One-third of Finance Firms Have Accelerated Use of AI to Detect Money Laundering
Financial institutions are heavily investing in Artificial Intelligence (AI) and Machine Learning (ML) as part of the money laundering prevention program.
Due to the turmoil brought by the COVID-19 pandemic, the global economy is facing a sudden increase in FinCrime while money laundering poses a serious threat to society. According to a United Nations report, approximately $2 trillion of the global GDP is laundered every year. Criminals use large banks to hide their illegally earned money. The National Crime Agency (NCA) in the UK estimated that money laundering costs £24 billion every year to the country’s economy.
A survey was conducted by the KPMG, SAS (a software company) and the Association of Certified Money Laundering Prevention Specialists (ACAMS). According to the survey, one-third of the financial institutions are rapidly adopting the use of AI and ML in their Anti-Money Laundering regimes to combat the growing threat of financial crimes.
Third of finance firms accelerate use of artificial intelligence to detect money laundering https://t.co/j9nr5biCaG
— ComputerWeekly (@ComputerWeekly) August 10, 2021
Around 57% of the survey respondents have employed AI-driven AML compliance processes or are working on policies to implement it within 18 months. Chief Analyst of ACAMS, Kieran Beer said, “Since regulators around the world are increasingly making decisions about financial institutions’ compliance efforts based on the effectiveness of the intelligence they provide to law enforcement agencies, 66% of respondents said that regulators are using AI and machine learning. It’s no wonder they want to take advantage of.”
The two primary reasons for adopting AI and ML in the AML screening process are to:
- Improve the quality of investigations and regulatory submissions
- Reduce false positives and associated operating costs
Inadequate AML systems have resulted in hefty penalties for banks over the years. Only in the first half of 2021, 17 banks have been penalised over £910,192,215 for inefficient AML procedures. After this study, it is evident that banks and other financial institutions are taking all possible measures to prevent future penalties.
