State Farm Mutual Automobile Insurance had 27 patents in mobile during Q4 2023. State Farm Mutual Automobile Insurance Co filed patents related to using machine learning models to evaluate insurance applicants without considering undesired factors, managing subrogation claims using a shared ledger, calculating insurance premiums based on telematics data from transportation platforms, identifying fraudulent online applications using browsing activity, and using vehicles as payment devices by transmitting tokenized card numbers securely to POS terminals. GlobalData’s report on State Farm Mutual Automobile Insurance gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

State Farm Mutual Automobile Insurance grant share with mobile as a theme is 29% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Method of controlling for undesired factors in machine learning models (Patent ID: US20230401647A1)

The patent filed by State Farm Mutual Automobile Insurance Co. describes a method that involves training a machine learning model, specifically a neural network, to evaluate insurance applicants based on image or audio data while excluding undesired factors such as age, sex, ethnicity, and race. The trained model receives an image of the applicant, analyzes it without considering the excluded factors, and suggests an appropriate insurance premium based only on the remaining desired factors. This approach aims to prevent prejudice or discrimination in the underwriting process by controlling for undesired factors that may influence the evaluation.

The method involves training two neural networks - one to correlate appearance with health-related characteristics and another to focus on the undesired factors. These networks are then combined to analyze the applicant's image and determine health-related characteristics without considering the excluded factors. The system can receive images via communication elements, such as still images or video recordings, and is designed to suggest insurance premiums based on the analyzed data. By utilizing this method, insurance companies can make more objective and fair decisions in the underwriting process, ensuring that premiums are determined based on relevant factors rather than potentially biased considerations.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.