Granted Patent B2

US 12,749,124 · App. 18/204,580 · Granted Sep 29, 2026

Inventors: Brian Mark Fields (Phoenix, AZ); Nathan L. Tofte (Downs, IL); Joseph Robert Brannan (Bloomington, IL); Vicki King (Bloomington, IL); Justin Davis (Bloomington, IL)

Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

G06Q40/08H04L51/02G06F40/40G06Q50/26

Abstract

Claims (89)

1 . A computer-implemented method for improved artificial intelligence (AI) insurance analysis for an insurance underwriter, the method comprising, via one or more processors:

initially training an AI model included in a pretrained large language model (LLM) for multi-turn conversations with starting prompts as inputs and using short term and long term memory, wherein the initial training uses a large training dataset of text;

further training the AI model by:

during a first training phase: building a supervised fine-tuning AI model based upon (i) historical input statements, and (ii) tags linking types of insurance policies to respective historical input statements;

during a second training phase: building a reward model using reinforcement learning with human feedback (RLHF) by iteratively inputting a previously unknown prompt into the supervised fine-tuning AI model and ranking output responses of the supervised fine-tuning AI model, wherein the ranked output responses are used to train the reward model; and

during a third training phase: building the AI model by: (1) inputting an additional previously unknown prompt into both (i) the supervised fine-tuning AI model, and (ii) the AI model, and (2) building the AI model according to (i) a comparison between outputs of the supervised fine-tuning AI model and the AI model and (ii) an output of the reward model;

determining, with an AI chatbot including the AI model, from an input statement, a type of insurance policy, wherein the type of insurance policy comprises a homeowners insurance policy, a renters insurance policy, and/or an umbrella insurance policy;

determining, with the AI chatbot, from the input statement, a question corresponding to the type of insurance policy;

determining, with the AI chatbot, an answer to the question by retrieving insurance information based upon (i) the type of insurance policy, and (ii) the question; and

displaying, via the AI chatbot, on a display of an insurance underwriter computing device, the answer to the question.

2 . The computer-implemented method of claim 1 , further including:

determining, with the AI chatbot, that the answer to the question is related to a value of a home; and

in response to determining that the question relates to the value of a home, accessing, with the AI chatbot, an estimation AI algorithm to estimate the value of the home;

wherein the answer to the question is further determined based upon the estimated value of the home.

3 . The computer-implemented method of claim 1 , wherein:

the input statement comprises text;

the method further comprises, with the AI chatbot, applying a natural language processing (NLP) algorithm to the text to generate a word or phrase; and

(i) the determining the type of insurance policy comprises determining the type of insurance policy based upon the word or phrase; and/or

(ii) the determining the question comprises determining the question based upon the word or phrase.

4 . The computer-implemented method of claim 1 , wherein:

the input statement comprises audio data;

the method further comprises, with the AI chatbot, (i) applying an audio recognition program to the audio data to generate text, and (ii) applying a natural language processing (NLP) algorithm to the text to generate a word or phrase; and

(i) the determining the type of insurance policy comprises determining the type of insurance policy based upon the word or phrase; and/or

(ii) the determining the question comprises determining the question based upon the word or phrase.

5 . The computer-implemented method of claim 1 , wherein the retrieving the insurance information comprises retrieving the insurance information from: (i) a ground truth insurance database, (ii) an insurance information aggregator database, (iii) an insurance claims database, (iv) a government records database, (v) a police reports database, and/or (vi) a blockchain.

6 . The computer-implemented method of claim 1 , wherein the determining the question corresponding to the type of insurance policy comprises:

determining, with the AI chatbot, that no question exists in the input statement; and

in response to determining that no question exists in the input statement, setting, with the AI chatbot, the determined question to be a default question corresponding to the type of insurance policy.

7 . The computer-implemented method of claim 6 , wherein one of:

the type of insurance policy is a homeowners insurance policy, and the default question corresponding to the type of insurance policy relates to what a most common type of damage to a home is in a particular geographic area;

the type of insurance policy is a renters insurance policy, and the default question corresponding to the type of insurance policy relates to what a most common type of possession of a renter is in the particular geographic area;

the type of insurance policy is an auto insurance policy, and the default question corresponding to the type of insurance policy relates to what a car theft rate is in the particular geographic area;

the type of insurance policy is an auto insurance policy, and the default question corresponding to the type of insurance policy relates to: services provided by an autobody shop, and/or reviews of the autobody shop;

the type of insurance policy is a life insurance policy, and the default question corresponding to the type of insurance policy relates to what leading causes of death are in the particular geographic area;

the type of insurance policy is a disability insurance policy, and the default question corresponding to the type of insurance policy relates to what leading causes of disability are in the particular geographic area; or

the type of insurance policy is an umbrella insurance policy, and the default question corresponding to the type of insurance policy relates to an average amount of civil claims against umbrella insurance policy holders in a particular geographic area.

8 . The computer-implemented method of claim 1 , wherein the AI chatbot includes: a generative AI chatbot, a deep learning algorithm, a generative pre-trained transformer (GPT), and/or long-short-term-memory (LSTM).

9 . The computer-implemented method of claim 1 , further comprising, via the one or more processors:

with the AI chatbot, applying a natural language processing (NLP) algorithm to the input statement to generate a plurality of tokens, each token comprising a word or phrase;

building, with the AI chatbot, a query vector, a key vector, and/or a value vector for each token of the plurality of tokens;

determining, with the AI chatbot, a similarity metric between a built query vector of a token of the plurality of tokens and each built key vector by taking respective dot products of the built query vector and each built key vector;

generating, with the AI chatbot, normalized weights by routing the respective dot products into a softmax function; and

generating, with the AI chatbot, a final vector by multiplying the normalized weights by the value vector of the token of the plurality of token, wherein the final vector represents an importance of the token of the plurality of tokens.

