From money laundering and terrorist financing to bribery and human trafficking, financial crime undermines the very foundation on which we’ve built our financial systems. Current investments in AI and biometrics already prove inadequate in deterring financial crime. Anti-money laundering (AML) and fraud-fighting executives report a

concerning increase in financial crime in just the last year. BioCatch expects that trend to continue into 2024 and beyond.

Consumers and, increasingly, governments look to financial institutions to combat fraud and prevent financial crime. Consumers spend more and more of their lives online, posting personal updates to social media, shopping on e-commerce sites, and paying bills, transferring funds, and checking balances from their phones. It is no longer possible to operate without a digital identity, leaving every

one of us vulnerable to bad actors, who find in this vast digital world ample opportunities to scam us.

From money laundering and terrorist financing to bribery and cybercrime, financial crime works to undermine the foundation on which all financial systems are built throughout society. Current investments in AI and biometrics are not enough to deter financial crime. As a result, financial crime and fraud executives have reported a concerning increase in financial crime in the last year – and that trend is unlikely to slow down anytime soon.

Banks and financial institutions are charged with combatting fraud and preventing financial crime. Consumers are conducting more and more activities online, posting personal updates on social media, shopping online, and using online banking services. It is no longer possible for people to operate without a digital identity. This reality represents a significant vulnerability for bad actors to exploit for fraudulent purposes. Bad actors are leveraging elements of our digital identities for personal gain through insurance fraud, mortgage fraud, check fraud, and identity theft.

What we found is that banks are facing a variety of emerging threats, many of which are powered and/or enabled by AI. At the same time, banks are investing in AI and integrating solutions that leverage this technology. But it isn’t enough. Further investment is needed. While most financial institutions are already using AI for financial-crime detection (74%) and fraud detection (73%), all respondents expect both financial crime and fraud activity to increase in 2024.

Thanks in part to AI, criminals are innovating faster than banks can keep up.

Bad actors share intelligence with other fraudsters, helping to improve attack methods and avoid detection. To combat fraud and financial crime in 2024, banks must also share with their competitors.

Rules and regulations make this process difficult, generating information silos that make collaboration difficult even within individual banks.

This allows threat actors to stay a step ahead. Financial

institutions must assess how they can take more thoughtful,

forward-thinking action to share intelligence and account

information to be more agile and rectify this problem.

Sharing information, collaborating with regulatory authorities, and implementing emerging technologies will be vital in combatting fraud and financial crime in 2024 and beyond.

Employing behavioral biometric intelligence will allow financial institutions to leverage the only element of digital identity that is truly human and almost impossible to replicate, thus providing better protection for their customers. Continued evolution will ensure financial institutions are ready for whatever the future may bring.

The pandemic sped up this digitalization of the banking world. Further enhancements via peer-to-peer payment services offering immediate transfers have led to more and more consumers relying on digital banking for their financial needs.

While the move towards online banking and financial services has increased convenience for consumers, it’s also created additional risks for banks and their customers and opportunities for threat actors. More than half (56%) of respondents globally report that financial-crime activity has increased in the past year.

Likewise, more respondents from North America expect financial-crime activity to increase in 2024 than their counterparts in other regions. This finding is not surprising considering a 2022 report which found the United States was the top destination for stashing money illegally, ranking ahead of traditional tax shelters like Singapore, Switzerland, Luxembourg, and the Cayman Islands.

In fact, in 2021 former Treasury Secretary Janet Yellen said, “In the popular imagination, the money laundering capitals of the world are small countries with histories of loose and secretive financial laws. But there’s a good argument that, right now, the best place to hide and launder ill-gotten gains is actually the United States.”

More than one in five (22%) respondents globally say their organization is not currently using AI for financial-crime detection but plans to start in the next six months.

Globally, banks use AI to detect financial crime through advanced machine learning (83%), natural language processing (72%), and deep learning (67%). Financial institutions can use AI technology to further understand user behavior and identify suspect activity.

Organizations worldwide face a multitude of problems regarding the ability to combat financial crime, including data security and privacy (36%), cybersecurity (31%), and integration issues in technological systems (23%). AI also poses an additional problem, as nearly seven in 10 (69%) say criminals are better at using AI to enact financial crime than banks are at using it to detect the crimes.

From the costs associated with investigating and uncovering financial crime to the costs of remediation, the monetary impact of financial crime is huge. Only one in four (28%) globally say their company spent less than $5 million in operational costs associated with investigating, combatting, or rectifying financial crime or consequences of financial crime in 2023. On the other hand, 16% report their company spent $25 million or more.

