A-01 · Subject
Making trusted data useful in consequential decisions.
I help enterprises turn data into a trusted part of how decisions are made.
Specification
| Ref. | Measure | Value | Note |
|---|---|---|---|
| S-01 | Trusted source of truth | 1 | Replacing 37 conflicting reports |
| S-02 | Value from analytics | ₹410 Cr | Verified by finance, year three |
| S-03 | Models governed | 220 | Under one responsible-AI framework |
| S-04 | Time to decision data | 9 days → 4 hrs | For the executive committee |
Modules of expertise
Career elevation
Stage 04 · 2020 — Present
Aldermoor Group
Leading enterprise data strategy, governance and analytics adoption.
Stage 03 · 2016 — 2020
Fairhaven Holdings
Built data and analytics capability around priority business uses.
Stage 02 · 2013 — 2018
Westmoor Housing Finance
Built the credit analytics capability that reduced losses while widening access to first-time borrowers.
Stage 01 · 2008 — 2013
Lumen Payments
Designed fraud models at national scale, and learned that a model is only as good as the decision it improves.
Detail drawings
01Detail
Business functions were maintaining different versions of a critical performance measure. I worked with the accountable owners to define the measure, document its source and agree how exceptions would be handled. The programme treated data ownership as an operating responsibility and gave users a visible path for resolving quality issues.
02Detail
An analytics initiative had produced technically sound outputs that were not part of the management routine. We redesigned the work around a specific decision, involved the decision owners in evaluation and made limitations visible in the way findings were presented. Adoption became part of the delivery definition.
03Detail
Teams wanted to move AI experiments into business use without a consistent review process. I convened product, data, risk and operating leaders to agree evaluation criteria, human accountability and monitoring responsibilities. The approach allowed use cases to be assessed on their actual purpose and exposure rather than on enthusiasm for the technology.
Board record
Independent Director
Risk · Data & AI Ethics (Chair)
2023 — Present
Advisory Board Member
Standards Council
2020 — Present
Peer review
Made our data trustworthy enough to bet decisions on — and honest about where it was not.
The clearest voice on responsible AI in our boardroom.
Working notes
Naming an owner is only useful if that person can make the decisions needed to keep information fit for purpose.
Read the essayAn analytical output can be accurate and still fail to influence the work it was intended to support.
Read the essayAn AI use case needs to be assessed in the context of the decision or task it supports.
Read the essayAn invitation
For board, advisory and leadership conversations where data strategy matters.
office@gracehalim.example