Data in fintech
fintech data: transaction and behavioral data, alternative-data underwriting, fraud and KYC/AML, and data governance.
This block builds sector-specific data fluency for fintech professionals. You will examine how core data concepts, such as data models, pipelines and quality frameworks, apply specifically to financial technology products. You will map the data landscape unique to fintech: transaction feeds, credit bureau files, KYC documents, open banking APIs and behavioral scoring data. You will learn the metrics used to judge data quality, freshness and reliability in payments, lending and banking contexts, strictly from a data lens, not financial ratios. Finally, you will cover the privacy and governance rules, including GDPR, PSD2, CCPA and PCI DSS, and the practical audits fintech data teams run to remain compliant, defensible and audit-ready.
Ce que vous allez maîtriser
- Identify and evaluate the core fintech data sources, including transaction, KYC, credit bureau and open banking data
- Apply data-quality metrics (completeness, latency, accuracy, lineage) to assess fintech datasets and pipelines
- Design a basic data governance and access-control framework compliant with GDPR, PSD2 and PCI DSS
- Conduct a practical data audit to detect gaps, bias, drift or compliance risks in a fintech dataset