10 . The computer-implemented method of claim 9 , wherein:

the determining the type of insurance policy comprises determining the type of insurance policy based upon the final vector;

the determining the question corresponding to the type of insurance policy comprises determining the question corresponding to the type of insurance policy based upon the final vector; and/or

the determining the answer comprises determining the answer based upon the final vector.

11 . The computer-implemented method of claim 1 , further comprising training the AI chatbot by inputting, via the one or more processors, into the AI chatbot, historical data from a ground truth insurance database.

12 . A computer system for improved artificial intelligence (AI) insurance analysis for an insurance underwriter, the computer system comprising one or more processors configured to:

initially train an AI model included in a pretrained large language model (LLM) for multi-turn conversations with starting prompts as inputs and using short term and long term memory, wherein the initial training uses a large training dataset of text;

further train the AI model by:

during a first training phase: building a supervised fine-tuning AI model based upon (i) historical input statements, and (ii) tags linking types of insurance policies to respective historical input statements;

during a second training phase: building a reward model using reinforcement learning with human feedback (RLHF) by iteratively inputting a previously unknown prompt into the supervised fine-tuning AI model and ranking output responses of the supervised fine-tuning AI model, wherein the ranked output responses are used to train the reward model; and

during a third training phase: building the AI model by: (1) inputting an additional previously unknown prompt into both (i) the supervised fine-tuning AI model, and (ii) the AI model, and (2) building the AI model according to (i) a comparison between outputs of the supervised fine-tuning AI model and the AI model and (ii) an output of the reward model;

determine, with an AI chatbot including the AI model, from an input statement, a type of insurance policy, wherein the type of insurance policy comprises a homeowners insurance policy, a renters insurance policy, and/or an umbrella insurance policy;

determine, with the AI chatbot, from the input statement, a question corresponding to the type of insurance policy;

determine, with the AI chatbot, an answer to the question by retrieving insurance information based upon (i) the type of insurance policy, and (ii) the question; and

display, via the AI chatbot, on a display of an insurance underwriter computing device, the answer to the question.

13 . The computer system of claim 12 , wherein:

the input statement comprises text; and

the one or more processors are further configured to:

with the AI chatbot, apply a natural language processing (NLP) algorithm to the text to generate a word or phrase; and

determine the type of insurance policy by determining the type of insurance policy based upon the word or phrase.

14 . The computer system of claim 12 , wherein the one or more processors are configured to retrieve the insurance information from: (i) a ground truth insurance database, (ii) an insurance information aggregator database, (iii) an insurance claims database, (iv) a government records database, (v) a police reports database, and/or (vi) a blockchain.

15 . The computer system of claim 12 , wherein the determining the question corresponding to the type of insurance policy includes:

determining, with the AI chatbot, that no question exists in the input statement; and

in response to determining that no question exists in the input statement, setting, with the AI chatbot, the determined question to be a default question corresponding to the type of insurance policy.

16 . A computer device for improved artificial intelligence (AI) insurance analysis for an insurance underwriter, the computer device comprising:

one or more processors; and

one or more memories;

the one or more memories having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computer device to:

initially train an AI model included in a pretrained large language model (LLM) for multi-turn conversations with starting prompts as inputs and using short term and long term memory, wherein the initial training uses a large training dataset of text;

further train the AI model by:

during a first training phase: building a supervised fine-tuning AI model based upon (i) historical input statements, and (ii) tags linking types of insurance policies to respective historical input statements;

during a second training phase: building a reward model using reinforcement learning with human feedback (RLHF) by iteratively inputting a previously unknown prompt into the supervised fine-tuning AI model and ranking output responses of the supervised fine-tuning AI model, wherein the ranked output responses are used to train the reward model; and

during a third training phase: building the AI model by: (1) inputting an additional previously unknown prompt into both (i) the supervised fine-tuning AI model, and (ii) the AI model, and (2) building the AI model according to (i) a comparison between outputs of the supervised fine-tuning AI model and the AI model and (ii) an output of the reward model;

determine, with an AI chatbot including the AI model, from an input statement, a type of insurance policy, wherein the type of insurance policy comprises a homeowners insurance policy, a renters insurance policy, and/or an umbrella insurance policy;

determine, with the AI chatbot, from the input statement, a question corresponding to the type of insurance policy;

determine, with the AI chatbot, an answer to the question by retrieving insurance information based upon (i) the type of insurance policy, and (ii) the question; and

display, via the AI chatbot, on a display of an insurance underwriter computing device, the answer to the question.

17 . The computer device of claim 16 , wherein:

the input statement comprises text; and

the one or more memories having stored thereon computer-executable instructions that, when executed by the one or more processors, further cause the computer device to:

with the AI chatbot, apply a natural language processing (NLP) algorithm to the text to generate a word or phrase; and

determine the type of insurance policy by determining the type of insurance policy based upon the word or phrase.

18 . The computer device of claim 16 , wherein the one or more memories having stored thereon computer-executable instructions that, when executed by the one or more processors, further cause the computer device to perform the retrieve of the insurance information by retrieving the insurance information from: (i) a ground truth insurance database, (ii) an insurance information aggregator database, (iii) an insurance claims database, (iv) a government records database, (v) a police reports database, and/or (vi) a blockchain.

19 . The computer device of claim 16 , wherein the determining the question corresponding to the type of insurance policy includes:

determining, with the AI chatbot, that no question exists in the input statement; and

in response to determining that no question exists in the input statement, setting, with the AI chatbot, the determined question to be a default question corresponding to the type of insurance policy.

Assignments (1)

Continuity (10)

References Cited (260)