Patent Issued for System and method for data record selection by application of predictive models and velocity analysis (USPTO 11861560): Hartford Fire Insurance Company
2024 JAN 19 (NewsRx) -- By a
The patent’s inventors are Drennan, III,
This patent was filed on
From the background information supplied by the inventors, news correspondents obtained the following quote: “Insurance claims arise in a variety of contexts, including insurance coverage for individuals, or personal lines, such as personal property coverage and personal automotive coverage, as well as business insurance coverage. Examples of categories of business insurance coverage include claims relating to employee injuries, including workers compensation claims, short term disability claims and long term disability claims. These types of claims are often underwritten by insurance companies, or are self-insured by large employers. The costs associated with these claims for insurance companies and self-insuring employers include the cost of medical services provided to injured employees, and income replacement payments provided to employees during a period when the employees are unable to perform their customary job duties.
“While insurance provides for medical expenses and partial replacement of lost income, generally regardless of responsibility for the injury, in some cases, another party is legally responsible for the injury. For example, in the event of an automobile accident, an individual insured driver or an employee of an insured business may be injured. If the negligence of another driver caused the automobile accident, then the insurance company or, in the case of the injured employee, a self-insuring employer, may be entitled to subrogation. By subrogration, the insurance company or self-insured employer stands in the shoes of the injured individual and can seek civil damages or a settlement from the negligent party, or the negligent party’s insurer. Similarly, in the event of a claim for covered property damage, the property owner’s insurance coverage may pay a claim to cover the cost of repairs, but then seek subrogation against a responsible party.
“A wide variety of factual circumstances may give rise to a right in the insurance company or self-insured employer to subrogation. For example, an employee may be injured as a result of malfunctioning equipment. The malfunction may result from defective design or manufacture of the equipment or a part, or incorrect maintenance by a contractor. Similarly, property of an insured individual may be damaged as a result of defective manufacture or maintenance of such items as household appliances, heating, ventilation and air conditioning systems, and other items.
“If a claim handler identifies that a claim may be suitable for subrogation, the claim handler refers the claim to an insurance claims recovery operation of the insurance company. However, the claim handler may not accurately identify all claims that have subrogation potential, thereby resulting in an absence of subrogation recovery. For example, the claim handler may be provided with rules such as excluding all injuries of certain types from consideration for subrogation. On the other hand, if a claim handler refers to a claims recovery operation excessive numbers of claims with little or no subrogation potential, the resources of the claims recovery operation are misdirected to review of those low potential referred claims.
“Systems and methods that provide for superior identification of subrogation opportunities would be desirable.”
Supplementing the background information on this patent, NewsRx reporters also obtained the inventors’ summary information for this patent: “In an embodiment, a computer system for processing data relating to determination of suitability for subrogation of insurance claims includes one or more data storage devices storing: data relating to the insurance claims, the stored data comprising: structured data and unstructured data, the unstructured data comprising data indicative of communications between claim handlers and one or more other persons; data defining a predictive model for assessing suitability for subrogation of claims based on review of the structured data and words and phrases extracted from the data indicative of the unstructured data. The system further includes at least one processor in communication with the one or more data storage devices and configured to, on a periodic basis: determine a set of claims for review including new claims and selected previously-reviewed claims; apply text mining to the data indicative of the unstructured data to extract words and phrases from the unstructured data; and apply the predictive model to the structured data and the extracted words and phrases from the unstructured data to determine a subrogation score associated with each of the claims in the set. The one or more processors are further configured to, for each of the previously-reviewed claims, determine whether the subrogation score is greater than on previous review; and generate a report including at least some of the new claims and the previously reviewed claims having a greater subrogation score.
“In an embodiment, a computer-implemented method for processing data for determination of suitability for subrogation of insurance claims, includes on a periodic basis accessing by a processor from one or more data storage devices data relating to insurance claims to determine a set of claims for review, the selected claims including new claims and previously-reviewed claims, the stored data including structured data and unstructured data, the unstructured data including data indicative of communications between claim handlers and one or more other persons. The method further includes processing by the processor using text mining the unstructured data to extract words and phrases from the unstructured data, and applying, by the processor, a predictive model for assessing suitability for subrogation of claims based on review of the structured data and words and phrases extracted from the unstructured data, to the structured data and the extracted words and phrases from the unstructured data to determine a subrogation score associated with each of the claims in the set. The method further includes determining by the processor, for each of the previously-reviewed claims, whether the subrogation score is greater than on previous review; and generating by the processor a report including at least some of the new claims and the previously reviewed claims having a greater subrogation score.
“In an embodiment, a non-transitory computer-readable storage medium has stored processor-executable instructions, which instructions, when executed by a processor, cause the processor to: on a periodic basis, access from one or more data storage devices data relating to claims to determine a set of claims for review, the selected claims including new claims and previously-reviewed claims, the stored data comprising structured data and unstructured data, the unstructured data comprising data indicative of communications between claim handlers and other persons; process using text mining the data indicative of notes of the unstructured data to extract words and phrases from the unstructured data; apply a predictive model for assessing suitability for subrogation of claims based on review of the structured data and words and phrases extracted from the data indicative of notes of the unstructured data, to the structured data and the extracted words and phrases from the unstructured data to determine a subrogation score associated with each of the claims in the set; determine, for each of the previously-reviewed claims, whether the subrogation score is greater than on previous review; and generate a report including at least some of the new claims and the previously reviewed claims having a greater subrogation score.”
