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Treasury Data - Fundamentals

What It Is (General)

Treasury data encompasses the raw and processed financial data that treasury teams use to make decisions — bank statements, transaction records, balances, forecasts, and reports. The domain focuses on how this data is ingested, parsed, validated, enriched, and made trustworthy for downstream use.

Key concerns: format diversity (MT940, CAMT, BAI2, CSV), data freshness (real-time vs T+1 vs monthly), quality validation (schema checks, completeness), and harmonization (unified schema across sources).

What It Means for Our ICP

How Treasury Teams Think About It

Treasury teams rarely think about "data" as a domain — they think about whether they can trust the numbers in front of them. Data quality surfaces as: - "The numbers don't match" — reconciliation gaps between bank, ERP, and TMS - "This is stale" — looking at yesterday's data when making today's decisions - "I don't know what's missing" — no visibility into which accounts aren't reporting

On's Situation (Source: 2024-09-26) Amanda's Looker dashboard "is not real-time banking information. This is based on the statements that are registered in our ERP" — a data freshness and trust problem.

On's Situation (Source: 2024-10-24) Rodrigo: "Right now until the end of the month, we don't really know how much money we have" — data only becomes trustworthy after monthly reconciliation.

Typical Data Flows

  • Bank → (statements/feeds) → TMS/ERP → (reconciliation) → Trusted balance
  • Bank → (SFTP/API) → Data lake → (transformation) → Analytics-ready
  • Palm approach: Plug into wherever data already lands, then normalize and validate

Tools They Use Today

  • ERP (SAP, Oracle, PeopleSoft) — system of record, but not real-time
  • Limitation: Data accuracy depends on reconciliation cadence
  • TMS (Kyriba, etc.) — bank statement ingestion and matching
  • Limitation: Rejects data that doesn't match rules; daily wipe-and-replace patterns
  • BI tools (Looker, Power BI) — reporting layer
  • Limitation: Only as good as the underlying data

How They Talk About It

  • "Source of truth" — which system has the authoritative number
  • "Reconciliation" — the process that makes data trustworthy
  • "Data quality" — whether the numbers are correct and complete
  • "Freshness" — how current the data is
  • "Statements" — bank-provided transaction and balance files

Sources: view all