Analytics

Predictive Analytics Dashboard

FinSight Capital

Python Tableau PostgreSQL
3x faster decisions

The Challenge

FinSight Capital's portfolio managers were making risk decisions based on reports compiled hours after market close. By the time the data reached decision-makers, it was stale. They needed a real-time view with forward-looking risk signals.

3x
Faster Risk Decisions
Real-time
Data Latency (was: 8hrs)
92%
Forecast Accuracy (7-day)

The Solution

We built a streaming data pipeline that ingests market feeds, portfolio positions, and macroeconomic indicators in real time using Apache Kafka and PostgreSQL. A Python-based ML layer generates 24-hour and 7-day risk forecasts using gradient-boosted models calibrated on 5 years of historical data.

The executive dashboard — built in Tableau with custom extensions — surfaces alerts, scenario analysis tools, and drill-down views for individual positions. Role-based access ensures each stakeholder sees exactly what they need.

We also delivered an automated morning briefing emailed to the leadership team at 7am, summarising overnight market moves and portfolio exposure changes.

Python Apache Kafka PostgreSQL Tableau scikit-learn AWS EC2

Key Results

3x
Faster Risk Decisions
Real-time
Data Latency (was: 8hrs)
92%
Forecast Accuracy (7-day)
Project Screenshot 1
Project Screenshot 2
Project Screenshot 3

"We went from looking at yesterday's data to seeing tomorrow's risks. This dashboard changed how we manage the portfolio."

EK
Elena Kostopoulos
CIO, FinSight Capital

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