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Data & Platforms · 1 June 2026

Data is a strategic asset. Treat it like one.

Three principles we use to turn data from an accounting line item into the foundation of agentic AI in financial services.

By Raghavachari K Madhavan

Every bank says data is a strategic asset. Most balance sheets do not reflect it. The work of treating data as an asset is unglamorous, and that is exactly why it is the moat.

Principle one: govern at the source

Governance is not a downstream cleanup project. It is a contract written at the system of record. When ownership, lineage, and quality SLAs are defined where the data is born, every downstream agent inherits them for free.

Principle two: model the domain, not the report

If your data model reflects last year's regulatory report, you will rebuild it for next year's. Model the underlying business — client, mandate, position, instruction — and let reports be projections, not the source of truth.

Principle three: instrument everything

An agentic system without observability is a black box you cannot defend in a regulator meeting. Treat every read, every inference, every override as telemetry. The cost is small. The optionality is enormous.

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