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CONSULTING SERVICES
Turn complex data into actionable insight.
Analytics, Econometrics & Data Science
Large‑scale analysis, econometrics, stress analytics, dashboards, decision memos.
OVERVIEW
SEDA's Analytics, Econometrics & Data Science practice provides rigorous quantitative analysis in support of business decisions, regulatory submissions, litigation matters, and strategic planning.
Our team includes econometricians, data scientists, and quantitative analysts with experience in financial markets research, regulatory analytics, and large-scale data processing — capable of handling complex, high-volume financial datasets with statistical rigor.
We deliver actionable insights through analytical reports, decision memos, dashboards, and expert-level presentations suited to senior audiences.
WHAT WE DELIVER
Large-scale financial data analysis
Econometric modeling and causal inference
Stress testing and scenario analytics
Statistical validation and backtesting
Dashboard design and implementation
Decision memos and analytical presentations
Typical deliverables
What to expect from an engagement.
01
Analytical Report
A rigorous, documented analysis of the data, methodology, findings, and conclusions — structured for regulatory or litigation use if required.
02
Econometric Model & Documentation
A fully documented econometric model, including specification, estimation, validation, and sensitivity analysis.
03
04
Executive Dashboard
A data visualization and monitoring dashboard translating complex analytical outputs into clear, decision-ready management information.
Stress Testing Framework
Design and implementation of scenario and stress analytics, including adverse case definitions, sensitivity tables, and management reporting.
ANALYTICAL CAPABILITIES
Analysis built to stand up in any room.
Whether the audience is a board, a regulator, or a court, SEDA's analytical work is designed to be challenged and to hold. Our methodology documentation is built into every engagement — not added as an afterthought.
Time-series and panel data econometrics
Causal inference and difference-in-differences
Machine learning and predictive modeling
Large-scale trade data analysis
Python, R, MATLAB, and SQL workflows
Regulatory stress testing (DFAST, CCAR, ICAAP)