Intellectual Property India Publishes Patent Application for Predictive System For Early Detection And Automated Resolution Of Net Asset Value (nav) Breaks Using Machine Learning In Fund Accounting Systems

MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641081964 A) filed by Sathish Kaniganahalli Ramareddy on July 02, 2026, for Predictive System For Early Detection And Automated Resolution Of Net Asset Value (nav) Breaks Using Machine Learning In Fund Accounting Systems.

Inventor includes Sathish Kaniganahalli Ramareddy.

The application for the patent was published on July 10, 2026, under issue no. 28/2026.

Abstract: Predictive System for Early Detection and Automated Resolution of Net Asset Value (NAV) Breaks Using Machine Learning in Fund Accounting Systems ABSTRACT The present invention discloses a predictive system for early detection and automated resolution of Net Asset Value (NAV) breaks in fund accounting systems using machine learning techniques. The system comprises a data acquisition module configured to collect financial, transactional, accounting, reconciliation, and market data from multiple internal and external sources. A preprocessing module cleanses, validates, and standardizes the collected data, while a feature engineering module extracts relevant operational, financial, and behavioral indicators associated with NAV break occurrences. A machine learning prediction engine analyzes historical and real-time data to identify hidden patterns, estimate break probabilities, and generate risk scores indicating potential NAV discrepancies before final NAV publication. An anomaly detection module continuously monitors operational activities and identifies irregularities including pricing errors, missing transactions, reconciliation mismatches, settlement delays, and valuation inconsistencies. Upon detection of a potential break, an automated resolution engine initiates corrective actions including validation procedures, reconciliation processes, workflow routing, exception management, and resolution recommendations. The system further incorporates a feedback learning module configured to retrain predictive models using incident outcomes and user actions, thereby continuously improving prediction accuracy and operational performance. By transforming NAV break management from a reactive process into a predictive and automated framework, the invention enhances fund accounting accuracy, reduces manual intervention, minimizes operational and regulatory risks, and improves overall efficiency and compliance.

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