AI’s promise in Asian financial crime prevention
The evolving landscape of financial crime prevention presents significant challenges for institutions across Asia. In an insightful webinar, “Advancing model maturity, predictive AI, and generative AI deployment to transform financial crime compliance in Asia,” chaired by Brad McLean, cofounder at Regulation Asia, experts delved into the potential for artificial intelligence (AI) and its subsets—predictive AI and generative AI (gen AI)—to revolutionize financial crime compliance across Asia.
The expert panelists offered a comprehensive overview of the current state of AI adoption in the region and provided six actionable recommendations for institutions eager to harness the transformative power of AI.
The urgency of AI adoption in financial crime prevention
Financial crime is an ever-growing challenge, with estimated costs reaching 6.7% of the global GDP. The need for robust, sophisticated defenses has never been more pressing. AI technologies provide new insights into unstructured data, transforming the detection, risk assessment, and compliance systems currently in place.
However, regardless of its substantial potential, integration of AI in financial crime compliance remains limited despite significant interest from institutions. Traditional barriers, such as outdated systems and fragmented regulations, continue to hinder progress. SymphonyAI’s APAC SME on financial crime and compliance Craig Robertson emphasized the importance of understanding the maturity of AI adoption across Asia’s financial institutions, pointing out that while some institutions have begun incorporating machine learning into their frameworks, many remain at a nascent stage of AI deployment.
BNY Mellon’s APAC head of financial crime compliance Thomas Hill added, “Disruption exists on the regulatory side, the technology side, and internally into your organization. The combination of these things amplifies the difficulty for someone to come with a clearly defined solution in this space.”
Assessing AI deployment maturity
A recent SymphonyAI and Regulation Asia report highlights the disparate stages of AI adoption among Asian financial institutions. While some have begun building foundational data infrastructure and using basic predictive models, others are venturing into more advanced implementations, incorporating machine learning and even experimenting with GenAI. Such uses can be seen with Sensa Investigation Hub and its Sensa Copilot feature.
SymphonyAI’s Robertson observed that “AML transaction monitoring seems to be the greatest focus right now,” with areas such as KYC, data refreshers, and anomaly detection following closely. He noted that AML transaction monitoring’s low hit rates present a prime opportunity for AI in financial crime prevention to enact change, explaining how AI’s capabilities in automation and risk detection can significantly improve effectiveness and efficiency. This use case has been seen in other continents, including African bank Absa’s use of SensaAI for AML, which saw a 77% reduction in false positives.
BNY Mellon’s Hill added that “the rate of disruption in both the technical and regulatory space is significant,” suggesting that the challenges institutions face often stem from a lack of understanding and prioritization of AI capabilities. He drew attention to the unpredictable regulatory landscape, which poses a significant hurdle for organizations operating across multiple jurisdictions.
Overcoming barriers to AI Integration
The webinar’s findings stress the importance of moving past existing barriers and embracing AI’s potential. Hill highlighted regulatory uncertainty as a primary obstacle, stating, “it’s difficult to articulate the benefits you’re going to get if you may need to move the goalposts… Regulatory uncertainty gives folks pause, not just in the delivery space, but also at the senior management level, as there’s a risk of execution and investment not coming to fruition.” The panelists agreed that greater clarity and guidance from regulators would significantly bolster AI adoption.
Robertson pointed out that “countries like Hong Kong and Singapore have made progress in issuing AI guidelines,” which provide a level of clarity for institutions (SymphonyAI contributed to Singapore’s proposed model AI governance framework). He emphasized that achieving regional harmony in regulation would further enhance AI’s integration into financial crime compliance processes.
The key to overcoming these challenges lies in strategic recommendations that institutions can employ to bridge the gap between AI’s potential and its current implementation. These include:
- Expanding AI applications beyond customer-facing functions
- Focusing on high-impact use cases
- Starting with scalable pilots
- Showcasing effectiveness in leadership
- Improving governance
- Proactively engaging regulators
Prioritizing AI developments
In exploring the future priorities for AI deployment in financial crime investigation programs, both panelists stressed the importance of aligning AI initiatives with broader business objectives. Robertson envisioned a future where predictive and GenAI work in tandem to offer comprehensive solutions across various risk dimensions.
Hill noted that “connecting the risk outcomes with AML transaction monitoring, onboarding, and other areas will lead to a more integrated risk management approach.” He emphasized that this integration would enable institutions to better coordinate resources and focus on genuine risks, thereby streamlining processes and improving overall effectiveness.
As financial institutions begin this journey, it’s crucial to keep in mind that while AI can enhance efficiency, the true goal should be to improve the overall effectiveness of financial crime prevention measures. This involves not only using AI for immediate gains but also ensuring its deployment contributes to a nuanced and sophisticated understanding of financial risks.
Futureproofing financial crime prevention programs
For many organizations, the path forward will be characterized by a balance of adopting advanced AI technology and ensuring robust financial crime compliance with evolving regulations. Financial institutions must embrace this technological revolution with an open mind and a commitment to continuous improvement.
Robertson highlighted the need for organizations to build internal capacity and adjust to the new realities posed by AI. Hill added, “AI is a tool, a capability, but in order to affect that capability, we need to invest in data, model development, and a compliance function that can navigate in a quantitative space.”
He went on, “It’s not just about investing in AI centers of excellence. Institutions need to reshape underlying frameworks, including data governance, model management, and compliance functions.”
The webinar illuminated the immense opportunities AI presents for transforming financial crime prevention in Asia. By strategically implementing AI, financial institutions can enhance their ability to detect and mitigate risks, strengthening their defenses against financial crime. To realize this vision, banks, insurance companies, and other financial organizations must invest in understanding AI’s full potential and integrate its capabilities across their operations.
Unlock the untapped potential of AI in financial crime prevention
As financial institutions explore the untapped potential of AI in financial crime prevention, it’s crucial to choose partners who understand the complexities of the industry and can provide strategic insights and support. SymphonyAI is at the forefront of offering AI-led financial crime prevention SaaS software that uses AI’s full potential, ensuring institutions stay ahead of the curve as bad actors’ practices and regulations evolve. This includes AML software, payment fraud solutions, and KYC/CDD tools.
The SymphonyAI research report features insights from 100 financial crime and compliance experts across Asia Pacific who have shared where they are focusing their AI efforts, the current state of maturity, and the challenges of AI deployment. You’ll also learn actionable strategies on how to overcome these challenges so you can transform your financial crime and compliance program.
