Securities Claims Identification System for Fraud Recovery
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Solution Overview
Problem
Investors and investment managers often miss opportunities for maximizing securities fraud recovery due to system inefficiencies, conflicts of interest, and lack of awareness, resulting in inadequate or delayed recoveries for portfolio assets.
Innovation Solution
A system and method for creating an aggregated class action litigation claims database that uses a graphical user interface to monitor and analyze securities portfolios for fraudulent activity, providing alerts and automated audits, and employing machine learning to predict trading volatility and optimize recovery strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual monitoring of securities portfolios is used, then system simplicity is maintained, but recovery rates and claim identification accuracy deteriorate due to human error and inefficiency
Solution Approach 1:
The patent replaces manual mechanical monitoring processes with automated electronic systems including machine learning models, algorithms, and software platforms that continuously analyze portfolio data, detect securities fraud, and identify claims opportunities without human intervention
Solution Approach 2:
The system enables self-service through automated portfolio monitoring where the electronic system independently detects fraudulent activity, identifies claim opportunities, and generates reports without requiring manual analysis by investors or intermediaries
2Productivity
If automated portfolio monitoring systems are implemented, then recovery rates increase through improved claim identification, but system complexity and implementation costs increase
Solution Approach 1:
The patent creates a multi-functional system that simultaneously performs portfolio monitoring, fraud detection, claim identification, and recovery optimization through a single integrated platform, eliminating the need for multiple separate systems and reducing overall complexity
Solution Approach 2:
The system performs preliminary analysis and identification of potential claims opportunities before formal litigation is initiated, allowing investors to proactively identify and pursue recovery opportunities rather than reacting to settled cases
3Reliability
If independent conflict-free analysis systems are used, then objectivity and recovery optimization improve, but the need for multiple data sources and processing mechanisms increases complexity
Solution Approach 1:
The patent introduces an independent electronic analysis system as an intermediary between portfolio data and investment decisions, providing objective, conflict-free analysis that eliminates biases from traditional intermediaries while consolidating multiple data sources into a unified processing mechanism
Data Source
AI summary
Systems and methods for securities claims identification, optimization and recovery are disclosed herein. The disclosed system may maximize returns on security claims assets arising from alleged fraud in the purchase or sale of securities in a securities portfolio. In one embodiment, the disclosed system monitors data, including unstructured data, relating to a plurality of entities' securities, and creates an aggregated data set to which machine learning may be applied to identify characteristics indicative of an event of interest, such as fraud. The systems and methods of the present invention may be used to monitor an investor portfolio using analytic tools to identify asynchronous activity or movements in portfolio securities associated with the event of interest, and perform loss and damages valuation analysis, and assist with identifying securities claims and optimize recovery of revenue associated with the securities claims.