According to a recent market impact report by AML RightSource and HFS, “Regulatory risk and compliance programs will fail to scale if they do not embrace artificial intelligence and automation with their people, partners, and peers.”
While financial institutions grapple with a myriad of diverse obstacles, two universal challenges confront banks of all sizes:
Over the last decade, we have seen an unprecedented shift in consumer payment behavior, with debit and credit cards becoming part of everyday life. Long gone is the adage “Cash is King.” Likewise, alternate payment methods continue to challenge the traditional, allowing faster payments and more inclusion of the unbanked in the global financial system.
As digital payment trends continue to proliferate, the sheer volume of transactional data passing through disparate sources and aged infrastructure within institutions presents a massive challenge when trying to identify suspicious behavior and stop financial crime.
The conventional approach has been to add more people to the equation. But that simply feeds another growing challenge: it's hard to train, recruit, and keep a large number of top performers, let alone backfill a departure. So, how can we minimize the reliance on large teams? Because at the core, we're going to have more and more trouble recruiting and retaining the talented professionals we need in this space to deal with the increasing volumes of data.
Then, when you go a layer deeper, analysts can spend between 80-95% of their day clearing false positive alerts. So, the next question is: how can we enrich the jobs of analysts and investigators and elevate them to focus on complex investigations and decision-making tasks instead of repetitive and mostly benign tasks?
Contemporary payment fraud prevention began in 1992 with the introduction of Falcon Fraud Manager by HNC Software, which deployed analytics to evaluate the authenticity of credit card transactions in real-time. The adoption of this software by financial institutions meant that any institution that lagged became an immediate target for fraudsters and bad actors.
Likewise, governments and regulatory bodies failed to fully grasp the implications of cryptocurrencies and approached them with conjecture. However, instead of fading away, cryptocurrencies have steadily increased in both value and popularity, leaving authorities scrambling to find effective ways to regulate them.
We are edging to the precipice of history repeating itself as institutions begin to adopt Artificial Intelligence (AI) and automation into their compliance ecosystems.
Market shifts, digital transformation, and the increasing complexity of regulatory requirements create both challenges and opportunities for financial institutions.
On one hand, the introduction of AI-driven solutions is poised to transform and redefine compliance over the coming years. These data-driven solutions are designed to automate, integrate, and scale. The result is a system that guides better decision-making and risk management – promising a future of efficiency and effectiveness. Likewise, regulators have a desire not to be left behind again as the industry moves forward and are increasingly recognizing the benefits of RegTech, paving the way for more support and adoption.
On the other, while analytic underpinnings of anti-crime software have proven that good can overcome evil, we still have to be realistic in setting expectations about what these tools and technologies can do. AI is not a silver bullet; it cannot replace the need for human judgment, decision-making, or oversight, and the biggest mistake leaders can make is to assume it's better than it is.
This assumption can lead to several pitfalls: trusting the output unquestioningly, neglecting to train employees appropriately on the process and risks, unrealistic stakeholder expectations, overlooking human intuition, and inadequate analysis of KPIs, use cases, and customer value.
Adopting AI is a delicate balancing act between innovation and human oversight, and by acknowledging its limitations rather than ignoring them, we can exercise the proper duty of care and unlock the full potential of human-AI collaboration.
While RegTech effectively manages big data – equipping employees with comprehensive and powerful decision-making tools at their fingertips – it doesn't negate the need for human intervention, and talent remains a major challenge, especially when the functional and technical requirements of compliance are changing.
The design and implementation of these solutions into compliance programs necessitate time, dialogue, and domain expertise. Once in place, RegTech solutions must be reviewed and assessed regularly to ensure they function correctly and align with the latest regulations, with potential issues promptly identified and addressed. The need for human interpretation and oversight makes it challenging for in-house compliance teams to keep pace.
Third-party providers can often offer a full suite of advanced technology tools coupled with subject matter experts that create a smarter, cost-effective solution without the pressure for institutions to expand internally. This partnership model, like the one AML RightSource deploys with its clients, helps to overcome talent shortages and drive AI and automation adoption in meaningful ways that directly impact an organization’s capability to remain compliant and take the fight to the illicit actors on the other side.
Rationalizing compliance IT infrastructure, integrating new technologies and platforms into compliance processes, enabling APIs, managing data, designing, and operationalizing – tech-enabled managed services partners are well equipped to develop and support all around. They also bring process frameworks, best practices, and knowledge from performing similar services for other clients to accelerate delivery.
These partnerships are invaluable and vital for expanding capacity in financial crime and regulatory compliance and will play a crucial role as we look toward the future of compliance.
“It's essential to collaborate with someone who has expertise in financial crime, not just someone who is proficient in AI. Without this industry-specific knowledge, you'll find yourself spending a lot of time educating them about your business, and that's only going to slow you down.” – Phil McLaughlin, EVP and CTO, AML RightSource.
“The advantage of a service partner is that products and offerings are supported, and code is reviewed and maintained.” – Eric Kringel Global Financial Crimes Risk and Compliance Executive Formerly Circle, Deutsche Bank, Citi, and FinCEN.
To learn more about how we blend human expertise and the latest technology to fight financial crime, fill out our contact form and let’s start the conversation.
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