approach, which is hindered by its isolated nature, this approach focuses on understanding the relationships between individuals and businesses and identifying behavioural anomalies. These new techniques have shown promise in outperforming traditional methods in uncovering illicit financial activities.

KEY POINTS

Use of AI and Advanced Tech: The BIS Innovation Hub has found that AI and advanced technologies, including data analytics and privacy-enhancing tools, are more efficient at detecting money laundering networks than traditional rule-based methods.


Launch of Project Aurora: In collaboration with the Icelandic AI SaaS company Lucinity, the BIS Innovation Hub initiated Project Aurora. This project used a synthetic dataset to train algorithms to detect money laundering patterns across various institutions and countries.


Launch of Project Aurora: In collaboration with the Icelandic AI SaaS company Lucinity, the BIS Innovation Hub initiated Project Aurora. This project used a synthetic dataset to train algorithms to detect money laundering patterns across various institutions and countries.

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