The claims supplied by the inventors are:
“1. A computer system, comprising: one or more data storage devices storing: a plurality of data records, each data record comprising stored data, the stored data comprising: structured data and unstructured data, the unstructured data indicative of communications between two or more persons; a data storage device storing data defining a predictive model for determining a score indicative of suitability of each of the plurality of data records for forwarding to an operation system based on review of the structured data and words and phrases extracted from the unstructured data of the data record; an analysis hardware server, in communication with the data storage devices and comprising a processor configured to, on a recurring and dynamic basis, in each of a plurality of cycles: extract, using data mining, words and phrases from the unstructured data associated with a determined set of data records for review by the predictive model; apply the predictive model to the structured data and the extracted words and phrases from the unstructured data to determine a current-cycle score associated with each of the data records in the set, and assign each of the data records of the set to one of a plurality of groups of equal numbers ordered in accordance with the determined current-cycle score; for each of the data records of the set for which a score was determined in a prior cycle, determine whether the current-cycle score is greater than a most-recently determined prior cycle score for the same data record; determine a velocity of change in group to which each data record is assigned; forward a select plurality of data records to an operation system based at least in part on the determined velocity of change in group to which a data record is assigned.
“2. The computer system of claim 1, wherein the plurality of data records comprise a plurality of data records indicative of workers compensation claims, and the unstructured data indicative of communications comprises at least notes based on conversations between claim handlers and one or more of injured individuals and employer representatives.
“3. The computer system of claim 1, wherein the data records for which scores were determined in one or more prior cycles comprise data records not forwarded to the operation system and having selected aging intervals.
“4. The computer system of claim 3, wherein the selected aging intervals include a first aging interval of between 10 and 45 days and a second aging interval of at least 180 days.
“5. The computer system of claim 1, wherein the predictive model comprises data values and coefficients associated with structured data, certain data values being negative and indicative of a reduced suitability for forwarding, and certain data values being positive and indicative of an increased suitability for forwarding.
“6. The computer system of claim 5, wherein the plurality of data records comprise data indicative of workers compensation claims and the data values associated with the structured data comprise an on premises indicator having a positive or negative value and a nature of injury indicator.
“7. The computer system of claim 5, wherein the structured data values include a report lag indicator, having a positive coefficient for a short report lag value and a negative coefficient for a long report lag value.
“8. The computer system of claim 1, wherein the predictive model comprises data coefficients associated with extracted words and phrases from unstructured data and positive and negative coefficients associated with the extracted words and phrases.
“9. A computer-implemented method comprising: storing, in one or more data storage devices, a plurality of data records, each data record comprising stored data, the stored data comprising: structured data and unstructured data, the unstructured data indicative of communications between two or more persons; on a recurring and dynamic basis on a cycle, by a processor of an analysis hardware server: extracting, by the processor, using data mining, words and phrases from the unstructured data associated with a determined set of data records for review; applying, by the processor, to each of the data records of the set, a predictive model for determining a current-cycle score indicative of suitability of data records for forwarding to an operation system, the predictive model being configured to perform the determination responsive to receipt of one of the data records, based on review of the structured data and words and phrases extracted from the unstructured data of the data record, and assigning each of the data records of the set to one of a plurality of groups of equal numbers ordered in accordance with the determined current-cycle score; determining, by the processor, for each of the data records in the set for which a score was determined in a prior cycle, whether the current-cycle score is greater than a most recently determined prior cycle score; determining, by the processor, a velocity of change in group to which each data record is assigned; forwarding to an operation system a plurality of data records selected by the processor based at least in part on the determined velocity of change in group to which a data record is assigned.
“10. The computer-implemented method of claim 9, wherein the determined set of data records for review comprises data records having no score determined in any prior cycle and selected data records assigned scores in one or more prior cycles.
“11. The computer-implemented method of claim 10, wherein the selected data records assigned scores in one or more prior cycles comprise data records not forwarded to the operation system and having selected aging intervals.
“12. The computer-implemented method of claim 9, wherein extracting words and phrases from the unstructured data using data mining comprises identifying sentences using text parsing logic, and tagging identified words to be associated with categories and subcategories.
“13. The computer-implemented method of claim 9, wherein the predictive model comprises data values and coefficients associated with structured data.
“14. The computer-implemented method of claim 13, wherein certain of the data values are negative and indicative of a reduced suitability for forwarding, and certain of the data values are positive and indicative of an increased suitability for forwarding.
“15. The computer-implemented method of claim 9, wherein a positive velocity of change in group renders a data record more likely to be selected for forwarding, and a negative velocity of change in group renders a data record less likely to be selected for forwarding.
“16. The computer-implemented method of claim 9, wherein forwarding the selected plurality of data records comprises forwarding the selected plurality of data records via bulk download using xml documents.”
For the URL and additional information on this patent, see: Drennan, III,
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