Researchers Submit Patent Application, “Method And System For Detecting Insurance Loss And Automating Insurance Loss Prevention”, for Approval (USPTO 20230196474): Chrp Technologies Inc.

2023 JUL 10 (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 KALISCH, Micah (DeBary, FL, US); MA, Chin (DeBary, FL, US), filed on December 22, 2022, was made available online on June 22, 2023.

The patent’s assignee is Chrp Technologies Inc. (DeBary, Florida, United States).

News editors obtained the following quote from the background information supplied by the inventors: “Home insurance companies generally pay a huge sum of money in claims annually, wherein a substantial amount in those claims is avoidable. Virtually, all insurers miss the opportunity to avoid these substantial payouts, due to lack of preventative maintenance embedded into the consumer’s home insurance experience.

“Loss prevention refers to any action that is taken to reduce the amount of theft, breakage, or wastage in a business. Adoption of loss prevention in the insurance industry has dramatically reduced claims, specifically in the personal automotive insurance industry. This is analogous to telematics that has made driving and therefore the drivers safer. However, for enabling such loss prevention strategies, currently, the insurance industry faces a multitude of challenges. For instance, underwriters of home insurance do not have the required expertise to understand a multitude of risks that come with a building’s construction and home inspectors do not have the expertise to understand coverage and risk-management associated with insurances. As a result, there is a disconnect between the recognition of a potential loss that is preventable, such as a faulty water supply line in a toilet or a kitchen sink.

“Further, erstwhile solutions available for prevention of such insurance loss or claims, do not proactively identify issues that may lead to potential insurance claim, and therefore are unable to implement appropriate measures for prevention of such losses in a timely manner.

“Limitations and disadvantages of conventional and traditional approaches will become apparent to one of ordinary skill in the art, through comparison of described systems with some aspects of the present disclosure, as set forth in the remainder of the present application and with reference to the drawings.”

As a supplement to the background information on this patent application, NewsRx correspondents also obtained the inventors’ summary information for this patent application: “A method and system for automating detection of insurance loss or risk and insurance loss prevention is provided substantially as shown in and/or described in connection with, at least one of the figures, as set forth more completely in the claims.

“These and other features and advantages of the present disclosure may be appreciated from a review of the following detailed description of the present disclosure, along with the accompanying figures in which like reference numerals refer to like parts throughout.”

The claims supplied by the inventors are:

“1. A computer-implemented method for detecting insurance loss or risk, comprising: accessing a plurality of digital images corresponding to a property; classifying, using a trained Artificial Intelligence (AI)-based classifier, the plurality of digital images into one or more AI containers based on one or more inspection points in relation to the property, wherein each AI container comprises one or more secondary AI models; detecting, by the one or more secondary AI models in a respective AI container, a condition pertaining to one or more components identified in at least one digital image of the plurality of digital images, wherein the detecting comprises analyzing the at least one digital image based on the one or more inspection points associated with the respective AI container; and deriving a signal indicative of insurance loss based on the detected condition pertaining to the one or more components.

“2. The computer-implemented method of claim 1, wherein the property is at least one of a home, a residential building and an office.

“3. The computer-implemented method of claim 1, wherein the plurality of digital images comprise metadata, the metadata comprising at least one of a camera make, a camera model, white balance, ISO speed ratings, an aperture, a shutter speed, a timestamp, an image resolution, a file name, a file size, a lens used, a focal length, an exposure bias, and flash.

“4. The computer-implemented method of claim 1, wherein the one or more inspection points comprise at least one of a toilet plumbing, sink plumbing, washer supply line and valve, electrical panel, water heater, address verification, product label and roof model.

“5. The computer-implemented method of claim 1, wherein the classifying comprises classifying, using the AI-based classifier, the plurality of digital images into the one or more AI containers based on one or more categories and one or more sub-inspection points in relation to the property.

“6. The computer-implemented method of claim 5, wherein the one or more categories comprise at least one of a home category and a room category.

“7. The computer-implemented method of claim 5, wherein the one or more sub-inspection points comprise at least one of a water valve, a plumbing joint, a tank bolt, corrosion, rusting, a leaking water supply line, a coupler nut, mains breakers, a manufacture date of HVAC, a brand of HVAC, a manufacture date of furnace, and a brand of furnace.

“8. The computer-implemented method of claim 1 further comprises iteratively auto-training the AI-based classifier using new digital images until the AI-based classifier reaches a maximum precision.

“9. The computer-implemented method of claim 1, wherein the detecting comprises identifying and scaling the one or more components down to an extra small pixel level, wherein the one or more secondary AI models detect a condition pertaining to the one or more components on a pixel level scale.

“10. The computer-implemented method of claim 1, wherein a condition is at least one of a damage and a health status of a component, wherein a component is a home component.

“11. The computer-implemented method of claim 1, wherein deriving the signal comprises generating an inspection report based on the signal, wherein the inspection report comprises one or more recommendations related to insurance risks and insurance loss prevention actions.

“12. The computer-implemented method of claim 11, wherein the inspection report further comprises at least one of an estimated cost to fix, an actual cost to fix, a client follow-up status, a resolution status, timestamps, and resolution notes.

“13. A system for detecting insurance loss or risk, comprising: a memory; a processor communicatively coupled to the memory, wherein the processor is configured to: access a plurality of digital images corresponding to a property; classify, using a trained Artificial Intelligence (AI)-based classifier, the plurality of digital images into one or more AI containers based on one or more inspection points in relation to the property, wherein each AI container comprises one or more secondary AI models; detect, by the one or more secondary AI models in a respective AI container, a condition pertaining to one or more components identified in at least one digital image of the plurality of digital images, wherein the one or more secondary AI models are further configured to analyze the at least one digital image based on the one or more inspection points associated with the respective AI container; and derive a signal indicative of insurance loss based on the detected condition pertaining to the one or more components.

“14. The system of claim 13, wherein the one or more inspection points comprise at least one of a toilet plumbing, sink plumbing, washer supply line and valve, electrical panel, water heater, address verification, product label and roof model.

“15. The system of claim 13, wherein the processor is further configured to classify, using the AI-based classifier, the plurality of digital images into the one or more AI containers based on one or more categories and one or more sub-inspection points in relation to the property.

“16. The system of claim 15, wherein the one or more categories comprise at least one of a home category and a room category.

“17. The system of claim 15, wherein the one or more sub-inspection points comprise at least one of a water valve, a plumbing joint, a tank bolt, corrosion, rusting, a leaking water supply line, a coupler nut, mains breakers, a manufacture date of HVAC, a brand of HVAC, a manufacture date of furnace, and a brand of furnace.

“18. The system of claim 13, wherein the processor is configured to iteratively auto-train the AI-based classifier using new digital images until the AI-based classifier reaches a maximum precision.

“19. The system of claim 13, wherein the processor is configured to identify and scale, using the one or more secondary AI models, the one or more components down to an extra small pixel level, wherein the one or more secondary AI models detect a condition pertaining to the one or more components on a pixel level scale.

“20. The system of claim 13, wherein the processor is configured to generate an inspection report based on the signal, wherein the inspection report comprises one or more recommendations related to insurance risks and insurance loss prevention actions.”

For additional information on this patent application, see: KALISCH, Micah; MA, Chin. Method And System For Detecting Insurance Loss And Automating Insurance Loss Prevention. U.S. Patent Application Number 20230196474, filed December 22, 2022 and posted June 22, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(20230196474)&db=US-PGPUB&type=ids

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