Bankruptcy risk factor identification system and bankruptcy risk factor identification method

The bankruptcy risk factor identification system uses a machine learning model to identify and simulate the impact of financial indicators on bankruptcy risk, addressing the limitations of conventional techniques by providing actionable insights for management.

JP7873043B1Active Publication Date: 2026-06-11SILOM PARTNERS TAX CORP
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Patent Information

Authority / Receiving Office
JP · JP
Patent Type
Patents
Current Assignee / Owner
SILOM PARTNERS TAX CORP
Filing Date
2026-01-20
Publication Date
2026-06-11

AI Technical Summary

⚠Technical Problem

Conventional bankruptcy prediction techniques focus on risk assessment from the perspective of stakeholders, failing to identify risk factors that affect a company's bankruptcy from the management's viewpoint and do not provide useful information for business improvement and avoidance.

⚗Method used

A bankruptcy risk factor identification system and method using a machine learning model generated from large amounts of accounting data, which includes an input unit, storage unit, indicator selection, model generation, bankruptcy determination, and simulation unit to identify and simulate the impact of financial indicators on bankruptcy risk.

🎯Benefits of technology

The system identifies financial indicators that constitute bankruptcy risk factors and their thresholds, allowing users to simulate the impact of changing these indicators, providing valuable insights for management decision-making.

✦ Generated by Eureka AI based on patent content.

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Abstract

This invention provides a system and method for identifying bankruptcy risk factors using a machine learning model generated from a large amount of accounting data. [Solution] The bankruptcy risk factor identification system 10 includes an input unit 13 that receives accounting data of a target company provided from an accounting system, a storage unit 12 that stores the accounting data of the target company and accounting data of multiple companies collected in advance, an indicator selection unit that selects financial indicators that are bankruptcy risk factors, a model generation unit 11b that generates a machine learning model with financial indicators as explanatory variables and bankruptcy or non-bankruptcy as the dependent variable, a bankruptcy determination unit that applies the accounting data of the target company to the machine learning model and determines whether the target company is bankrupt or not, and a simulation unit 11c that receives input from the user to change the values ​​of the explanatory variables, applies them to the machine learning model, and causes the bankruptcy determination unit to execute a process to determine whether it is bankrupt or not, and a control unit 11 that outputs the determination result to a display means in a display format in which branching paths can be identified.
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