AI Horizons: Strategy and Skills
A running briefing on how artificial intelligence is reshaping banking, insurance and asset management — and what each shift means for hiring.
Singapore and Hong Kong have taken the lead in translating AI adoption into supervised, industry-wide practice — publishing toolkits, running live sandboxes, and pooling data across institutions rather than leaving adoption to individual firms. The sequence below moves from the broadest regional policy picture to the specific programmes now shaping how banks, insurers and asset managers in our markets are putting AI to work.
- 1Regional PolicyDecember 2025OECD
Artificial Intelligence in Asia's Financial Sector: A Review of Country Policies
The essential starting point — a country-by-country review of how financial regulators across Asia are approaching AI policy. Useful as the frame for everything that follows: it shows how Singapore and Hong Kong's specific programmes sit within a wider regional pattern.
Excalibur's ViewRead the report →Best read as regional context rather than a specific hiring signal — useful background for any employer or hiring leader trying to understand why AI governance requirements are tightening across the region.
- 2SingaporeCross-Sector ToolkitMarch 2026Monetary Authority of Singapore
Project MindForge: AI Risk Management Toolkit for the Financial Sector
Built collaboratively by a consortium of 24 banks, insurers and capital markets firms, this toolkit covers traditional AI, generative AI and emerging agentic AI. It includes an operationalisation handbook and a case-study supplement documenting real institutional experience — the clearest evidence yet of industry-wide, rather than single-firm, AI maturity in Singapore.
Excalibur's ViewRead the release →A 24-institution consortium building shared AI risk infrastructure points to "AI governance" emerging as its own hiring category, distinct from traditional model risk. We'd expect the strongest candidates to combine model risk or compliance grounding with genuine hands-on exposure to generative or agentic AI, rather than one or the other alone.
- 3SingaporeFinancial CrimeMay 2026Monetary Authority of Singapore
MAS Collaborates with the Banking Industry to Harness AI Against Financial Crime
A live proof-of-value pooling transaction data from five banks, GovTech and the Singapore Police Force to train shared AI/ML models for pre-emptive scam detection. A concrete example of AI adoption moving from single-institution pilots to coordinated, industry-wide infrastructure.
Excalibur's ViewRead the release →Pooling data and models across five banks for scam detection suggests the AML and fraud function is absorbing data science and ML capability directly, rather than routing through a separate technology team. We'd expect hybrid AML-plus-ML profiles to become harder to find, and more valuable, as this kind of collaboration scales across the market.
- 4SingaporeStrategyJuly 2026Monetary Authority of Singapore
Singapore to Set Up a National Centre to Accelerate AI Adoption in Finance
The newly announced Future of Finance Institute will pool AI and tokenisation capabilities, implementation toolkits and sandbox infrastructure — MAS's stated ambition is for Singapore to become "a global launchpad for AI in financial services." Directly relevant to where demand for AI-fluent talent in the market is heading.
Excalibur's ViewRead the article →Worth watching over the next 12–18 months — for employers, an early signal to start building AI capability before competition for talent intensifies; for candidates, a sign that Singapore may draw AI opportunities from across the region and beyond.
- 5Hong KongSandbox ResultsOctober 2025Hong Kong Monetary Authority
GenA.I. Sandbox: Phase One Results Across 10 Banks
The most concrete numbers in the region. Suspicious transaction report preparation time fell by 30–80%, document processing dropped from a full day to around five minutes, and risk assessment report generation time was cut by 60%. The second cohort now tests 27 use cases across 20 banks and 14 technology partners.
Excalibur's ViewRead the release →With 20 banks now running live use cases, the constraint shifts from experimentation to people who can operationalise AI inside regulated processes reliably. That's a different profile from a data scientist — closer to a business or risk analyst fluent in both LLM behaviour and control frameworks.
- 6Hong KongAdoption & TalentApril 2025Hong Kong Institute for Monetary and Financial Research
Financial Services in the Era of Generative AI: Facilitating Responsible Adoption
A survey of banks, insurers and wealth and asset managers on the current state of GenAI adoption, its expected trajectory in Hong Kong, and — notably — the talent development strategies firms are pursuing alongside it. A follow-up survey found 75% of firms had implemented or were piloting at least one use case, rising to 83% among large firms.
Excalibur's ViewRead the release →The gap between stated upskilling ambition and actual investment is worth watching — for employers, it's a competitive opening if they close that gap faster than peers; for candidates, a sign that real AI upskilling may still be scarce enough to stand out.
Sources are linked directly to the originating regulator or institution. Excalibur Executive Search is not affiliated with the OECD, the Monetary Authority of Singapore or the Hong Kong Monetary Authority; these are shared as independent reading for clients and candidates.