How can wealth managers realistically double their assets under management without surging costs and doubling their workforce? That was the challenge posed by Abe Teo, Senior Presales Consultant at Wealth Dynamix, during his engaging presentation at the Hubbis Philippines Wealth Management Forum in Manila. Abe cut through the hype around artificial intelligence and laid out a practical roadmap for applying it to wealth management today. With a blend of insight, humour and firsthand experience, he explained why scalable tools, secure cloud strategies, quality data, and embedded compliance are critical for transforming operational efficiency and freeing up relationship managers to focus on what truly matters – serving clients.

The growth challenge and why AI now

Abe explained why AI must become a priority. Asia’s wealth management sector is undergoing fast growth, but with intense pressure on margins and rising client expectations. Institutions are being asked to double their AUM within three years – while keeping costs flat and maintaining compliance. “And 95% of that growth,” he said, “is expected to come from the relationship managers.”

The implication: each RM will need to manage twice as many clients while delivering more value and deeper engagement – something that simply isn’t possible without a radical shift in operational efficiency. “That’s where AI steps in – not as a gimmick, but as a way to automate burdens and make RMs exponentially more productive.”

To frame this transformation, Abe outlined what he called three certainties – fundamental truths that firms must accept and address to build a realistic AI roadmap.

Certainty one: You will need the cloud – but securely

Abe’s first certainty was the growing inevitability of cloud infrastructure. Regulatory barriers that once blocked adoption have faded. “I remember when banks told me, ‘We can’t move to the cloud; the regulator won’t allow it.’ Then MAS came out with a statement supporting cloud use – and everything changed.”

Still, major concerns remain around Client Identifying Data (CID), such as names, account numbers, and meeting notes. Firms fear the reputational damage of data breaches, which go beyond financial cost. “The average cost of a breach is about USD 4.5 million, but what keeps executives up at night is seeing their name in the headlines,” Abe remarked.

To solve this, Wealth Dynamix developed a smart tokenisation system. “We don’t just scramble the data – we scramble it intelligently,” he explained. For example, the name ‘Robert Paul’ might be transformed into an unrecognisable token, but the system still recognises that it’s a name. Dates still behave like dates. “The structure is preserved, so AI can still work with the data, but the actual CID never leaves your premises.”

Wealth Dynamix partnered with REGData to achieve this field-level tokenisation, giving firms control over which data fields are depersonalised. This architecture has already been reviewed and cleared by regulators like FINMA in Switzerland. And for most banks, it’s the only viable option. “Building a private cloud costs millions,” Abe said. “Only a handful of banks in Asia can do that. Everyone else needs a solution that works securely in the public cloud.”

Certainty two: You need wealth-specific, structured data

The second certainty was that no amount of AI can succeed without clean, structured, and domain-specific data. Abe was candid: “No bank has perfect data. Everyone struggles with quality, and in AI, the consequences of poor data are even worse.”

In traditional banking, data errors are manually corrected through reconciliation and operational checks. But AI systems don’t have human judgment. If bad data goes in, the risk of sending the wrong message to the wrong client – or misapplying compliance rules – rises dramatically.

To mitigate this, Abe stressed the need for a wealth-specific client data model – not something retrofitted from retail banking. “Wealth is complex. Multiple relationships, discretionary portfolios, layered mandates – it’s not something a generic data model can handle.”

Equally important are the operational processes that support that model. “You need controls in place that validate and clean data as it moves through the system. You can’t just load a spreadsheet and hope for the best,” he warned.

Certainty three: Compliance must be embedded

Compliance wasn’t presented as a bolt-on requirement – it was central to the entire strategy. “Compliance is the cost of doing business,” Abe said. “But it’s much cheaper when you’re ahead of it.”

He stressed that systems must be explainable, transparent, and auditable. When regulators ask for documentation, firms need to show what happened, why it happened, and prove that it was compliant. “You can’t tell the BSP or MAS, ‘We onboarded this client because the AI told us to.’ That’s not going to work.”

He also pointed out that many wealth firms operate in multiple jurisdictions, and AI systems must reflect the regulations of each – particularly when consolidating client data across markets.

And while fines are increasing, Abe argued that public exposure is now the greater risk. “If BSP or MAS names your firm in a press release, that’s far more damaging than a million-dollar fine. Regulators know this, and they’re using it.”

AI in action: From admin burden to relationship value

While AI has potential across every part of the client lifecycle – prospecting, onboarding, portfolio management, service, compliance – Abe believes the greatest initial payoff lies in eliminating administrative burden.

To bring this to life, he shared a personal story. After relocating from Hong Kong to Singapore, he and his wife met with an RM to open a joint bank account. “We spent two and a half hours sitting in a room filling out forms, validating paperwork, going through checklists,” he said. “That RM could have spent that time talking to other clients or explaining their products to us.”

This is where Abe envisions the future of the AI-augmented RM. Instead of two or three human assistants, the RM has 10 support agents – most of them digital. “They handle onboarding, documentation, KYC checks – everything that pulls time away from client engagement. This is how RMs go from 100 clients to 200 without breaking.”

At Wealth Dynamix, Abe explained, AI is being built into every layer of the platform: improving productivity, recommending next-best actions, streamlining onboarding, managing compliance, and enhancing the client experience – all while maintaining auditability.

The time to act is now

Abe closed with a direct challenge to the audience. “Everything I’ve talked about exists today. This isn’t five years away – it’s already here.”

He urged firms to begin their AI journey with clarity and care: adopt public cloud with proper safeguards, protect CID through tokenisation, build strong data and operational foundations, and embed compliance from the start. These elements form what he called REAL Intelligence – AI that is not only powerful but practical, scalable, secure, and explainable.

“You want to double your AUM? You want to grow the business without doubling your cost base? This is how you do it,” he said. “The question now is whether you’ll wait – or take the first step.”