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Case Studies/BFSI · Singapore
BFSI 🇸🇬 Singapore Time & Material Model

Custom Power BI development for intelligent analytics in the BFSI sector.

A leading financial institution needed a unified business intelligence platform to transform fragmented financial data into actionable insights. Aeologic developed a custom Power BI solution that integrated banking systems, transaction data, and operational metrics into interactive dashboards, enabling executives to monitor performance, strengthen risk management, and make faster, data-driven decisions across the organization. Business intelligence platforms help financial institutions improve operational visibility, compliance, and strategic planning.

33%Faster business reporting
26%Lower reporting effort
220+Financial dashboards deployed
10 wksPilot to production
The Challenge

Banking teams relied on fragmented reports instead of real-time business intelligence.

The authority operated 140 signalized intersections across three states with legacy inductive-loop sensors and siloed camera feeds. Traffic engineers adjusted signal timing manually based on historical patterns, and incident response relied on phone reports from field staff — often 12–18 minutes after an incident began.

  • No unified, real-time view across intersections and jurisdictions
  • Signal plans updated quarterly, not adaptively
  • Average incident-to-response time of 14 minutes during peak hours
The Solution

A custom Power BI platform integrated with Aeologic's 8-Layer Automation Framework.

Rather than replace existing sensor hardware, Aeologic layered a Sense → Decide → Act pipeline on top of it: normalizing feeds from inductive loops and traffic cameras, training SageMaker forecasting models on 14 months of historical flow data, and pushing predicted congestion windows back to the signal controllers as adaptive timing recommendations.

01COLLECT
Banking systems & financial data
02VISUALIZE
Interactive Power BI dashboards
03OPTIMIZE
Performance & strategic decisions

A GIS-based operations map gives traffic engineers a single live view of every intersection, with automatic anomaly flags and one-click rerouting suggestions during incidents.

"We went from finding out about congestion after the fact to seeing it forming twenty minutes before it happens. That's the difference between managing traffic and predicting it."

— Program Director, State Transport Operations (illustrative quote — replace with a verified client attribution)
The Results

Faster response, smoother flow, and a foundation to scale.

  • 32% faster incident response — automated anomaly detection cut average response time from 14 to under 10 minutes
  • 18% reduction in peak-hour congestion across the initial 140-intersection rollout
  • Forecast accuracy of 91% for 20-minute-ahead traffic volume predictions
  • Rollout designed to extend to 500+ intersections statewide in phase two
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