We collect and ingest credit data from a wide range of sources — structured or unstructured, internal or third-party — including Excel files, client systems, flat files, and more.
After ingestion, raw data is mapped to our internal credit data model. Field names, structures, and formats are aligned into a unified schema, enabling consistent processing across asset classes and portfolios.
All data runs through automated validation checks and standardization rules to eliminate inconsistencies, errors, and gaps — creating a high-confidence, normalized dataset.
Once validated, the data is loaded into our centralized credit data warehouse. Structured, connected, and compliant, it powers reporting, monitoring, and portfolio insights from a single source of truth.
We collect and ingest credit data from a wide range of sources — structured or unstructured, internal or third-party — including Excel files, client systems, flat files, and more.
After ingestion, raw data is mapped to our internal credit data model. Field names, structures, and formats are aligned into a unified schema, enabling consistent processing across asset classes and portfolios.
All data runs through automated validation checks and standardization rules to eliminate inconsistencies, errors, and gaps — creating a high-confidence, normalized dataset.
Once validated, the data is loaded into our centralized credit data warehouse. Structured, connected, and compliant, it powers reporting, monitoring, and portfolio insights from a single source of truth.