Furthermore, the cost of financial crime extends beyond measurable monetary losses. Financial crime can also cost organizations through damage to their reputation, causing negative perception among existing clients, potential customers, and investors, leading to further losses. Penalties for failed

compliance with AML can be devastating to financial institutions. In 2023, the Federal Reserve fined Deutsche Bank and its U.S. affiliates $186 million for failing to address AML shortcomings. Binance, the world’s largest cryptocurrency exchange, was fined $4.3 billion in relation to AML violations. Investing in tools to fight financial crime is imperative to business success in 2024.

Survey respondents agree that all types of fraud – from payment fraud to credit card fraud to identity theft – either stayed the same or increased in the past year.

Approximately three-quarters of global fraud-management decision makers expect fraud activity to stay the same or increase in 2024 in both the total value of financial losses (76%) and volume (74%). Decision makers in North America are most likely to be pessimistic about fraud activity in 2024 compared to other regions.

As fraud continues to evolve online, often powered by technologies like AI, many organizations are turning to the same technologies to drive improved detection and response.

Many organizations are already using technologies like AI to improve their ability to detect fraud, while others indicate plans to adopt AI for fraud detection in the near future. Nearly three-quarters (73%) of organizations are currently using AI for fraud-detection.

Concerningly, two in five (41%) anti-fraud decision-makers say fraud and financial crime are handled in separate units (i.e., different teams, divisions, etc.) with no cross-collaboration. Three in 10 (31%) say fraud and financial crime are handled in separate units with cross-collaboration.

Only 28% report that fraud and financial crime are handled by the same unit at their organization. Siloed operations with a lack of communication pose a major issue to an organization’s ability to accurately track and successfully combat both financial crime and fraud.

AI allows these threat actors to automate tactics and scale attacks beyond traditional limitations. AI and large language models (LLMs) are also being used to create believable messages for social-engineering attacks, power voice scams, and fuel deepfake videos.

The use of AI in social-engineering attacks will make events like the hack of MGM–which resulted in the exposure of personally identifiable customer information and cost the company $100 million–much more prevalent in the future. This is especially concerning given that more than 90% of all cyber-attacks begin with phishing.

Furthermore, a 2022 IBM report found that targeted phishing attacks that included phone calls were three times more effective than those that did not.

Fraud-management decision makers expect these threats to result in major losses at their organizations. Globally, respondents expect automating scam tactics to scale attacks (45%), AI scanning for leaked PII (42%), and LLMs drafting believable messages for social engineering (36%) to have the highest related dollar losses for their organization. AI-based threats also proved to be damaging for organizations in 2023. Only three percent of respondents reported that their organization did not lose anything to AI-based or AI-driven threats in 2023.

Global organizational losses varied in 2023 – with some organizations experiencing fewer losses while other companies were faced with recovering from significant damages. One in three (33%) lost less than $5 million, while 12% lost $25 million or more to AI-based threats in 2023.

Fraudsters can use synthetic identities to apply for credit cards and open new accounts to borrow or launder money. Identified as the fastest-growing type of financial crime in the United States in 2019 by the Federal Reserve, synthetic identities have largely escaped detection, with an estimated 85-95% of applicants identified as potential synthetic identities not flagged by traditional fraud models. Synthetic-identity fraud costs companies billions and is also a contributing factor to the increase in new-account fraud.

These organizations were largely able to uncover these synthetic identities within three months, with more than one-third (35%) discovering the fraud within 30 days and one-quarter (26%) within 90 days. Only 16% were able to uncover the synthetic identities within 24 hours.

As synthetic identities become increasingly difficult to identify due to the evolution and use of AI among bad actors, organizations will need to allocate appropriate resources and processes to uncovering this type of fraud. Moving forward, it will be integral for financial institutions, law enforcement agencies, and regulatory authorities to share information to better combat this synthetic-identity fraud.

Organizations also use AI technology (48%) to uncover these synthetic identities, proving that while the use of AI by bad actors still poses a threat to financial institutions, it can also be greatly beneficial in proactive detection of fraud, such as synthetic identities.

Nearly half of organizations have also used anomalies in identity elements (48%) and behavioral analysis (41%) to uncover synthetic identities.

The evolution of behavioral analysis to incorporate both expertise in online user behavior and the psychology of cybercrime and social engineering has resulted in behavioral biometric intelligence, an integral tool in identifying fraud.

Behavioral biometric intelligence leverages elements of user behavior like application fluency, data familiarity, and expert behavior to uncover fraud in the new-account opening process. It will be integral for financial institutions to apply behavioral biometric intelligence to gain insights that traditional fraud-prevention tools do not offer and successfully distinguish between legitimate users and cybercriminals.

