“Systems And Methods For Modeling Item Damage Severity” in Patent Application Approval Process (USPTO 20230245239): Allstate Insurance Company

2023 AUG 17 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A patent application by the inventor Collins, Laura (Northbrook, IL, US), filed on January 28, 2022, was made available online on August 3, 2023, according to news reporting originating from Washington, D.C., by NewsRx correspondents.

This patent application is assigned to Allstate Insurance Company (Northbrook, Illinois, United States).

The following quote was obtained by the news editors from the background information supplied by the inventors: “Insurance claims are provided to insurance providers to receive insurance benefits, such as payouts, when an insured item is lost or damaged. Insurance providers may analyze insurance claims in order to determine item damage severity and the associated expected payout amount in a given time period. However, analyzing large amounts of insurance data, such as claims where each claim has multiple variables impacting the item damage severity, may be time consuming and inaccurate.”

In addition to the background information obtained for this patent application, NewsRx journalists also obtained the inventor’s summary information for this patent application: “At least one embodiment relates to a provider computing system. The provider computing system includes a communication interface structured to communicatively couple the provider computing system to a network. The provider computing system also includes a claims database storing claims information for a plurality of claims. The claims information includes a plurality of claim variables. The provider computing system also includes an item damage severity database storing severity information. The provider computing system also includes an item damage severity modeling circuit storing computer-executable instructions embodying one or more machine learning models. The provider computing system also includes at least one processor and memory storing instructions that, when executed by the at least one processor, cause the at least one processor to: receive a first claim dataset corresponding to a first time period; parse a first plurality of variables from the first claim dataset; receive a second claim dataset corresponding to a second time period before the first time period; parse a second plurality of variables from the second claim dataset; cause, by the item damage severity modeling circuit, the one or more machine learning models to parse a first plurality of explainer values from the first claim dataset and a second plurality of explainer values from the second claim dataset; determine a first plurality of average explainer values for each of the first plurality of explainer values and a second plurality of average explainer values for each of the second plurality of explainer values; determine percent impact values, wherein each of the percent impact values correspond to a first claim variable of the first plurality of variables and a second claim variable of the second plurality of variables, and wherein the first claim variable corresponds to the second claim variable; generate and render, via a display of a computing device, a damage severity user interface comprising one or more selectable features, the one or more selectable features each representing one of the percent impact values; and filter and sort the one or more selectable features based on the percent impact values and a predetermined impact threshold such that the one or more selectable features representing the percent impact values that are above the predetermined impact threshold are ordered from left to right in descending order.

“Another embodiment relates to a method. The method includes communicatively coupling, by a communication interface, a provider computing system to a network. The method also includes storing, by a claims database, claims information for a plurality of claims. The claims information includes a plurality of claim variables. The method also includes storing, by an item damage severity database, severity information. The method also includes storing, by an item damage severity modeling circuit, computer-executable instructions embodying one or more machine learning models. The method also includes receiving a first claim dataset corresponding to a first time period. The method also includes parsing a first plurality of variables from the first claim dataset. The method also includes receiving a second claim dataset corresponding to a second time period before the first time period. The method also includes parsing a second plurality of variables from the second claim dataset. The method also includes causing, by an item damage severity modeling circuit of the provider computing system, the one or more machine learning models to parse a first plurality of explainer values from the first claim dataset and a second plurality of explainer values from the second claim dataset. The method also includes determining a first plurality of average explainer values for each of the first plurality of explainer values and a second plurality of average explainer values for each of the second plurality of explainer values. The method also includes determining percent impact values, wherein each of the percent impact values correspond to a first claim variable of the first plurality of variables and a second claim variable of the second plurality of variables, and wherein the first claim variable corresponds to the second claim variable. The method also includes generating and rendering, via a display of a computing device, a damage severity user interface comprising one or more selectable features, the one or more selectable features each representing one of the percent impact values. The method also includes filtering and sorting the one or more selectable features based on the percent impact values and a predetermined impact threshold such that the one or more selectable features representing the percent impact values that are above the predetermined impact threshold are ordered from left to right in descending order.

