Case Study
Published June 3, 2025
Advanced Analytics & Modeling Credit Decisioning Marketing
The Forrester Total Economic Impact™ (TEI) study, commissioned by Experian, explores the quantifiable and unquantified benefits of implementing the Experian Ascend Platform™. Based on interviews with global financial institutions, the report provides a comprehensive analysis of how the platform improves credit decisioning, reduces fraud, and delivers significant ROI.
Key insights include:
- 183% return on investment (ROI) and $13.3M in net present value (NPV) over three years
- 67% improvement in credit decisioning efficiency
- 20% reduction in default costs through better risk modeling
- 5% annual growth in application volume without added headcount
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Webinar
Model Risk Management for Regulatory Excellence
Financial institutions face numerous challenges when complying with model risk management regulations. Watch our Model Risk Management for Regulatory Excellence webinar and discover more from our experts Ankit Sinha and Masood Akhtar on how to:
- Automate documentation processes
- Reduce regulatory risk
- Speed up time-to-market
- Monitor for performance
Infographic
Harness the power of cashflow data
Smarter lending starts with greater visibility.
Read our one pager to discover:
- Why leveraging cashflow data is imperative in today's modern lending environment
- The types of financial behaviors cashflow data reveals
- The benefits of leveraging cashflow data
Report
The Evolving Challenge of Regulatory Compliance in Model Risk Management
As regulations continue to change, financial institutions must establish robust risk management practices and adopt technology that matches the scale and speed of compliance requirements.
Key priorities include:
- Strengthening model governance and transparency
- Enhancing explainability and responsible AI integration
- Reducing compliance burden through seamless automation
- Ensuring consistency across model validation and approval processes
Read our full report to learn more about the growing importance of monitoring, transparency, and automation in model risk management.