Data & AI Platform

EDB Grant Strategy & Business Case

Executive Summary

MSIG Asia wants to build an in-house Data & AI capability — a dedicated team that owns the data platform, builds AI solutions, and upskills the organisation. Singapore's Economic Development Board (EDB) offers two grant programmes that can co-fund this investment significantly.

The Need
A central Data & AI team across 14 markets — modern data platform, custom AI agents for insurance operations, and an internal academy to build AI capability at every level.
The Opportunity
Two EDB grant programmes — RIS(C) for the R&D team and TG(C) for the AI Academy — can return over S$1M in salary and equipment reimbursements over 3 years.
Maximise Internal Talent
Use the AI Academy to convert existing data analysts and business analysts into AI engineers and AI analysts. Minimise external hiring, keep the bottom line low — and internal converts still count as new R&D headcount for the grant.
Sequence Matters
Both grants must be approved before the project starts. The RIS(C) application must precede any hiring — otherwise new hires don't qualify as additional headcount.

In-House AI Capability — Three Pillars

Build a central Data & AI Platform organisation at MSIG Asia. Three pillars, one team, compounding capability that stays in-house.

Modern Data Platform
Unified data layer connecting SAP, CoverGo, and Graphene across 14 markets with an API backbone
AI & Automation Platform
Custom AI agents for claims, underwriting, operations — built on MSIG's own data, owned by MSIG
MSIG AI Academy
Executive AI literacy + analyst enablement across functions — embedded AI capability at every level

EDB Grant Programmes

Two Singapore EDB grant schemes map directly to the three-pillar proposal. Both are reimbursement-based — MSIG claims back costs after incurring them. No upfront commitment to EDB.

RIS(C) — Research & Innovation
Funds the R&D team build. Maps to Pillar 1 (Data Platform) and Pillar 2 (AI & Automation Platform).
TG(C) — Training Grant
Funds the MSIG AI Academy. Maps to Pillar 3. Reimburses employee salary costs during training.

RIS(C) — What Qualifies

RIS(C) supports new R&D and innovation projects in Singapore. The key requirement: the project must develop new or significantly improved products and processes — not adopt existing technologies.

Why MSIG Qualifies
No commercial product exists for multi-system AI agent orchestration across heterogeneous insurance core platforms operating across 14 regulatory jurisdictions
What Counts
Local manpower (60% reimbursed), foreign manpower (30%), cloud & equipment (30%). Additional R&D headcount includes internal transfers.
Two Packages
Standard: S$500K grant (5 R&D hires). Enhanced: S$1M grant (8 R&D hires). Both over a 3-year qualifying period.
R&D Framing
"Development of a Multi-System Agentic AI Platform for Cross-Market Insurance Operations" — genuinely novel, defensible

Good to know: RIS(C) requires "additional R&D headcount" — but these can be existing MSIG employees transferred into the Data & AI function. Internal converts count as new R&D headcount for the grant.

TG(C) — Academy as Training Programme

The MSIG AI Academy maps directly to TG(C). EDB reimburses MSIG for employee salary costs during training — both formal sessions and on-the-job application count.

Who Gets Trained
The "dotted-line AI analysts" — staff in finance, claims, underwriting, and operations who learn to use the AI platform. Must be SG citizens/PRs.
What Counts as Training
Structured AI sessions, hands-on workshops, and on-the-job time spent building and using AI solutions for their department.
Grant Cap
Up to S$2,500 per trainee per month. Maximum S$300,000 per application over a 3-year qualifying period.
Zero Extra Cost
The Academy is built in-house as part of the platform organisation. No external training vendor fees — the grant is pure reimbursement.

Business Case

Team Scenario

Select the target team size. This drives both the team cost and the RIS(C) grant package.

Team Composition & Annual Cost

RIS(C) Reimbursement (3-Year Qualifying Period)

TG(C) Reimbursement — AI Academy

Each cohort trains 5 people over 6 months. Select training intensity and total people trained over the 3-year qualifying period.

3-Year Business Case

Select benefit scenario. Estimates to be validated with Raj based on actual MSIG spending and operational data.

Recommendation

Target: 8 R&D Headcount
Qualifies for the S$1M enhanced RIS(C) package. Prioritise internal transfers — same bottom line for MSIG, but transfers count as new R&D headcount for the grant.
Max Out Training Grant
Train everyone through the in-house AI Academy. No external vendor costs — the Academy is part of the platform organisation. The grant is pure salary reimbursement.
S$1M+ Co-Investment
Combined RIS(C) + TG(C) potential exceeds S$1M over 3 years. EDB co-invests because this is exactly the capability build Singapore wants to see.
Apply Before You Start
Both grants require application before the project begins. The sequence matters — applying first costs nothing and unlocks significant co-funding.

Next Steps

1
Confirm interest in pursuing EDB grants

Green light to explore both RIS(C) and TG(C). No commitment at this stage.

2
Designate internal contact for applications

HR or Finance lead to own the grant application process with EDB.

3
Submit RIS(C) application

R&D project description, team plan, and projections. Application support included.

!
RIS(C) must be approved before hiring the Head of Data & AI

If the Head of Data & AI is hired before RIS(C) approval, the role does not count as "new R&D headcount" and is excluded from the grant. The approval must come first.

4
Submit TG(C) application

Training Plan and trainee list for the AI Academy. Must be submitted before training starts.

5
Begin hiring and launch Academy

Post-approval. Team build-up and first Academy cohort kick off in parallel.