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Vidhya Veeraraghavan, VP & AI Delivery Lead – Financial Crime & Fraud Detection, Standard Chartered Bank

Vidhya Veeraraghavan, Vice President & Artificial Intelligence Delivery Lead – Financial Crime & Fraud Detection, Standard Chartered Bank

Is the use of #ArtificialIntelligence in #AML #CFT and #financialcrimecompliance becoming mainstream? If so, what are the main reasons for this? 

#MoneyLaundering is one of the key ‘engines of crime’ sustaining global #criminal business worth billions of dollars. According to a report by Europol, just around 10% of the #suspicioustransactionreports filed by #financialinstitutions lead to further investigation by competent authorities.

On one hand, financial institutions struggle to keep their #compliance costs down and on the other hand, the sophistication of money laundering threats continue to increase exponentially.

Being part of the #analytics and #AI landscape for more than a decade, I strongly believe that a lot can happen with AI on your side. #AIcanhelp but only if you allow it to.

However, organizations need a shift in #mindset; financial institutions where financial crime compliance still follow age-old processes, rule-based thresholds and legacy systems will take time in #transformation.

Having said that, we have seen significant increase in investments in emerging technology and #RegTech sector worldwide. Compared to the 11.8 billion U.S. dollars in 2021, investments shot up to 18.6 billion U.S. dollars in 2022, which was notable. A study by IBM found that 90% of well-known companies invest in AI, and 83% of them think AI will help them maintain or gain a competitive edge. The AI market is expected to skyrocket in the coming years, reaching $300 billion by 2026. However currently only 35% of the businesses are actually using AI.

The significant increase in investments in RegTech and emerging technologies such as Artificial Intelligence implies that firms are finally looking to technology to meet regulatory obligations, improve customer trust, and outperform their rivals in terms of efficiency. Increased efficiency and cost saving are of paramount importance to avoid regulators levying hefty fines while simultaneously working on dealing with the cut-throat competition in the market.

Which processes would you say are best suited for leveraging AI in the fight against financial crime?

AI can be used to fight financial crime in various ways. Some #banks and #financialinstitutions are already using AI efficiently to tackle some of the perennial problems within the financial crime area. In my opinion, the following processes are best suited for leveraging AI to combat financial crime:

  • Anti-Money Laundering (AML): AI can be used to identify suspicious transactions that may be associated with money laundering activities by monitoring transactional data and identifying patterns or anomalies that are out of the ordinary. By employing specific AI techniques such as anomaly detection, clustering, and network analysis helps financial institutions detect anomalous transactions and to link them to other transactions or entities that may also be associated with money laundering activities.
  • Fraud Detection: It is quite evident that AI algorithms can analyze large volumes of financial data in real-time and identify any unusual #patterns or #transactions that may indicate #fraudulent activity. Algorithms such as decision trees, random forests, logistic regression, and neural networks can make a significant difference in detection, prevention, and investigation processes.
  • Know Your Customer (#KYC): AI can help financial institutions by deploying techniques such as facial recognition, document analysis, and natural language processing (NLP) to automate the customer identification and verification process (KYC), making it faster and more accurate.
  • Cybersecurity: Anomaly detection, machine learning, and natural language processing (NLP) can also be used to provide #cybersecurity solutions. These algorithms can be used to predict, detect, and prevent #cyberattacks, such as data breaches, phishing scams, and identity theft and protect the financial institutions from financial crimes.

Overall, AI has the potential to be a powerful asset in the arsenal of financial institutions fighting financial crime. These organizations can increase their efficiency and accuracy in identifying and preventing financial crimes by utilising AI to automate and streamline their processes at scale.

Many thanks to Vidhya Veeraraghavan for sharing her thoughts with Fintelekt.

To stay updated on this subject, follow her newsletter at https://www.linkedin.com/newsletters/7032560970778501120/

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