Financial Services
How AI is shaping the future of financial crime prevention strategies
Whether we like it or not, the world of financial crimes is never at rest. The fight to keep criminals at bay in the banking and finance world is an unceasing and relentless battle. What is worrying is that advancing technologies are being adopted by criminals at a rate that is as fast or at times even faster than financial institutions. So, institutions will need to adopt aggressive strategies to ensure that the attempts by criminals are constantly thwarted. As these criminals become more sophisticated, the latest technologies will need to be leveraged to combat the challenges posed by them. One of the ways this can be achieved is by ensuring that Artificial Intelligence (AI) is embraced in order to meet the challenges posed by fraudsters.
Needless to say,banks have to be at the top of their game to proactively prevent financial crimes. They need to persistently keep a tab on transactions done to detect any anomalies that are an indication of crimes being perpetrated. A case in point is one of the global financial institutions that provides banking and financial services to customers in over 60 countries and territories – it checks about 1.35 billion transactions for signs of financial crime each month and this is done with the help of AI.
While using AI to combat financial crimes has become an imperative, one key point to note is that in this world, AI is a double-edged sword. While it certainly has its advantages, the uncomfortable truth is that it can also be used by criminals to unleash more sophisticated and dangerous crimes!
Why use AI to fight financial crimes?
Given the volume of financial crimes seen, it is impossible for humans to manually sift through data and flag irregularities. AI, with its ability to handle large volumes of data, is the best bet to tackle this issue. It is good at analysing large scales of data and spotting suspicious patterns in this data.
How does AI combat financial crimes?
Banks constantly train their AI to look out for financial crime tactics and trends. This way they are able to keep a watch out for irregularities more thoroughly and track crimes with greater accuracy. Thus the use of AI helps in precisely calling out more financial crimes than during earlier times.
How does AI help with financial fraud solutions?
AI learns the normal behaviour of banking customers through unsupervised learning, which is a type of machine learning that learns from data without the need for human oversight. Once this type of learning is done, the technology is able to spot anomalies based on behavioural patterns and call out irregularities in such patterns.
Apart from that, AI can also help with reducing false positives while tracking these crimes. Banks would see an umpteen number of false positives earlier while tracking financial crimes. This number has reduced significantly due to the use of AI which is smarter in detecting crimes that actually need follow up – this helps save the time for investigating such crimes.
It is also interesting that AI is being used to stem the flow of cash for illegal activities around the world. It plays a significant role in combating money laundering by enhancing the ability to detect, analyse, and prevent suspicious financial activities. For example, if a customer suddenly starts transferring large amounts of money to an offshore account, AI will flag the same as a deviation from typical patterns. Traditional AML (anti-money-laundering systems) often produce false alerts which overwhelm compliance teams. With AI, false alerts are minimised.
In the digital age, financial systems are prime targets for cybercriminals. Cybersecurity tools that use AI are capable of recognizing suspicious activities, such as abnormal login behaviours, unauthorised access attempts, or atypical data transfers. When cybercriminals send phishing emails, AI can detect such emails and block them even before the situation escalates by reaching the intended people.Based on customers’ transaction frequency and historical behaviour, AI can assign them risk scores. High-risk activities, such as large wire transfers to international regions, could be flagged for further review.
A recent news article stated that the United States Treasury Department used machine-learning AI to halt 1 billion dollars in cheque fraud, in the fiscal year 2024, which ran from October 2023 to September 2024. It is clear that AI is adding immense value to the fight against financial crimes. It can carry out repetitive cybersecurity tasks, identify potential vulnerabilities and anticipate threats that could appear in the future. This allows compliance and security teams to focus their energy on more strategic initiatives. AI is continuously learning from past incidents, thus minimising false positives and allowing security teams to focus on actual risks.
Why Infosys BPM?
Infosys BPM Compliance practice empowers banks to revolutionise their KYC, AML, Trade Surveillance, and Fraud Detection & Prevention operations with comprehensive services, expert process consulting, and advanced technology-driven solutions that help with financial crime compliance. By harnessing our deep domain expertise and global delivery capabilities, we enable the seamless implementation of banks’ target operating models.
