Advanced Techniques: Differential Privacy and Synthetic Data
Differential privacy adds carefully calibrated noise to results, making it difficult to infer whether any single person’s data contributed. Use privacy budgets to manage cumulative risk across many queries. In fintech, this allows aggregate trend reporting and performance metrics without disclosing patterns tied to specific customers or small groups.
Advanced Techniques: Differential Privacy and Synthetic Data
High-fidelity synthetic datasets enable testing, demos, and experimentation without real customer records. Generate statistically similar distributions and edge cases while preventing re-identification. Include guardrails to avoid reproducing rare, sensitive combinations. Monitor drift between synthetic and production patterns so your tests remain reliable as business conditions evolve.
