Automated Policy

Transition to Automated Underwriting

2OS built the first automated credit policy and custom risk model for a client, whose existing underwriting process was manual.

Our Approach

Data-Driven Decision-Making

2OS used existing bureau data to build a custom machine learning risk model and credit policy for a small business lender to decrease portfolio exposure and risk while maintaining profitability.

  • Improved Modeling

    The custom model developed by 2OS outperformed the industry benchmark. The credit policy was designed to meet the lender's target return while maintaining loss rate constraints.

  • Decreased Risk

    The model decreased charge off rates on the client's portfolio by 11%, compared to the industry benchmark, while maintaining target approval rates.

  • Credit Policy Construction

    2OS developed a credit policy for acquisitions and line assignments (approve/decline and receivable purchase size assignment) to achieve the client's objectives.

Our Results

  • Decreased Risk

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