Industry
Higher Education
Annual Revenue
$1.1+ Billion
Location
Baltimore, Maryland, USA
How we unified siloed financial aid data, implemented intelligent risk detection, and enabled informed, compliant decision-making for a global education provider.
Business Problems/Requirement:
The client operated across 100+ global campuses with multiple disconnected financial systems, leading to inefficiencies and lack of visibility into aid distribution and risk. Key challenges included:
- Disparate Data Systems: Financial need data was spread across numerous isolated databases, limiting cross-campus visibility and traceability.
- Manual Risk Monitoring: Abnormal transaction reviews were performed manually, resulting in delays and human error.
- Inefficient Decision-Making: Leadership lacked unified insights to assess whether approved students and aid amounts were aligned with policy and compliance requirements.
- Operational Complexity: The absence of a centralized framework made it difficult to identify systemic inefficiencies or inconsistencies in financial need fulfilment.
Strategic Approach:
Data Integration & Risk Modelling
- Consolidated financial aid data from multiple campus systems into a centralized SQL Server environment..
- Developed analytical models using SAS to assess student eligibility, risk indicators, and transaction patterns.
Automation & Visualization
- Replaced manual transaction monitoring with automated anomaly detection logic and flagging rules.
- Built interactive Tableau dashboards enabling users to monitor key metrics, identify irregularities, and generate self-service reports in real time.
Operational Efficiency & Governance
- Established a unified data layer that allowed for end-to-end visibility into student approvals and financial aid disbursements.
- Created a governance framework to support periodic reviews and continuous process improvement.
Results:
- Enhanced Compliance: Automated detection of anomalies and potential noncompliance incidents, reducing audit risk.
- Risk Reduction: Improved accuracy and transparency of aid allocations, minimizing instances of over- or under-funding.
- Decision Support: Enabled real-time decision-making on student aid approvals through data-driven insights.