Kerper and Bowron files patent applications for contract-level warranty model
Kerper and Bowron LLC has filed a U.S. non-provisional patent application and a PCT application for its Kerper-Bowron Method, a financial model for service contracts and manufacturer warranties. The firm also submitted a new paper on extending the method to warranty accruals and collateralization, as it looks to expand software capacity for higher transaction volume.
Why it matters: - The Kerper-Bowron Method is aimed at replacing aggregate models with monthly, contract-level forecasts for losses, cancellations and value emergence. - The approach is designed to improve financial reporting, reserving, capital management and risk transfer in a market the company estimates at about $350 billion in annual service contract revenue and manufacturer warranty accruals. - The framework also targets downstream uses such as lending against projected equity in unearned premium reserves and risk-adjusted Customer Lifetime Value analytics.
What happened: - Kerper and Bowron LLC announced the filing of a U.S. non-provisional patent application and a corresponding international PCT application for the Kerper-Bowron Method. - The applications claim priority to a U.S. provisional patent application filed in August 2025. - Irish Trinity LLC holds the intellectual property. - Bradley Arant Boult Cummings LLP is serving as intellectual property counsel. - The firm also submitted a new paper for peer review that extends the method to manufacturer warranty accruals and collateralization applications. - The new paper builds on earlier work published in the journal Risks.
The details: - The method uses only point-of-sale data to generate individual contract- and warranty-level projections. - The company says the model replaces traditional aggregate earning curves and warranty accruals with precise monthly probabilistic forecasts. - The system is intended to support more accurate financial reporting, reserving and capital management. - The company estimates a global market of about $350 billion in annual service contract revenue and manufacturer warranty accruals, with substantially larger outstanding liabilities. - The company says the framework could support more precise accounting and revenue recognition under ASC 606, IFRS 17, ASC 460 and IAS 37. - The framework also enables structured risk transfer through special purpose vehicles. - The firm estimates about $20 billion in potential U.S. capacity for lending against projected equity in unearned premium reserves. - The model is also positioned for risk-adjusted Customer Lifetime Value analytics for short-duration contracts. - Kerper and Bowron is modernizing its software platform, which has been developed over the past 23 years, to support expected growth in transaction volume. - The company was founded in 2003 by John Kerper and Lee Bowron. - The firm is based in Birmingham, Alabama, and works as an actuarial consulting firm.
Between the lines: - The patent move signals an effort to protect the method as the company pushes into broader financial applications beyond its original service-contract work. - The peer-review submission suggests the firm is trying to validate the approach academically at the same time it seeks commercial protection. - The focus on collateralization and structured risk transfer points to a push toward capital markets and financing use cases, not just accounting support.
What's next: - The patent applications will proceed through the U.S. and international review process. - The submitted paper will go through peer review. - Kerper and Bowron plans to keep upgrading its software platform to handle higher transaction volume. - The company is also likely to keep expanding use cases for manufacturer warranty accruals and collateralization.
The bottom line: - Kerper and Bowron is pairing patent protection with new research to position its contract-level forecasting method as a tool for accounting, reserving and financing.
Disclaimer: This article was produced by AGP Wire with the assistance of artificial intelligence based on original source content and has been refined to improve clarity, structure, and readability. This content is provided on an “as is” basis. While care has been taken in its preparation, it may contain inaccuracies or omissions, and readers should consult the original source and independently verify key information where appropriate. This content is for informational purposes only and does not constitute legal, financial, investment, or other professional advice.
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