As technology advances and evolves, so do criminals. But FinTech has the potential to help banks stay one step ahead. Whether it’s digital currency tracking, data connectivity or machine learning, more powerful IT systems combined with technological advances open up new possibilities in the fight against money laundering.
As digital currency circulation grows, so does concern about how to regulate it. Blockchain technology could hold the key to tracking digital currency. Blockchain is a public ledger that records transactions, which are then independently verified. Once a payment is confirmed, it cannot be changed. This makes every payment to a digital wallet traceable and trustworthy. Regulators are likely to require verified wallets to be KYC and AML compliant. Customers would enter all their personal information as a “blockchain”. This information would be encrypted and stored in the blockchain. The customer would then receive a password to access this information. If the customer wants to enter into a business relationship with a financial institution, they would provide the password, allowing the financial institution access to their personal information. The financial institution now has access to the customer’s digital currency transaction history and can verify the customer’s identity.
Another FinTech solution that has great potential to help combat money laundering is machine learning. Machine learning uses algorithms, rather than a set of explicitly programmed instructions, to analyse information, make decisions and learn from those decisions. Over time, machine learning then modifies its own code, without human supervision, so that it can make better, faster and more accurate decisions. Machine learning technology can examine verified money laundering and identify often obscure predictive variables that go unnoticed by data scientists. With huge volumes of data and more powerful computing power, algorithms can detect subtle patterns of criminal activity. By implementing machine learning technology, banks can reduce the number of false alerts, allowing investigators to spend more time examining high-risk cases.
Putting it all together:
When banks invest in a strategic versus reactive approach, they can reduce their risk and get the most out of FinTech anti-money laundering solutions. The first thing banks need to consider is assessing their entire KYC and AML process from start to finish. When starting a business relationship with a new customer, how banks onboard them and verify their identity sets the foundation for their entire AML process. Ensuring that individuals are vetted through the correct database to identify any links to criminals, terrorist groups, public figures or politicians is crucial in defending against money laundering. Next, banks need to consider how to link all customer information to KYC and AML data to detect anomalies or suspicious activity. One FinTech solution to consider is machine learning, which can link individuals and customer investments, associated entities and individuals, and sanctioned data. Machine learning can detect patterns often missed by data scientists when looking at the big picture, leading to fewer false alerts. As banks increasingly rely on technology in their day-to-day operations, it’s easy to see how FinTech fits into their anti-money laundering processes. The benefits of FinTech solutions are beginning to outweigh the challenges of implementing technology into AML practices. FinTech has great potential to save time and money while making more accurate decisions, which ultimately helps better serve bank customers.
