One workflow, three markets: planning an AI rollout across Singapore, Malaysia and Indonesia
A practical method for adapting a finance workflow across countries, with a rollout worksheet for data, systems, people and approvals.
Insights
Evidence and practical judgement for the decisions institutions face when operating with AI.
21 items
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Build, buy, integrate or stop: an AI investment memo for 2027
A decision memo for approving one AI workflow, comparing existing software, specialist products, custom delivery and the option to stop.
Who controls the AI stack?
How to identify material AI dependencies, compare deployment choices and test whether a supplier can be replaced without losing control of the workflow.
From experimentation to institution: what deployment requires
How to turn AI experimentation into an owned, funded operating capability, with explicit acceptance, support and expansion decisions.
AI in Q1 2026: choosing a useful first investment
A business review of January–March 2026 AI developments, with a practical worksheet for selecting a measured trial in Singapore and ASEAN.
Tokenisation after the demo: the operating work still to do
How to map cash, securities, custody, records and exceptions before approving an institutional tokenisation project.
Who is accountable when an AI agent acts?
How institutions can allocate responsibility for an AI agent's authority, execution and recovery across business owners, deployers, suppliers and human reviewers.
The full cost of an automated workflow
Calculate review, integration and support costs, distinguish released capacity from cash savings, and test an automation business case.
Where should AI enter your finance operation?
A practical method for choosing a finance workflow worth testing, with a usable selection worksheet.
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