Increasing Confidence in Model Performance Monitoring Through Automation

When an information services company discovered its model monitoring process was fraught with inefficiencies and roadblocks, they needed to redesign the platform to support automation, provide confidence in results, and facilitate widespread adoption throughout the organization.

Reducing Risk, Lowering Cost in Credit Card Authorization Decisions

Having already invested heavily to create a robust authorization platform, the bank was prepared to increase its stake in technology with an additional $1.2M. After investigating the problem, Flying Phase provided the bank with a roadmap to save between $500K and $1M in fraud costs and credit-risk approvals by rebuilding the back-up decision logic found within the third-party processor.

Leveraging Credit Expertise to Forecast Customer Hardship and Minimize Bank Charge-Offs

When the COVID-19 pandemic slowed the world’s economy to a crawl, many banks relied on models and forecasting to anticipate customer delinquencies and hardship and to efficiently staff its call centers.

Leveraging Data Infrastructure and Governance to Speed Model Development and Execution

Architected data platforms provide a foundation for automated modeling and forecasting to reduce cycle times and ensure well-managed data inputs.

Building an Efficient and Compliant CCAR Modeling System

Robust coding practices and streamlining the process and reduces delays and errors in model development and implementation for critical CCAR stress testing execution.

Productionizing Allowance: An Engineering Approach to an Analytical Process

Bringing production quality methods and controls to the quarterly impairment allowance created a fully compliant allowance process that reduced cycle time and resource needs by 80%.

Automation of Monitoring in Field Operations and Calculating Incentives

Automation delivers higher accuracy and speed in $60 million in annual incentive payouts to telecommunication field technicians.

Superior Loss Forecasting Through Machine Learning

Automated machine learning solutions drive better modeling results and a more controlled process in loss forecasting.