“Another embodiment relates to non-transitory computer readable media having computer executable instructions embodied therein that, when executed by at least one processor of a computing system, cause the computing system to perform operations for generating multi-variable severity values. The operations include communicatively couple, by a communication interface, to a network. The operations also include store, by a claims database, claims information for a plurality of claims. The claims information includes a plurality of claim variables. The operations also include store, by an item damage severity database, severity information. The operations also include store, by an item damage severity modeling circuit, computer-executable instructions embodying one or more machine learning models. The operations also include receive a first claim dataset corresponding to a first time period. The operations also include parse a first plurality of variables from the first claim dataset. The operations also include receive a second claim dataset corresponding to a second time period before the first time period. The operations also include parse a second plurality of variables from the second claim dataset. The operations also include cause the one or more machine learning models to parse a first plurality of explainer values from the first claim dataset and a second plurality of explainer values from the second claim dataset. The operations also include determine a first plurality of average explainer values for each of the first plurality of explainer values and a second plurality of average explainer values for each of the second plurality of explainer values. The operations also include determine percent impact values. Each of the percent impact values correspond to a first claim variable of the first plurality of variables and a second claim variable of the second plurality of variables, and wherein the first claim variable corresponds to the second claim variable. The operations also include generate and render, via a display of a computing device, a damage severity user interface comprising one or more selectable features, the one or more selectable features each representing one of the percent impact values. The operations also include filter and sort the one or more selectable features based on the percent impact values and a predetermined impact threshold such that the one or more selectable features representing the percent impact values that are above the predetermined impact threshold are ordered from left to right in descending order.

“It should be appreciated that all combinations of the foregoing concepts and additional concepts discussed in greater detail below (provided such concepts are not mutually inconsistent) are contemplated as being part of the subject matter disclosed herein. In particular, all combinations of claimed subject matter appearing at the end of this disclosure are contemplated as being part of the subject matter disclosed herein.

“The foregoing and other features of the present disclosure will become more fully apparent from the following description and appended claims, taken in conjunction with the accompanying drawings. Understanding that these drawings depict only several implementations in accordance with the disclosure and are therefore, not to be considered limiting of its scope, the disclosure will be described with additional specificity and detail through use of the accompanying drawings.

“These and other advantages and features of the systems and methods described herein, together with the organization and manner of operation thereof, will become apparent from the following detailed description when taken in conjunction with the accompanying drawings.”

The claims supplied by the inventors are:

“1. A provider computing system comprising: a communication interface structured to communicatively couple the provider computing system to a network; a claims database storing claims information for a plurality of claims, the claims information comprising a plurality of claim variables; an item damage severity database storing severity information; an item damage severity modeling circuit storing computer-executable instructions embodying one or more machine learning models; at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the at least one processor to: receive a first claim dataset corresponding to a first time period; parse a first plurality of variables from the first claim dataset; receive a second claim dataset corresponding to a second time period before the first time period; parse a second plurality of variables from the second claim dataset; cause, by the item damage severity modeling circuit, the one or more machine learning models to parse a first plurality of explainer values from the first claim dataset and a second plurality of explainer values from the second claim dataset; determine a first plurality of average explainer values for each of the first plurality of explainer values and a second plurality of average explainer values for each of the second plurality of explainer values; determine percent impact values, wherein each of the percent impact values correspond to a first claim variable of the first plurality of variables and a second claim variable of the second plurality of variables, and wherein the first claim variable corresponds to the second claim variable; generate and render, via a display of a computing device, a damage severity user interface comprising one or more selectable features, the one or more selectable features each representing one of the percent impact values; and filter and sort the one or more selectable features based on the percent impact values and a predetermined impact threshold such that the one or more selectable features representing the percent impact values that are above the predetermined impact threshold are ordered in descending order.

“2. The provider computing system of claim 1, wherein the claims database is structured to communicatively couple to a telematics device via the network, wherein the telematics device is associated with an insured item.

“3. The provider computing system of claim 2, wherein the telematics device is structured to detect, by one or more sensors, one or more impact parameter values associated with the insured item; and wherein the claims information comprises the one or more impact parameter values provided by the telematics device.

“4. The provider computing system of claim 1, wherein the instructions further cause the at least one processor to train, by the item damage severity modeling circuit, the one or more machine learning models based on a first subset of the claims information and a first subset of the severity information such that the one or more machine learning models outputs a predicted severity based on an input claim dataset, wherein the first subset of claims information corresponds to a third time period.

“5. The provider computing system of claim 4, wherein the third time period is at least partially before the second time period.

