In the complex world of financial crime, where shadowy figures shuffle money like a game of cards, technology emerges as our hero.
Financial crime is a serious threat to the global economy and society. These crimes can undermine the integrity of financial markets, harm the reputation of businesses, and ease the activities of criminals and terrorists. Financial crime costs the global economy trillions of euros every year and affects millions of people’s lives.
When we talk about the fight against financial crime, we aren’t just referring to the occasional pickpocket or a rogue trader. No, it’s much more intricate than that. Imagine a vast web of illicit activities: Money laundering, insider trading, market manipulation, terrorist financing, among others.
This is the shadowy realm where financial criminals thrive, exploiting gaps in the system to their advantage. Financial crime can have serious consequences as it can erode the trust of customers and investors in the financial sector, or expose businesses to legal, reputational and operational risks.
Our heroes? The compliance officers, auditors and investigators, who tirelessly sift through data to uncover these hidden threats.
Don’t have time to read the whole blog entry? Then watch our “Blog in 1 minute” video for a quick summary of its main points:
But in the fight against financial crime, technology such as artificial intelligence (AI) and Generative AI (GenAI) are game changers. These technologies are revolutionising the way we detect, prevent and combat financial crime, making our financial world safer and more secure. As a quick reminder, the first applications of AI in the financial sector from the 90s’ were on fraud detection and fraud prevention.
In this blog, we explore how technology, particularly AI and GenAI, can help you fight financial crime, and what are the challenges and opportunities that it brings.
In the complex world of financial crime, where shadowy figures shuffle money like a game of cards, technology emerges as our hero.
Financial crime is a serious threat to the global economy and society. These crimes can undermine the integrity of financial markets, harm the reputation of businesses, and ease the activities of criminals and terrorists. Financial crime costs the global economy trillions of euros every year and affects millions of people’s lives.
When we talk about the fight against financial crime, we aren’t just referring to the occasional pickpocket or a rogue trader. No, it’s much more intricate than that. Imagine a vast web of illicit activities: Money laundering, insider trading, market manipulation, terrorist financing, among others.
This is the shadowy realm where financial criminals thrive, exploiting gaps in the system to their advantage. Financial crime can have serious consequences as it can erode the trust of customers and investors in the financial sector, or expose businesses to legal, reputational and operational risks.
Our heroes? The compliance officers, auditors and investigators, who tirelessly sift through data to uncover these hidden threats.
But in the fight against financial crime, technology such as artificial intelligence (AI) and Generative AI (GenAI) are game changers. These technologies are revolutionising the way we detect, prevent and combat financial crime, making our financial world safer and more secure. As a quick reminder, the first applications of AI in the financial sector from the 90s’ were on fraud detection and fraud prevention.
In this blog, we explore how technology, particularly AI and GenAI, can help you fight financial crime, and what are the challenges and opportunities that it brings.
How can technology help in fighting financial crime?
Picture an AI-powered Sherlock Holmes, tirelessly scanning mountains of data for anomalies. Fraud investigations? Piece of cake. Our digital detectives cross-reference watchlists, flagging suspicious transactions faster than you can say “cryptocurrency.” False positives? Not on their watch.
The use of technology, including AI and GenAI, can transform the way we combat financial crime. For instance, AI can act as a smart detective, helping us to identify and investigate suspicious activities and to reduce false positives and negatives.
GenAI, on the other hand, can act as a creative innovator, helping us to generate and test new scenarios, solutions, and strategies and to improve our existing ones. We have a few examples on how you can apply technology to fight financial crime:
Transaction monitoring
Click here to expand or collapseWhen enhancing transaction monitoring systems with AI, you should do it gradually. The traditional approach when it comes to transaction monitoring is usually to implement rule-based systems. These systems operate by applying predefined rules and thresholds to identify potentially suspicious activities. For example, they might flag transactions above a certain amount or those that occur in high-risk regions.
While these systems are straightforward and relatively easy to implement, they can generate a high number of false positives and may struggle to adapt to evolving money laundering tactics. Therefore, enhancing these traditional systems with AI can significantly improve their accuracy and efficiency.
A first phase can be to have an AI-powered behavioural customer segmentation instead of customer segments that are based on static data. As a result, you can tune scenarios with different thresholds depending on the segments (the customer group’s behaviour), which will raise more relevant alerts and less false-positive alerts.
In a second phase, you can create new AI-driven scenarios to identify unusual patterns and analyse customers’ behaviour over time to detect deviations from their typical financial activities. Significant deviations may show potential money laundering or other illicit activities, prompting further investigation.
Customer due diligence
AI-driven systems can automate Know Your Customer (KYC) procedures by extracting and verifying information from documents, and reducing the time and cost associated with manual verification processes.
Technology can also help you to assess the customers’ risk profile by analysing various data points, including transaction history, geographic location and behaviour patterns.
Real-time screening
AI can rapidly screen transactions and customer data against global sanctions lists and Politically Exposed Persons (PEP) databases. With technology, you can streamline and simplify this process, and use natural language processing and generation to extract, process and summarise information from various sources and formats.
