Data in banking
the data that runs a bank: transactions, credit scoring, fraud and AML detection, risk models, and the strict governance, privacy and model-risk rules around them.
Banking runs on data: payment flows, credit bureau feeds, transaction logs, core banking systems, and regulatory reporting all generate structured and unstructured datasets that drive lending, risk, and compliance decisions. This block builds fluency in the data assets unique to banking, from KYC and transaction records to loan performance and market data feeds, and how their quality is measured and governed. You will learn the sector's core data infrastructure (core banking platforms, data warehouses, APIs), the metrics used to assess data quality and completeness, and the regulatory frameworks (BSA/AML, GDPR, BCBS 239) that shape how banks collect, store, and audit data. The goal is practical fluency, not general finance theory.
Ce que vous allez maîtriser
- Identify and map the core data sources banks rely on, from core banking systems to bureau and payments data
- Evaluate data quality using banking-specific metrics like completeness, lineage, and reconciliation accuracy
- Interpret regulatory requirements such as BCBS 239, KYC/AML, and GDPR as they apply to banking data governance
- Design and run practical data audits and checks to catch gaps, duplication, or compliance risks in banking datasets