Data Architecture & Analytics

Most financial institutions do not have a data problem, they have a data access problem. The information exists, spread across a core or policy administration system, a servicing platform, a custodian file, several spreadsheets and a handful of vendor feeds, and nobody can assemble it fast enough to act on.

We design the architecture that fixes that: reliable ingestion, a clear model, and storage that serves both real-time operations and analytical workloads without one starving the other.

What we build

• Operational data stores for live origination, underwriting, servicing, trading and claims workflows
• Analytical warehouses and marts for portfolio, vintage, reserving, performance and regulatory reporting
• Pipelines and integration across core banking, policy admin, servicing, clearing, billing and third-party feeds
• Data quality, lineage and governance so a number can be traced to its source and defended

Why lineage is the requirement, not the nice-to-have

In this industry, being able to produce a number is not enough, you have to be able to show where it came from. Call reports, capital-provider reporting, client statements and regulatory filings all depend on that. We build lineage in from the start, and design pipelines that can be replayed with late or restated data and still produce the same answer.

Making it usable

Dashboards for people, APIs for systems. Underwriters, credit officers and executives read the position at a glance; the same governed data feeds downstream models and automation. The analytics layer and the AI layer draw on one version of the truth rather than diverging quietly.

Related work: Real-time underwriting data for an MGA