Zero-basing our finance foundations

Airwallex describes how rapid growth and the complexity of global payments created fragmented financial data, with millions of micro-transactions, differing product schemas, and inconsistent definitions across markets. Following a migration from BigQuery to Databricks, the company made Finance responsible for defining decision-driven use cases and built its reporting model around the reconciled Airwallex ledger. Finance teams across tax, treasury, controllership, and FP&A collaborated on a shared data dictionary, standardized nomenclature and table structures, and expanded ERP account tagging to create a governed, business-wide source of truth. This foundation provides AI tools with the context needed to interpret financial fields correctly, enabling faster tasks such as attributing regional operating-cost changes through agents used in platforms including Cursor, Claude, and Hex. The company argues that the main obstacle to using AI in finance is often data readiness rather than data sensitivity, while noting that maintaining a unified data model remains an ongoing challenge as new business data emerges.

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