Fraud, embezzlement and other economic crimes are serious risks in any industry. However, nowhere is the risk more acute than in the financial sector, where large amounts of money are at stake and many millions of transactions occur every day. Global losses from fraudulent activities are a reported $42B yearly1, and only a fraction of the money is ever recovered. The damage to brand reputation and market share is almost incalculable.
Banks and investment houses are also uniquely vulnerable because customers trust investment professionals to manage their money responsibly. Unfortunately, some investment professionals turn out to be far from trustworthy.
Just a few recent examples:
In addition to the financial blows, the loss of investor trust and confidence in a fund or portfolio management house can lead to “running” landslides and withdrawals, decreased investment and even bankruptcy.
Clearly, detecting and preventing fraud are of the highest priority to financial institutions, but there is an enormous obstacle in the way: their massive volume of data. In the US alone, major banks have an estimated billion billion bytes of data (think 18 zeros), gathered from credit cards, web interactions, transaction records, chats and more. As new data constantly flows in, that figure keeps growing.
With mountains of data and millions of transactions taking place every day, often at time-sensitive rates and quotes, it can be challenging to spot unusual or suspicious activities. Fraudsters and embezzlers capitalize on this complexity to cover up their activities. But now bankers have a new weapon to bring them out in the open: Artificial Intelligence.
Advanced AI- and ML-driven analytics, coupled with AI automated testing, can sift through billions of data points at lightning speed and with laser-point accuracy, transforming data from a giant headache to a huge advantage.
Armed with multidimensional transaction data, AI systems can be trained as pattern-recognizing watchdogs, scanning for anomalies and suspicious asset movements. Then the systems can alert compliance officers that further investigation is needed.
The systems can pull data from multiple sources, such as demographics and behavioral data, and even add biometric identifiers such as fingerprints and facial recognition to the mix. All of this helps create a more detailed, nuanced picture of customer behavior, drilling down deep to uncover atypical activity.
While AI-based detection is a big benefit to banks, the best way to fight fraud is with a proactive approach, through prediction and prevention. By analyzing historical data and identifying patterns, AI systems can optimize their own prediction models that are in place to ensure increasingly accurate results. In other words, they teach themselves the “right” settings to detect fraudulent behaviors so potential fraudsters and their activities can be flagged before they cause significant harm.
Last, by analyzing up-to-the minute transaction data, AI systems can detect and track fraud as it unfolds, so financial institutions can take appropriate actions or terminate relationships with high-risk individuals.
Financial fraud is soaring. Digital fraud attempts on financial services companies rose by 150% in 2021, according to one report.2 The smart money is on smart tech to help financial institutions fight back, with one leading economic group predicting banks and insurance companies will see an 86% increase in AI-related technology by 2025. But as data continues to proliferate and financial institutions become overwhelmingly digital-first, opening up more opportunities for fraudsters, can AI-enabled fraud prevention and detection systems really keep up?
The fact is, AI systems get smarter all the time. They learn from their mistakes, use self-heal mechanisms and continually improve their accuracy. By analyzing feedback from compliance officers and continuously updating their algorithms, AI systems can become even more effective at detecting and predicting fraudulent activities over time.
However, it’s important to remember that not all AI-enabled tech is the same. Investigate before investing. As the world’s leading AI-driven engineering company, Qualitest has the most innovative smart tools and tech available and the BFSI specialists, data scientists-in-test and quality engineers to build your customized solution.
1 https://www.pwc.com/gx/en/services/forensics/economic-crime-survey.html
2 https://www.bloomberg.com/press-releases/2021-06-03/suspected-financial-services-digital-fraud-attempts-rise-nearly-150-worldwide-as-prevalence-of-digital-transactions-increase
3 https://pctechmag.com/2018/12/more-than-86-of-businesses-organizations-will-use-ai-by-2025/
