Finance
Optimizing KYC processes to prevent money laundering
Published by Jessica Weisman-Pitts
Posted on October 25, 2022
4 min readLast updated: February 3, 2026
Global Banking & Finance Review®
Company
Published by Jessica Weisman-Pitts
Posted on October 25, 2022
4 min readLast updated: February 3, 2026
By Chor Teh, Director, Financial Crime Compliance Industry Practice Lead at Moody’s Analytics,
Despite the continual development of solutions to combat money laundering, criminals still have the capacity to get ahead. Indeed, it is hard to escape news stories of money laundering activity in the media. Presently, anti-money laundering (AML) measures can demand huge amounts of time, capital, and vital resources from organizations. And still criminals find ways around systems and processes.
With a growing complexity in global supply chains and counterparty relationships, money laundering and the exploitation of financial services are global issues for regulators, corporates, and compliance professionals alike. Optimizing KYC processes however can be an invaluable tool for organizations when it comes to preventing bad actors using them to legitimize dirty money or hide human rights violations.
Digital economy grows; crime grows
New and advanced techniques are constantly emerging to exploit lawful individuals and organizations. These criminal activities have arisen in part due to a rapid expansion of the digital economy – the explosion of fintechs and Neobanks has offered new methods for money laundering.
Preventing money laundering has also become more challenging as the digital economy is a borderless economy. Organized crime groups engage in cross border activity, to take advantage of regulatory blind spots and to insert illegal operations into supply chains. Consequently, regulators, financial services businesses, and compliance teams are finding themselves playing catch up, rather than besting criminals.
With all that said, for criminals to legitimize their money and circulate it back into the mainstream financial system is not easy, and it’s where they have vulnerabilities.
Organizations can and do prevent money laundering daily through AML compliance, risk management processes, and enforcement of rigorous KYC. Regulatory technology is one method that has improved these procedures.
Also, regulators, law enforcement, and financial institutions are uniting resources in support of legislation such the German Supply Chain Due Diligence Act. And they are sharing information to create more corporate transparency, which helps uncover counterparty risk. Implemented effectively, organizations can use data and automation as the foundation for a robust KYC framework.
Leaning on KYC
Automating KYC processes has numerous advantages, not least, it improves the efficiency of the KYC processes themselves. Automated risk-engines can process the intensive workloads involved in continually monitoring risk and carrying out routine checks. This makes them ideal for executing AML processes to uncover politically exposed persons (PEPs) and sanctioned individuals for example.
Automating KYC and introducing AI can also be integral to identifying recurring patterns which might point towards criminal activity. Automation is adept at spotting these recurring patterns and raising flags for investigation into possible money laundering threats.
However, automation will only get a firm so far. Risk is continually changing and evolving, and recognizing new threats is something automation alone cannot tackle. Professional insight is invaluable here – a person carrying out the ‘sniff test’ and detecting that something simply doesn’t feel right.
AI models are not yet able to accurately predict and identify new behaviors, meaning human involvement is crucial for spotting new risks and new forms of criminal activity. Human influence and effective technology working together is the most powerful and effective combination in the fight against financial crime.
Hitting the right balance
Although automated technology is excellent at developing efficient KYC processes, it is not complete enough to operate independently and understand the full nuance of criminal threat. It is paramount that financial institutions truly understand their customers and counterparties to properly control risk.
Finding the balance between automation, technology, and cognitive thinking is the most effective strategy for optimizing KYC processes. It enables humans to identify the complexity and variation in crime while ensuring the most informed risk-based decisions are being made on behalf of a business.
KYC stands for 'Know Your Customer,' a process used by financial institutions to verify the identity of their clients to prevent fraud and comply with regulations.
AML stands for 'Anti-Money Laundering,' which refers to laws and regulations aimed at preventing criminals from disguising illegally obtained funds as legitimate.
Risk management involves identifying, assessing, and prioritizing risks followed by coordinated efforts to minimize, monitor, and control the probability of unfortunate events.
Regulatory technology, or RegTech, refers to the use of technology to help companies comply with regulations efficiently and effectively.
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