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Government Agency Leverages Analytics to Reduce Loan Portfolio Risk

Government Agency Leverages Analytics to Reduce Loan Portfolio Risk

This federal agency nurtures the growth and viability of businesses across the nation – in part by helping them access critical funding from the agency’s loan portfolio valued over $100 billion. To ensure operational efficiency and optimize taxpayer value, it must analyze, assess and monitor over 4,200 participating lenders and partners. The success of the oversight process depends on the agency’s implementation of proactive evaluative systems.

The Challenge:

Reactive approach to monitoring loans and lenders

Lacking a holistic view of the loans and lender relationships under its management, this government agency often relied on reactive decision making. Further, low-depth program oversight information failed to provide early warning indicators – leaving the agency susceptible to unforeseen challenges.

Struggling to meet its mission successfully, and shift to proactive decision making, agency leaders were determined to undertake a system modernization in order to:

  • Identify the riskiest lenders in its portfolio
  • Conduct efficient risk-based portfolio reviews
  • Monitor lender delinquency and viability
  • Score performance attributes and utilize the scores in predictive models

The Solution:

Predictive indicators & enriched data optimize operations

Focusing on the agency’s focal needs of risk management and portfolio monitoring, Dun & Bradstreet conceptualized, created, and implemented a robust loan and lender monitoring system. This compressive system leveraged scores, industry best practices, and advanced analytic models to enhance the organization’s ability to analyze and trend lender and portfolio risk.

In addition to the implementation of batch data cleansing and normalization, Dun & Bradstreet enriched the agency’s data with key attributes and predictive indicators, thereby enabling the use of advanced financial models.

The enhanced data, integrated with third-party sources, was successfully extracted into the agency’s data warehouse. This standardized process enabled accurate data transformation for future use within analytical and reporting environments.

The Results and ROI:

Optimized risk management & portfolio monitoring systems strengthen program integrity

By partnering with Dun & Bradstreet, this agency established a best practice loan and lender monitoring system on par with those used in the commercial lending industry. The use of modern, intuitive and comprehensive data analytics allows the agency to effectively manage risk, monitor performance, and select high-risk lenders for risk-based reviews. These strategic efforts strengthened program integrity, ensured transparency and connectivity with private sector banking institutions, and allowed agency data to be better leveraged by lending partners.

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