The Future Of AML Solutions In a Digital-first World

With the pandemic blindsiding people, businesses, and economies near the beginning of last year and forcing a stay-at-home mindset, companies found themselves having to accelerate the digitization of their services even more than they have been the past few years.

After all, with people staying home most of the time and limiting their exposure to the outdoors, businesses would have to find better and faster ways of catering to the new normal. While this urgency did bring about innovative new ideas and platforms, it also paved the way for new methods of cybercrimes and money laundering seeking to take advantage of the same new tech.

In response to this, updates to existing AML solutions are continuously being made and new systems are rapidly being developed to combat the latest in money laundering threats.

The coming years are sure to introduce new methods of laundering money but the future of anti-money laundering looks to be exceedingly bright. Here are some plausible strategies that we could see implemented in the near future.

Automation is inevitable

Despite AML investigation processes remaining mostly manual so far, there have been big strides in the realm of artificial intelligence as far as the investigation of alerts is concerned. By implementing machine learning and AI, organizations can more efficiently analyze false positives and can apply the same technology to even decide on new alerts.

False positives tend to significantly slow down business operations and take away resources that could be better used in fleshing out true positives. Companies that encounter a high volume of false positives often find themselves hiring a large AML back-office team to keep up with it.

Through the automation of AML, businesses can reduce the alerts that require manual investigation by up to 30%, saving the company money and manpower in the process.

AI can also assist with the significant growth in the volume of online transactions by using its advanced technology to generate in-depth reports on alerts. This helps analysts review data more efficiently and at a broader scope, allowing for better decision-making on alerts and an overall shorter turnaround time for cases.

Taking KYC to the next level

Know your customer, better known nowadays as KYC, has quickly transitioned from being a menial part of a security checklist into one of the core pillars of AML compliance for financial institutions as well as various other organizations.

What started as due diligence towards monitoring customers is now expanding to also encompass other parties, including partners, vendors, employees, and more. Customer monitoring has also become more comprehensive in general, adding more focus to the different customer categories which include retail, charities, corporate, small and medium enterprises, etc.

Certain financial institutions have also begun implementing new forms of security and identification for their customers and employees, which includes facial recognition software and forensic scan based digital identification and verification.

Bringing customer reviews closer to real-time may be in the cards

Most financial institutions undergo periodic customer reviews every 1 to 5 years depending on the risk level of the customers. Given how fast-paced today’s digital world is, waiting years to update customer information could introduce some serious risks in itself. How effective is customer monitoring if their data is inaccurate, after all?

With that in mind, the topic of dynamic KYC is currently being explored, with the idea being that organizations would progressively update their customer profiles whenever a significant change has been identified. Given the sheer amount of data that needs to be processed and the speed at which it needs to be done, AI is the most likely way to accomplish this.

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