Risk Classification and Loan Modeling

Industry Customer Scenario

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About this Accelerator

Use predictive analytics and machine learning to estimate the optimal loan size that the SBA will approve for a given applicant which enables lending partners to process loan applications and make data-driven lending decisions quickly. Automate process for accelerating the loan approval and rejection process and providing right-size loans to increase the likelihood of complete and timely payments to ensure compliance with SBA guidelines.

Challenges

  • Backlogs and errors in loan application due to reliance on labor-intensive, manual, low-tech processing.
  • High volumes of loan applications lead to bottlenecks and delays.
  • Delays can cause applicants to lose critical business opportunities and impact their risk profiles.
  • Inability to regularly run and re-run risk classification limits the accuracy of assessments.
  • Lack of efficient, precise loan modeling makes it difficult to determine exactly what the SBA will approve.

Benefits

  • Automate processes to ensure compliance with SBA guidelines.
  • Accelerate the loan approval and rejection process.
  • Predict right-size loans to increase the likelihood of complete and timely payments.
  • Improve customer experience and increase customer retention.
  • Support small businesses and the chain of industries dependent on them.

Relevant Personas

Financial

Primary Industry

Financial Services

Products

Azure Data Lake Storage

Synapse Analytics

Technical Value Assets

Business Value Assets

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