Published by Jessica Weisman-Pitts
Posted on October 11, 2021
5 min readLast updated: January 29, 2026
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AI plays a crucial role in predicting and preventing financial crime, enhancing security and compliance in the banking sector.
By Martin Rehak, CEO of Resistant AI
For each dollar of fraud lost, the cost to the merchant is three times as great. Banks need to be agile to compete with the fintechs, but how can they do this without compromising both security and the onboarding process?
Banks are always going to be target number one for cybercriminals, after all that is where people keep their money. As a bank you have to protect your customer’s money, their information and your reputation. Additionally, you now have to do this with regulations and a financial climate that demands you transform under intense pressure on your margins.
The Covid Impact
The Pandemic forced all banks to automate and there were huge increases in mobile and online transactions. The bank robber is no longer a balaclava-wearing person with a gun, but someone stealing money from the comfort of their home without anyone noticing. Much of the verification and common-sense processes get lost in automation, which makes it easy to attack. Criminals have become more sophisticated, learning to target complex environments and use financial innovation, such as block chain and instant payments, against banks and their customers.
According to SAS Institute, “COVID-19 has not changed how fraud is committed but has shone a bright light on the risks of fraud in a digital age. Without technological and operational improvements, the global rise of digital fraud will surpass the losses associated with counterfeiting magnetic stripe payment cards.”
Financial Automation Oversight
Once an organisation makes a decision to automate, it is not as straightforward as simply keeping the anti-fraud and compliance the same. That would be akin to bringing the proverbial knife into a gunfight. What is required is financial automation oversight, a set of AI powered technologies and processes that can effectively and efficiently supervise modern financial systems in real time.
Financial organisations spend huge amounts of money to protect their information and IT, yet the automated processes that give access to money are often the least protected. What has become clear is that traditional approaches to fraud prevention that rely primarily on human intervention are losing out to criminals that can operate on a large scale.
The combination of AI, automation and human interaction offers the strongest form of defence when it comes to fighting financial crime. In a recent study of 151 traditional banks and fintechs, 85% currently use AI and 77% see it as of high importance1. Without greater investment in AI technologies, it will become virtually impossible to defeat the criminals.
Financial automation oversight is a system of continuously refined relationships between the algorithms, methods and capabilities that are required to deliver a safe environment that is trusted by both brands and their customers. It understands the end-to-end customer journey and protects that relationship from criminal intervention.
Strengthening Validation, Verification and Transaction Processes
In the general onboarding process, identity validation is the first step to ensure an applicant actually exists. Next is verification, which links that person to the information they have provided in the validation stage. In many automated workflows there are risks from forged or manipulated documents that support the customer journey in online lending, trading, insurance, financing, factoring and payments.
In fact, 1-20% of documents in the application and onboarding process can be subject to manipulation, such as forged bank statements, modified invoices and amended pay slips. By protecting automated processes that use unauthorised documents from third-parties, banks can be sure that all digital documents are genuine.
Continual assessment of transactions instantly alerts teams to potentially fraudulent activity taking place. These anomalies could be behavioural, device characteristics, geo-locations, unusual switching between accounts and much more. Fraud and cyber analyst teams are inundated with alerts, many of which can be false. By narrowing the focus of investigations, the analysts only have to investigate genuine priority alerts.
Predict, detect and deter – the holy grail
Every bank and fintech needs to be in a position to predict a problem before it becomes a threat and today’s AI powered solutions are able to detect advanced fraud and manipulation earlier and faster. Similarly, these financial automation oversight engines are adept at identifying previously unidentified vulnerabilities and gaps in third-party systems, thus deterring exploitation.
Using AI technology to strengthen the validation, verification and transaction processes ensures security is enhanced, but not at the expense of the customer journey. Not only will this create a safer and more trusted customer experience, but it will also play a key part in improving company reputation and attracting new customers.
Financial criminals will continually up their game and AI is the only way to stay ahead. Get the right financial automation oversight technology in place, keep one step ahead of the criminals and never sleep on your success.
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1 World Economic Forum and the University of Cambridge Judge Business School, with support from Invesco and Ernst & Young
The article discusses how AI can predict, detect, and deter financial crime in the banking sector.
AI enhances fraud detection and prevention by providing real-time oversight and identifying anomalies in transactions.
It ensures that automated financial processes are secure and compliant, protecting against sophisticated cybercriminals.
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