Researchers Submit Patent Application, “Automated Insurance Claim Evaluation Through Correlated Metadata”, for Approval (USPTO 20210082054)

2021 APR 07 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- From Washington, D.C., NewsRx journalists report that a patent application by the inventors Rodriguez Bravo, Cesar Augusto (Alajuela, CR); Fajardo, Ivonne Rocio Cuervo (San Rafael, CR); Orellana, Ugo Ivan (Westlake, CA); Trim, Craig M. (Ventura, CA), filed on September 16, 2019, was made available online on March 18, 2021.

The patent’s assignee is International Business Machines Corporation (Armonk, New York, United States).

News editors obtained the following quote from the background information supplied by the inventors: “The present invention relates generally to the field of fraud detection, and more particularly to fraudulent insurance claim detection.

“Insurance is a means of protection from financial loss. It is a form of risk management, primarily used to hedge against the risk of a contingent or uncertain loss. An insurance providing entity is often known as an insurer or insurance company. A person or entity that purchases insurance is known as an insured or, alternatively, as a policyholder. The transaction involves the insured providing payment to the insurer in exchange for the insurer’s promise to compensate the insured in the event of a covered loss. The loss typically involves something in which the insured has an insurable interest established by ownership, possession, and/or a pre-existing relationship. The insured receives a contract, known as an insurance policy, which details the conditions and circumstances under which the insurer will compensate the insured. The amount of money charged by the insurer for the coverage established in the insurance policy is called the premium. If the insured experiences a loss which is potentially covered by the insurance policy, the insured submits a claim to the insurance company for processing.

“Insurance fraud is an act committed to defraud one or more insurance processes. Insurance fraud may occur when a claimant attempts to fraudulently obtain some benefit or advantage they are not legally entitled to obtain. Insurance fraud may also occur when an insurer knowingly denies one or more benefits that the insurer is contractually obligated to provide to a claimant. Common insurance fraud schemes include premium diversion, fee churning, asset diversion, and/or workers compensation fraud. False insurance claims are insurance claims filed with fraudulent intention towards an insurance provider. Fraudulent claims account for a significant portion of all claims received by insurers and cost upwards of billions of dollars annually. Insurance fraud is diverse crime that occurs across a wide range of insurance types and vary in severity. Insurance fraud poses a significant problem for the general public, governments and other organizations attempt to deter such activity when possible.

“A ‘smart device’ is an electronic device that is typically connected to other devices and/or networks through various wireless protocols (e.g., Bluetooth, Wi-Fi, etc.) that operates, to some extent, interactively and autonomously. Examples of smart devices include smartphones, autonomous vehicles, smartwatches, and smart speakers. A smart device may be programmed to complete a specific task or interact with other smart device accessories to complete tasks. Typically, data is transmitted and/or received though various wireless protocols with a wide range of applications, such as data analytics.”

As a supplement to the background information on this patent application, NewsRx correspondents also obtained the inventors’ summary information for this patent application: “According to an aspect of the present invention, there is a method, computer program product and/or system that performs the following operations (not necessarily in the following order): (i) receiving an insurance event data set, including a plurality of event metadata values; (ii) parsing the event metadata values into a plurality of event data categories; (iii) generate an initial network of correlations between at least some event metadata values within the same event data category; and (iv) generate a secondary network of correlations between at least some event metadata values, where connections are made between event metadata values of different event data categories based, at least in part, on a nature of information corresponding to the event metadata values.”

The claims supplied by the inventors are:

“1. A computer-implemented method (CIM) comprising: receiving an insurance event data set, including a plurality of event metadata values; parsing the event metadata values into a plurality of event data categories; generate an initial network of correlations between at least some event metadata values within a shared event data category; generate a secondary network of correlations between at least some event metadata values, where connections are made between event metadata values of different event data categories based, at least in part, on a nature of information corresponding to the event metadata values; generating a personal risk score (PRS) for one or more involved parties corresponding to an insurance event based, at least in part, on inconsistencies between event metadata values within the initial and secondary networks; automatically generating an insurance claim conclusion based on one or more PRS scores; and responsive to automatically generating the insurance claim conclusion, outputting over a computer network to a computer device an electronic message that is modified based on the insurance claim conclusion.

“2. The CIM of claim 1, wherein the PRS scores are selected from the group consisting of: (i) low risk, (ii) medium risk, and (iii) high risk.

“3. The CIM of claim 2, wherein the automatically generated insurance claim conclusion is a claim denial based, at least in part, on a high risk PRS score.

