Automated Business Plan Underwriting via Statistical Deviation
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Solution Overview
Problem
Financial institutions face high underwriting costs when approving small business loans, particularly for loans under $500,000, as analyzing business plans is resource-intensive and often unprofitable, leading to qualified small businesses being turned down for financing.
Innovation Solution
A method and system that utilize business records of existing entities to generate a model correlating entity profiles, incomes, and expenses, allowing for the evaluation of proposed business plans by calculating statistical deviations in projected incomes and expenses, thereby streamlining the loan underwriting process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis of business plans is used for underwriting small business loans, then underwriting accuracy is improved, but underwriting cost increases
Solution Approach 1:
The system performs preliminary analysis by pre-processing business records of existing businesses to generate a model that correlates entity profiles, incomes, and expenses before actual underwriting. This preliminary modeling enables automated comparison and statistical deviation calculation for new business plans, reducing the need for manual analysis while maintaining accuracy.
Solution Approach 2:
The system creates a computational model that copies and generalizes patterns from historical business records. This model serves as a surrogate for manual underwriting analysis, enabling automated evaluation of projected incomes and expenses by comparing them against the learned patterns from existing successful businesses.
2Loss of energy
If automated underwriting is implemented, then underwriting cost is reduced, but underwriting accuracy deteriorates
Solution Approach 1:
The system introduces a statistical deviation metric as an intermediary between automated data processing and underwriting decisions. This intermediary quantifies how much projected incomes and expenses deviate from historical patterns, providing an objective measure that maintains accuracy while enabling automation. The deviation metric serves as a bridge between raw data and underwriting judgment.
3Reliability
If comprehensive business plan analysis is performed, then loan approval quality is improved, but processing time increases
Solution Approach 1:
The system extracts only the essential elements needed for underwriting evaluation from comprehensive business plans - specifically projected incomes and expenses. By focusing on these critical financial metrics and comparing them against historical patterns, the system maintains approval quality while significantly reducing processing time by eliminating analysis of non-essential plan components.
4Reliability
If manual evaluation of business plans is used, then decision quality is improved, but productivity deteriorates
Solution Approach 1:
The system enables self-service underwriting by allowing business plans to be automatically evaluated against the pre-trained model. The system independently calculates statistical deviations and generates underwriting recommendations without requiring manual reviewer intervention for each application, thereby maintaining decision quality through consistent application of the model while dramatically increasing approval throughput.
Data Source
AI summary
A method for underwriting a business loan. The method includes obtaining a collection of business records of existing business entities, where a business record includes a business entity profile, recorded incomes, and recorded expenses, generating, based on the business records, a model that correlates the business entity profile, the recorded incomes, and the recorded expenses, obtaining a business plan of a proposed business entity, where the business plan includes a proposed business entity profile, projected incomes, and projected expenses, and generating, by using at least the proposed business entity profile as an input to the model, a statistical measure of deviation of the projected incomes and the projected expenses with respect to the existing business entities.