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.
Three Packages
S$500K (5 R&D hires), S$1M (8 R&D hires), or S$1.5M (12 R&D hires). All 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 Incremental Cost
The Academy is built in-house by the platform team. No external training vendor fees — the grant is pure salary reimbursement for time already budgeted.

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. Directional estimates — to be validated with internal stakeholders 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 and await approval

R&D project description, team plan, and projections.

⚠ Any new R&D hire made before RIS(C) approval does not count as "additional headcount" and is excluded from the grant — 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.