Virtual Expert Panel

Tackling financial crimes in ASEAN with Innovation technology and data

ASEAN Tackling Finance Crime - GBG

Our recent survey with found that financial institutions (FIs) in the ASEAN region ranked Identity fraud/false identification (67.9%) and Trade-based money laundering (50%) as the top two financial crime typologies. This is also the reason why the effective enforcement of AML regulations has long been a priority for governments. In the next few years, several more countries in Asia are likely to upgrade their AML regulations, and the enforcement of those laws.

In this webinar, we’ve uncovered whether ASEAN FIs are combating financial crime effectively, particularly within the Anti-Money Laundering space. Having up to date systems is paramount for financial institutions to predict and identify potential financial crime activities.

Key insights from the experts:

  • The current state of play in the ASEAN region
  • Challenges in fighting financial crime with the increasingly rigorous regulatory requirements and growing levels of data
  • Leveraging scalable technology innovation (AI/machine learning & data) to add more context in decision-making whilst increasing its business efficiency
  • Reducing the timeline of RegTech implementation to fight financial crime more effectively
  • FIs are deploying a combination of different tools (AI, machine learning, advanced analytics, link analysis, data cleansing) to automate the decision-making process in mitigating sanctions risks
  • FIs that implemented AI/machine learning technology are more likely to gain traction from overseas bank partnerships

Expert panellists

Josephine Woo

Chief Risk Officer | RHB

Nick Vitchev

Research Specialist, Financial Crime and Fraud | Chartis

Francis Choi

Head of AML | Ping An OneConnect Bank (HK) Ltd

Dev Dhiman

Managing Director, Asia Pacific | GBG


47% of FIs planned to enhance their KYC/ customer due diligence and transaction monitoring systems

In addition to minimising regulatory fines, 26% of FIs are looking to enhance their AML solution because of the inability of their current rules-based system to detect anomalies and unusual patterns

Machine learning and AML transaction monitoring are the top two solutions that FIs are exploring this year

Watch now

Josephine Woo, Chief Risk Officer, RHB; Francis Choi, Head of AML, Ping An OneConnect Bank; Nick Vitchev, Research Specialist, Financial Crime and Fraud, Chartis and Dev Dhiman, Managing Director APAC, GBG discussed how banks leverage scalable technology and up to date system to innovate and mitigate potential financial crime activities while increasing their business efficiency.