Trends in Global Financial Crime 2024

• Financial crime affects individuals, corporates, financial institutions and governments.
• The problem is massive; USD 3.1tn in money laundering and USD 476bn in fraud.
• Financial crime is growing due to organised crime and technology.
• The burden of prevention largely falls on banks and PSPs, accountants and lawyers lack capability.
• Technology is a cure, but effective integration is required across systems and processes.

How big is money laundering?

According to NASDAQ, USD 3.1tn illicit money laundering flowed through the global financial system in 2023.

Money laundering crimes were USD 783bn drug trafficking, USD 347bn human trafficking and USD 12bn terrorist financing.

Money laundering estimates are the money flowing in/out of the banking systems but exclude transactions in cryptocurrencies.

How big is global fraud?

According to NASDAQ, USD 485.6bn was lost to fraud scams in 2023. 

Losses are likely to be significantly higher as the true number and value of crimes are not reported.

Fraud estimates do not include tax evasion, corruption, bribery, embezzlement, business lost to counterfeit goods, or industrial espionage.

Financial crime by region

Source: NASDAQ

Who pays for financial crime?

According to NASDAQ, financial institutions lost USD 442bn to payments, cheque and credit card fraud in 2023. Losses reduce the funds available to investors, result in increased charges to clients, and lower investment in service.

Individuals lost USD 43.6bn to scams, reducing the potential to consume, invest or afford essential items. The impact terms of victim well-being, economic prosperity, and trust in financial systems is significant.

Key trends in financial crime

According to the Interpol, several drivers exist for the growth in financial crime:

Technology: Artificial Intelligence such as deepfakes enables criminals to conceal their identity, deceive victims, and impersonate others. Fraud becomes real-time and transnational, increasing the incentives for criminals. 

Payment Fraud: Crypto and stablecoin payments bypass money laundering controls and are prevalent in investment fraud. Complex payment routing seeks to spoof controls in traditional banking and payments.

Organised crime: Criminals gain access to expertise, infrastructure and financial services, in some cases sharing this with other bad actors. State–sponsored crime increases. 

Synthetic Identity: Fake names, corporations, and documentation circumvent AML/CTF, sanctions, and PEP checks. 

How do regulators fight financial crime?

Criminals seek gaps and grey areas, operating for a short time then adapting. Regulators face a long cycle of implementing laws, while enforcement agencies must resource and act carefully. This mismatch, and transnational crime, put enforecement behind.

The current financial crime toolkit of governments includes:

• Sanctions lists.
• PEP lists.
• Anti-money laundering (AML) rules.
• Counter-terrorism finance (CTF) rules.
• Increased data sharing and common blacklists.
• Expanding scope to cover gatekeepers like accountancy to legal.
• Tougher standards for banks, payment, crypto, and investment firms when applying for licenses.
• More enforcements and higher penalties for non-compliance.

The basis of regulation is changing and compliance is no longer enough; liability for fraud can be transferred from the victim to the financial institution (UK Authorised Push Payments (APPs)). 

How do financial institutions fight financial crime?

Approaches usually blend technical and GRC processes to create a multi-layer approach. The current toolkit of financial institutions includes:

• AML/CTF, sanctions and PEP checks.
• AI-powered regulatory technology for document and user verification.
• Cybersecurity to prevent phishing, penetration, etc.
• Warning payment initiators if an outbound payment looks suspicious (ML analyses prior patterns).
• Asking payment initiators for Verification of Payee (VoP) and two-factor authentication (2FA).
• Transaction screening of in/outbound payments and velocity checks on card processing (ML analyses prior patterns).
• Implementing additional controls across operations, compliance, risk, and internal audit.
• Reviewing risk more frequently.
• Increased co-operation among industry.
• Increased data sharing and common blacklists.
• Exiting high-risk products and business lines.

Financial institutions must meet higher demands at a time when their technological and financial capabilities are stretched.

Only close integration of humans, technology and process will create the ability to defend at scale, and be agile as crime and regulation evolve.

Kroll believe most financial institutions will invest heaviliy in artificial intelligence and machine learning.