Voices from the field – Victoria Ting

Victoria Ting

Seita Law, Singapore

In your professional experience, what is the most significant anti‑corruption risk or enforcement challenge currently affecting your country or region?

Singapore has a low domestic corruption rate but, as an international financial centre, its greatest exposure is to foreign corruption and fraud proceeds being laundered through its system. In practice, the hardest enforcement challenge is a cross-border one: the predicate conduct and the controlling minds usually sit offshore, while only money mules, shell companies and enablers are onshore. This makes it difficult to attribute liability, prove the requisite knowledge and trace assets before they dissipate—particularly where funds move as digital assets through anonymous wallets or through opaque structures such as shell companies and family offices. Cyber-enabled fraud and scams remain the most prominent money-laundering threat and increasingly intersect with corruption typologies.

How is this issue being addressed in your organisation, sector or jurisdiction?

Singapore takes a whole-of-government, technology-forward approach. Post-rules machine-learning AML systems now detect suspicious behaviour without predefined rules, and MAS' COSMIC platform lets major banks share red-flag intelligence in real time under a defined materiality threshold—dismantling the 'silos create gap' problem. 'Digital to the core' governance centralises identity, income and document verification, shrinking the space for forged records and bribed certifiers. These are reinforced by public-private partnerships, strong prosecutorial and Corrupt Practices Investigation Bureau enforcement and legislative reform following the recent S$3bn laundering case. Blockchain-forensics capability is now embedded within investigations practice.

Based on your experience, what is one practical lesson, implementation challenge or effective approach that may be relevant to practitioners in other jurisdictions?

A recurring lesson is that legislation is only half the battle—effective, consistent deployment is the other half. On method, the most transferable approach is a hybrid investigative model that fuses blockchain forensic tracing and on-chain analytics with conventional legal tools (disclosure, asset-preservation orders and coordinated law-enforcement engagement), with forensic experts embedded from the outset so anonymous on-chain data becomes court-ready evidence at speed. Because blockchain data and fraud typologies are borderless, this ‘forensic-plus-legal’ template adapts readily to other jurisdictions building digital-asset recovery capability.

Looking ahead, what emerging development, regulatory shift or risk area are you monitoring most closely?

The convergence of sanctions, export-control and digital-asset enforcement—illustrated by matters involving diversion of advanced AI processors—where financial-crime, national-security and technology-supply-chain risks now overlap. I am also watching the ‘arms race’ in AI: criminals using deepfakes and synthetic identities to defeat KYC, against enforcement's growing reliance on AI analytics, which raises a pressing explainability question—can a model articulate why it flagged a transaction in a way that withstands court scrutiny? Alongside this, evolving cross-border asset-recovery and non-conviction-based confiscation frameworks remain a key area.