Abstract: The system and methods for securities claims identification, optimization and recovery are disclosed herein. The disclosed system can maximizes returns on assets that are the securities claims arising from alleged fraud in the purchase or sale of securities in a securities portfolio. In one embodiment, the disclosed system monitors portfolio using analytics tools to identify asynchronous activity or movements in portfolio securities, performs loss and damages valuation analysis, open arms-length communications with securities litigation plaintiffs' bar and/or litigation funders, publishes relevant information to investors, provides analysis and information for merit analysis, counsel selection and/or litigation monitoring and performs risk mitigation analysis to identify securities claims and optimize recovery of revenue associated with the securities claims.

Abstract: The system and methods for securities claims identification, optimization and recovery are disclosed herein. The disclosed system can maximizes returns on assets that are the securities claims arising from alleged fraud in the purchase or sale of securities in a securities portfolio. In one embodiment, the disclosed system monitors portfolio using analytics tools to identify asynchronous activity or movements in portfolio securities, performs loss and damages valuation analysis, open arms-length communications with securities litigation plaintiffs' bar and/or litigation funders, publishes relevant information to investors, provides analysis and information for merit analysis, counsel selection and/or litigation monitoring and performs risk mitigation analysis to identify securities claims and optimize recovery of revenue associated with the securities claims.

Abstract: 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.

Abstract: The system and methods for securities claims identification, optimization and recovery are disclosed herein. The disclosed system can maximizes returns on assets that are the securities claims arising from alleged fraud in the purchase or sale of securities in a securities portfolio. In one embodiment, the disclosed system monitors portfolio using analytics tools to identify asynchronous activity or movements in portfolio securities, performs loss and damages valuation analysis, open arms-length communications with securities litigation plaintiffs' bar and/or litigation funders, publishes relevant information to investors, provides analysis and information for merit analysis, counsel selection and/or litigation monitoring and performs risk mitigation analysis to identify securities claims and optimize recovery of revenue associated with the securities claims.