Rising economic uncertainty and market volatility, fuelled by global macroeconomic events such as shifting tariffs, are opening the door to greater financial crime activity.
Given the large impact on China, many companies are relocating operations to Southeast Asia to get around trade barriers where they are fast emerging as key hubs for reconfigured global supply chains.
Napier AI’s Greg Watson recently travelled to Southeast Asia, and particularly, Malaysia, this week to meet with customers and prospects. He outlined that it’s clear that the region’s growth presents strong economic opportunities. The strong economic growth is why Napier AI have its technology hub in the thriving Kuala Lumpur, said Watson.
However, it is important to be cognisant that any period of economic change also heightens the risk of financial crime. As seen recently, through the COVID-19 pandemic, in times of rapid change and business transformation, compliance gaps widen.
In many cases, illicit activity is embedded in otherwise legitimate-looking commercial flows making it difficult to detect without proactive, real-time oversight.
How does this financial crime look in practice?
In many cases, criminal networks can exploit newly formed business entities or even set up companies to move illicit capital under the radar.
It could also be in the shape of trade-based money laundering, which often involves complex typologies, including suspicious transactions exploiting gaps in documentation, using phantom shipments, and routing funds through opaque networks of intermediaries and shell companies.
Such evasion tactics are often to disguise the ultimate origins and beneficial ownership for sanctions evasion, making it harder for compliance teams to track individuals and transactions with traditional rule-based AML systems.
Rethinking compliance strategies amid tariff fluctuation
There needs to be increased scrutiny from institutions that are enabling businesses with financial services. Many of whom have passed rigorous due diligence checks at the time of onboarding. These institutions need to be doing ongoing monitoring for suspicious activity, using AI to detect anomalies. This includes:
Multi-layered screening that covers customers, suppliers, and partners across multiple jurisdictions and languages. This will help senior management have oversight while each of the business units meet its regulatory frameworks and reporting guidelinesArtificial intelligence powered dynamic risk assessments that evolve as new intelligence, transactions, or relationships emerge. Real-time alerting when a customer’s behaviour or risk profile changes, with insights from explainable AI models so that analysts can finetune their rule configurations even further.
Why MAS’s recent crackdown comes at the right time
In times of market volatility, it is often regulators who pave the way towards strengthening the fight against financial crime. Leading the charge in Singapore, the Monetary Authority (MAS) recently proposed tougher AML/CFT requirements, including faster STR filing timelines, expanded definitions of risk, and clearer expectations for screening, source of wealth verification, and escalation.
These changes reflect an important truth: compliance cannot be static while financial crime is adaptive.
The MAS changes send a strong signal not just to institutions in Singapore, but to the entire Southeast Asia region to modernise compliance processes. In a climate of economic uncertainty, regulatory fragmentation, and rising cross-border flows, financial institutions need to move beyond box-ticking at onboarding and invest in systems that provide continuous, intelligent monitoring with artificial intelligence.
The inaugural Napier AI / AML Index report found that $138 billion USD could be saved in financial institutions’ compliance budgets globally each year, by implementing AI in financial crime compliance solutions. Particularly in Malaysia, where the country lost 5.44% of its gross domestic product (GDP) to money laundering, AI-powered compliance strategies can help financial institutions save up to $1.94 billion.
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