Moreover, it can scan and cross-reference watchlists and flag potential matches or risks that require further verification or action. This ensures compliance with regulatory requirements and helps prevent transactions involving sanctioned entities.
Entity resolution
Entity resolution is a complex task and presents many challenges such as misspellings in the data entries, inconsistent formatting, outdated information (for instance, addresses), similar names and attributes leading to false positives, or variety of the data sources and formats.
AI can combine and cross-reference data from multiple sources to accurately identify and link entities involved in financial transactions. This helps you to spot complex networks of individuals and entities that may be involved in money laundering activities.
Case management and fraud investigation
Technology can sift through mountains of data on fraud investigations for you and identify patterns, anomalies and links that would otherwise be missed or take too long to find.
For example, imagine you are investigating a case of fraud involving multiple parties, transactions and jurisdictions. With the right tool, you can automate and accelerate this process, and use artificial intelligence and machine learning to detect and highlight the key evidence and connections.
Indeed, AI can help you by providing advanced tools for analysing and visualising complex transaction networks, making it easier to trace the flow of illicit funds and find key actors.
As for GenAI, you can use it, for example, to create and simulate different financial crime scenarios such as fraud schemes, money laundering networks or cyberattack vectors. It can also generate synthetic data to augment or replace real data for training or testing purposes—for instance, test the system’s effectiveness to detect fake KYC data, or the transaction monitoring system to detect a newly-generated fraud pattern.
But we can’t stress enough that, to develop effective algorithms as well as AI and GenAI applications, you need to have in place robust data management practices (mostly data quality), and continuously refine your processes and solutions.
Technology: a double-edged sword
Technology, like Excalibur, cuts both ways. As we strengthen our defences and boost the compliance teams’ and systems’ crime prevention and detection capabilities, we inadvertently bolster the arsenal of bad actors.
Cybercriminals exploit the same tools meant to protect us. Dark web marketplaces peddle hacking kits, and ransomware attacks cripple entire organisations. It’s a delicate balance—one that keeps our digital knights awake at night.
You probably heard about the recent case of the finance worker in Hong Kong who paid US$25m after a video call with his—apparently—chief financial officer. It turns out, fraudsters tricked him using deepfake technology.
Indeed, AI and GenAI can give people sophisticated and innovative ways to commit financial crime. They can use social engineering, impersonation or deception to trick and persuade victims or compliance staff to reveal financial information or to perform unauthorised or fraudulent transactions.
By knowing the traditional rule-based scenarios that are used in transaction monitoring systems, AI can analyse and manipulate large volumes of data for bad actors to create convincing fraudulent schemes. This includes generating financial transactions that can deceive systems and humans alike.
GenAI also quickly allows people to create a completely new identity to conceal and disguise their real identity and location, and bypass KYC measures (with a fake ID, passport, profile pictures, among others) and sanctions restrictions.
Bad actors can use emerging technologies, such as cryptocurrencies and decentralised finance, to transfer and launder money or assets across borders and jurisdictions, and to evade the scrutiny and oversight of the regulators and authorities.
Therefore, compliance teams and systems need to constantly monitor and adapt to the evolving threats and risks technology poses and invest in the necessary resources and skills to keep up with the pace and scale of innovation. Educating the teams about the potential misuse of AI can help individuals recognise and mitigate their impact.
Humans’ involvement still matters
Within the buzz of servers and the glow of screens, let’s not forget the essential role of people in compliance. Algorithms, while valuable, can’t replace intuition, judgement or ethical nuanced decision-making. The compliance team—our last line of defence—evaluates alerts, weighs risks, and investigates anomalies.
Technology can augment and complement the compliance team’s human capabilities and expertise, but it can’t replace them. They are still essential because:
- They will remain accountable to customers, regulators, and other stakeholders for explaining and justifying the compliance decisions and actions taken, whether they were AI-supported or not.
- They can provide the context and judgement that technology might lack or misinterpret and apply the ethical and legal principles and standards that technology mightn’t fully understand or adhere to.
- They need to oversee the technology and ensure that it’s reliable, accurate and compliant. They should also continuously monitor and audit the performance and accuracy of the algorithms used.
- They can innovate and create new solutions, scenarios and approaches to fight financial crime and learn from the feedback and the technology’s outcomes.
Conclusion
As the sun sets on our digital battlefield, we leave you with this thought: Technology, including AI and GenAI, is our ally, but it’s no silver bullet.
It can help us to prevent and detect financial crime more efficiently and effectively, but it can also pose new challenges and risks that we need to be aware of and address. It can enhance and support the compliance team’s capabilities and knowledge, but it can’t substitute them.
Understanding technology’s dual nature is essential to better prepare for and counteract its malicious use while still benefiting from its positive applications in the fight against financial crime.
What we think
Remember, the next time you tap your contactless card/phone or transfer funds online, you are part of this grand saga—one where technology wields its sword against financial crime. Stay vigilant, stay informed, and may your digital footsteps lead to justice.
Loïc Guillemin, Director, Forensic and Anti-Financial Crime services at PwC Luxembourg