“4. The CIM of claim 1, wherein the outputted electronic message further includes information indicative of how the PRS score was calculated that resulted in the automatically generated insurance claim conclusion.

“5. The CIM of claim 1, wherein the plurality of event metadata values includes a heartrate metadata set from a wearable smart device, with the heartrate metadata set including at least one heartrate value associated with a timestamp.

“6. The CIM of claim 1, wherein the plurality of event metadata values includes an accelerometer metadata set from a wearable smart device, with the accelerometer metadata set including at least one acceleration value associated with a timestamp.

“7. A computer program product (CPP) comprising: a machine readable storage device; and computer code stored on the machine readable storage device, with the computer code including instructions for causing a processor(s) set to perform operations including the following: receiving an insurance event data set, including a plurality of event metadata values; parsing the event metadata values into a plurality of event data categories, generate an initial network of correlations between at least some event metadata values within a shared event data category, generate a secondary network of correlations between at least some event metadata values, where connections are made between event metadata values of different event data categories based, at least in part, on a nature of information corresponding to the event metadata values, generating a personal risk score (PRS) for one or more involved parties corresponding to an insurance event based, at least in part, on inconsistencies between event metadata values within the initial and secondary networks, automatically generating an insurance claim conclusion based on one or more PRS scores, and responsive to automatically generating the insurance claim conclusion, outputting over a computer network to a computer device an electronic message that is modified based on the insurance claim conclusion.

“8. The CPP of claim 7, wherein the PRS scores are selected from the group consisting of: (i) low risk, (ii) medium risk, and (iii) high risk.

“9. The CPP of claim 8, wherein the automatically generated insurance claim conclusion is a claim denial based, at least in part, on a high risk PRS score.

“10. The CPP of claim 7, wherein the outputted electronic message further includes information indicative of how the PRS score was calculated that resulted in the automatically generated insurance claim conclusion.

“11. The CPP of claim 7, wherein the plurality of event metadata values includes a heartrate metadata set from a wearable smart device, with the heartrate metadata set including at least one heartrate value associated with a timestamp.

“12. The CPP of claim 7, wherein the plurality of event metadata values includes an accelerometer metadata set from a wearable smart device, with the accelerometer metadata set including at least one acceleration value associated with a timestamp.

“13. A computer system (CS) comprising: a processor(s) set; a machine readable storage device; and computer code stored on the machine readable storage device, with the computer code including instructions for causing the processor(s) set to perform operations including the following: receiving an insurance event data set, including a plurality of event metadata values; parsing the event metadata values into a plurality of event data categories, generate an initial network of correlations between at least some event metadata values within a shared event data category, generate a secondary network of correlations between at least some event metadata values, where connections are made between event metadata values of different event data categories based, at least in part, on a nature of information corresponding to the event metadata values, generating a personal risk score (PRS) for one or more involved parties corresponding to an insurance event based, at least in part, on inconsistencies between event metadata values within the initial and secondary networks, automatically generating an insurance claim conclusion based on one or more PRS scores, and responsive to automatically generating the insurance claim conclusion, outputting over a computer network to a computer device an electronic message that is modified based on the insurance claim conclusion.

“14. The CS of claim 13, wherein the PRS scores are selected from the group consisting of: (i) low risk, (ii) medium risk, and (iii) high risk.

“15. The CS of claim 14, wherein the automatically generated insurance claim conclusion is a claim denial based, at least in part, on a high risk PRS score.

“16. The CS of claim 13, wherein the outputted electronic message further includes information indicative of how the PRS score was calculated that resulted in the automatically generated insurance claim conclusion.

“17. The CS of claim 13, wherein the plurality of event metadata values includes a heartrate metadata set from a wearable smart device, with the heartrate metadata set including at least one heartrate value associated with a timestamp.

“18. The CS of claim 13, wherein the plurality of event metadata values includes an accelerometer metadata set from a wearable smart device, with the accelerometer metadata set including at least one acceleration value associated with a timestamp.”

For additional information on this patent application, see: Rodriguez Bravo, Cesar Augusto; Fajardo, Ivonne Rocio Cuervo; Orellana, Ugo Ivan; Trim, Craig M. Automated Insurance Claim Evaluation Through Correlated Metadata. Filed September 16, 2019 and posted March 18, 2021. Patent URL: http://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220210082054%22.PGNR.&OS=DN/20210082054&RS=DN/20210082054

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