Organizations can do this by implementing evolving technologies like AI in addition to tactics like behavioral biometric intelligence.

Financial institutions can also collaborate with other banks, industry bodies, and law enforcement agencies to share information and ensure greater protection and prevention across the industry.

While organizations look to AI to improve protection and fraud-prevention capabilities, the technology continues to be a double-edged sword, with bad actors employing AI to develop increasingly advanced attacks. AI can be used to create deepfake videos, craft more realistic messages to be used in social-engineering attacks, clone voices to take advantage of voice verification systems, and more.

Nearly nine in 10 (88%) fraud decision makers say more³ information should be shared between banks, financial institutions, and government or regulatory

authorities in the next one to two years to combat financial crime and fraud.

While once considered cutting-edge and a promising answer to complex threats, voice verification will no longer be adequate for financial institutions to protect their customers.

As such, financial institutions will need to use a strategic combination of authentication methods to minimize user frustration while maximizing protection. Notably, of the top authentication methods listed below, only behavioral biometric intelligence reduces friction for the end user.

Organizations must evolve protocols and utilize the vast trove of historical data collected around customer behavior through behavioral biometric intelligence. Failing to embrace behavioral biometric intelligence, coupled with a lack of information-sharing across the industry, will allow financial criminals to continue to win.

Paying close attention to customer behavior and intent behind the biometrics, device, geo-location, and other machine-created signals can ensure financial institutions truly know their customers.

By applying methods like fraud telemetry, continuous behavioral sequencing, and predictive intelligence, leading financial institutions and banks can keep customers safe from digital fraud and build long-lasting trust.

For financial institutions and banks to adapt and appropriately tackle the obstacles presented by modern financial crime and fraud, they must use and share behavioral biometric intelligence if they hope to leap-frog criminal innovation and protect customers.

Many organizations are already taking steps to support customers that fall victim to AI scams like Elon Musk’s crypto investment YouTube deepfake, including:

Nearly all (97%) fraud management experts agree that nations should strengthen international cooperation to share intelligence and coordinate efforts in enforcing sanctions surrounding fraud or financial scams.

Virtual assets also pose a significant threat to the integrity of financial systems and combatting financial crime. The U.S. Treasury 2024 report noted: “While the use of virtual assets for money laundering continues to remain far below that of fiat currency and more conventional methods that do not involve virtual assets, U.S. law enforcement agencies have observed virtual assets being misused for ransomware, scams, drug trafficking, human trafficking, and other illicit activities."

Indeed, two in five (42%) global respondents think that international collaboration will be key to combatting the use of cryptocurrencies to fund criminal activities.

Those in APAC are most confident that AI will lead to more revenue (73%), followed by North America decision-makers (64%).

According to respondents, AI is also expected to impact several areas of financial-crime prevention, from detection to compliance.

Respondents in EMEA also believe that regulatory compliance will be affected by AI, with half (50%) reporting that regulatory compliance will be most impacted by AI in 2024 in comparison to decision makers in North America (37%) and APAC (35%).

As to whether AI will positively impact their organization’s ability to comply with regulatory requirements, the jury is still out.

While 43% think the use of AI has made it more difficult⁴ for their organization to comply with regulatory requirements, approximately an equal percentage (46%) believe it has made it easier⁵ to comply. AI will also prove useful in combatting various activities, attacks, and threats, from social-engineering attacks to identity theft and even check fraud.

From combatting global financial crime to protecting their organization and their customers from fraud, banks will need to do even more in the future. Threat actors are sharing intelligence among themselves. Shared intelligence allows attackers to evolve and succeed, even though banks are investing more in technology to detect and prevent fraud and financial crime.

This is of great importance, especially as the consequences of fraud and financial crime grow in impact and monetary value. Banks, financial institutions, and regulatory authorities must share more information to stand a chance against combatting and preventing financial crime and fraud in 2024.

Financial institutions must evolve and transform to survive this unprecedented era of rapidly increasing fraud and financial crime.

By understanding what makes their customers uniquely human, financial institutions can protect customers from even the most advanced types of fraud while providing the simple, personalized customer experience that drives brand loyalty.

Despite financial institutions increasingly investing and employing technologies like AI and behavioral biometric intelligence, experts and practitioners in the industry largely expect financial-crime and fraud activity to continue to increase in the next year.

This finding shows that the current level of investment is simply not enough. Banks will need to adopt a new approach to successfully combat fraud and financial crime. Banks who are not investing in innovative approaches to detect financial crime and fraud will put themselves and their customers at great risk.