“6. The provider computing system of claim 4, wherein determining a first percent impact value of the percent impact values comprises: determining a difference between a first explainer value and a second explainer value, wherein the first explainer value is associated with the first claim variable and the second explainer value is associated with the second claim variable; and dividing the difference by the predicted severity corresponding to the first claim variable within the second time period.

“7. The provider computing system of claim 6, wherein the instructions further cause the at least one processor to: generate, by an item damage severity aggregation circuit of the provider computing system, a first actual severity value for each of the claim variables within the second time period; determine, by the item damage severity modeling circuit, a first percent change between the first plurality of average explainer values and the second plurality of average explainer values; determine, by the item damage severity modeling circuit, a second percent change between the first plurality of average explainer values and the first actual severity value; and correct, by the item damage severity modeling circuit, the first percent impact value by multiplying the first percent impact value by the second percent change divided by the first percent change.

“8. The provider computing system of claim 7, wherein the severity user interface is structured to display, on the display and responsive to a first selectable feature of the one or more selectable features being selected, a detailed list of impact data associated with the first percent impact value, wherein the first selectable feature is associated with the first percent impact value.

“9. A method comprising: communicatively coupling, by a communication interface, a provider computing system to a network; storing, by a claims database, claims information for a plurality of claims, the claims information comprising a plurality of claim variables; storing, by an item damage severity database, severity information; storing, by an item damage severity modeling circuit, computer-executable instructions embodying one or more machine learning models; receiving a first claim dataset corresponding to a first time period; parsing a first plurality of variables from the first claim dataset; receiving a second claim dataset corresponding to a second time period before the first time period; parsing a second plurality of variables from the second claim dataset; causing, by an item damage severity modeling circuit of the provider computing system, the one or more machine learning models to parse a first plurality of explainer values from the first claim dataset and a second plurality of explainer values from the second claim dataset; determining a first plurality of average explainer values for each of the first plurality of explainer values and a second plurality of average explainer values for each of the second plurality of explainer values; determining percent impact values, wherein each of the percent impact values correspond to a first claim variable of the first plurality of variables and a second claim variable of the second plurality of variables, and wherein the first claim variable corresponds to the second claim variable; generating and rendering, via a display of a computing device, a damage severity user interface comprising one or more selectable features, the one or more selectable features each representing one of the percent impact values; and filtering and sorting the one or more selectable features based on the percent impact values and a predetermined impact threshold such that the one or more selectable features representing the percent impact values that are above the predetermined impact threshold are ordered from left to right in descending order.

“10. The method of claim 9, further comprising: communicatively coupling, by the communication interface, the claims database to a telematics device via the network, wherein the telematics device is associated with an insured item; detecting, by one or more sensors of the telematics device, one or more impact parameter values associated with the insured item; and receiving, by the claims database and via the communication interface, the claims information, the claims information comprising the one or more impact parameter values provided by the telematics device.

“11. The method of claim 9, further comprising training, by the item damage severity modeling circuit, the one or more machine learning models based on a first subset of the claims information and a first subset of the severity information such that the one or more machine learning models outputs a predicted severity based on an input claim dataset, wherein the first subset of claims information corresponds to a third time period.

“12. The method of claim 11, wherein the third time period is at least partially before the second time period.

“13. The method of claim 11, wherein determining a first percent impact value of the percent impact values comprises: determining a difference between a first explainer value and a second explainer value, wherein the first explainer value is associated with the first claim variable and the second explainer value is associated with the second claim variable; and dividing the difference by the predicted severity corresponding to the first claim variable within the second time period.

“14. The provider computing system of claim 13, wherein the instructions further cause the at least one processor to: generate, by an item damage severity aggregation circuit of the provider computing system, a first actual severity value for each of the claim variables within the second time period; determine, by the item damage severity modeling circuit, a first percent change between the first plurality of average explainer values and the second plurality of average explainer values; determine, by the item damage severity modeling circuit, a second percent change between the first plurality of average explainer values and the first actual severity value; and correct, by the item damage severity modeling circuit, the first percent impact value by multiplying the first percent impact value by the second percent change divided by the first percent change.”

There are additional claims. Please visit full patent to read further.

URL and more information on this patent application, see: Collins, Laura. Systems And Methods For Modeling Item Damage Severity. U.S. Patent Application Number 20230245239, filed January 28, 2022 and posted August 3, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(20230245239)&db=US-PGPUB&type=ids

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