Finance
Privacy-safe risk modeling with synthetic ledger data
SDG 8SDG 9
The Challenge
A bank needed to evaluate ML risk pipelines without sharing sensitive transactions.
Our Approach
Modeled temporal dependencies with flow-based generative models; utility and privacy audits before release.
Key Outcomes
- Cut data-access approval time by 70%
- Maintained >95% downstream model fidelity
"Unamani unlocked collaboration without compromising compliance."
— Client testimonial
Project Details
Sector: Finance
Duration: 3-6 months
Team size: 3-5 people
SDG Impact
8SDG 8
9SDG 9
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