The findings detailed in this report are based on data collected by TEAM LEWIS through an online survey of 600 professionals within fraud management, anti-money laundering, and risk and compliance. All respondents were of manager-level or above at banking or financial services companies in the United States, Canada, France, Germany, Spain, the United Kingdom, the United Arab Emirates, Netherlands, Sweden, Australia, and India.

There were 200 responses per region (NorthAmerica, EMEA, and APAC). Data was collected from January 19 to February 2, 2024 with a margin of error of +/- 3.9 percentage points.

BioCatch stands at the forefront of digital fraud detection, pioneering behavioral biometric intelligence grounded in advanced cognitive science and machine learning.

BioCatch analyzes thousands of user interactions to support a digital banking environment where identity, trust, and ease coexist. Today, more than 30 of the world’s largest 100 banks and more than 180 total financial institutions rely on BioCatch Connect™ to combat fraud, facilitate digital transformation, and grow customer relationships. BioCatch’s Client Innovation Board, an industry-led initiative featuring American Express, Barclays, Citi Ventures, HSBC, and National Australia Bank, collaborates to pioneer creative and innovative ways to leverage customer relationships for fraud prevention.

Approximately three-quarters of global fraud-management decision-makers expect fraud activity to stay the same or increase in 2024 in both the total value of financial losses (76%) and volume (74%). Decision makers in North America are most likely to be pessimistic about fraud activity in 2024 compared to other regions.

As fraud continues to evolve online, often powered by technologies like AI, many organizations are turning to the same technologies to drive improved detection and response.

Many organizations are already using technologies like AI to improve their ability to detect fraud, while others indicate plans to adopt AI for fraud detection in the near future. Nearly three-quarters (73%) of organizations are currently using AI for fraud-detection.

Concerningly, two in five (41%) anti-fraud decision-makers say fraud and financial crime are handled in separate units (i.e., different teams, divisions, etc.) with no cross-collaboration. Three in 10 (31%) say fraud and financial crime are handled in separate units with cross-collaboration.

Only 28% report that fraud and financial crime are handled by the same unit at their organization. Siloed operations with a lack of communication pose a major issue to an organization’s ability to accurately track and successfully combat both financial crime and fraud.

Respondents agree that all types of fraud – from wire fraud to credit card fraud to identity theft – have stayed the same or increased in the past year. Approximately three-quarters of global fraud management, anti-money laundering, and risk and compliance decision makers expect fraud activity to stay the same or increase in 2024 in both value (76%) in terms of the total value of the financial losses and volume (74%).

Despite the importance of combating financial crime and fraud, many organizations are still utilizing siloed operations. Concerningly, two in five (41%) fraud decision makers say fraud and financial crime are handled in separate units (i.e., different teams, divisions, etc.) with no cross-collaboration. Three in ten (31%) say fraud and financial crime are handled in separate units with cross-collaboration. Only twenty-eight percent report that fraud and financial crime are handled by the same unit at their

organization. Siloed operations with a lack of communication pose a major issue to an organization’s ability to accurately track and successfully combat both financial crime and fraud.

More than one in five (22%) respondents globally say their organization is not currently using AI for financial-crime detection but plans to start in the next six months.

Globally, banks use AI to detect financial crime through advanced machine learning (83%), natural language processing (72%), and deep learning (67%). Financial institutions can use AI technology to further understand user behavior and identify suspect activity.

Organizations worldwide face a multitude of problems regarding the ability to combat financial crime, including data security and privacy (36%), cybersecurity (31%), and integration issues in technological systems (23%). AI also poses an additional problem, as nearly seven in 10 (69%) say criminals are better at using AI to enact financial crime than banks are at using it to detect the crimes.

From the costs associated with investigating and uncovering financial crime to the costs of remediation, the monetary impact of financial crime is huge. Only one in four (28%) globally say their company spent less than $5 million in operational costs associated with investigating, combatting, or rectifying financial crime or consequences of financial crime in 2023. On the other hand, 16% report their company spent $25 million or more.

Furthermore, the cost of financial crime extends beyond measurable monetary losses. Financial crime can also cost organizations through damage to their reputation, causing negative perception among existing clients, potential customers, and investors, leading to further losses. Penalties for failed

compliance with AML can be devastating to financial institutions. In 2023, the Federal Reserve fined Deutsche Bank and its U.S. affiliates $186 million for failing to address AML shortcomings. Binance, the world’s largest cryptocurrency exchange, was fined $4.3 billion in relation to AML violations. Investing in tools to fight financial crime is imperative to business success in 2024.