AI TO RECOMMEND CHANGE IN INSURANCE COVERAGE

1 . A computer-implemented method for recommending a change in insurance coverage, the method comprising:

receiving, via one or more processors, customer information of an insurance customer;

determining, via the one or more processors, that an insurance change recommendation trigger has occurred by routing the customer information into an insurance recommendation machine learning algorithm; and

in response to determining the insurance change recommendation trigger, sending, via the one or more processors, a recommendation for an insurance policy change for the insurance customer.

2 . The computer-implemented method of claim 1 , wherein the customer information comprises: (i) an email generated by a computing device of the insurance customer, (ii) an insurance profile of the insurance customer, (iii) an update to the insurance profile of the insurance customer, (iv) an interaction between the insurance customer and a chatbot, and/or (v) an interaction between an insurance agent and the insurance customer.

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

the customer information comprises an email generated by a computing device of the insurance customer;

upon receipt of the customer information, the insurance recommendation machine learning algorithm analyzes the email to generate analyzed email information; and

the insurance recommendation machine learning algorithm determines that the insurance change recommendation trigger has occurred based upon the analyzed email information.

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

the insurance recommendation machine learning algorithm includes a natural language processing (NLP) machine learning algorithm;

the insurance recommendation machine learning algorithm analyzes the email to generate the analyzed email information by applying the NLP machine learning algorithm to the email to generate a word or phrase; and

the analyzed email information comprises the word or phrase.

5 . The computer-implemented method of claim 1 , wherein the customer information comprises an insurance profile of the insurance customer, and wherein the insurance recommendation machine learning algorithm determines that the insurance change recommendation trigger has occurred by:

determining an optimal insurance policy for the insurance customer based upon the insurance profile of the insurance customer; and

comparing the optimal insurance policy to a current insurance policy of the insurance customer indicated by the insurance profile of the insurance customer.

6 . The computer-implemented method of claim 1 , wherein the customer information comprises an update to an insurance profile of the insurance customer, and wherein the method further comprises:

receiving, via the one or more processors, and from an insurance company application (app), the update to the insurance customer profile of the insurance customer.

7 . The computer implemented method of claim 1 , further comprising:

receiving, via the one or more processors, from a computing device of the insurance customer, a request for communication; and

in response to receiving the request for communication, initiating, via the one or more processors, an interaction between a chatbot and the insurance customer; and

wherein the interaction between the chatbot and the insurance customer comprises: (i) at least one question and/or answer sent from the chatbot to an insurance customer computing device, and (ii) at least one question and/or answer sent from the insurance customer computing device to the chatbot; and

wherein information of the insurance customer comprises the interaction between the chatbot and the insurance customer.

8 . The computer-implemented method of claim 1 , further comprising receiving, via the one or more processors, audio data of a conversation between the insurance customer and an insurance agent, wherein the conversation corresponds to an interaction between the insurance customer and the insurance agent, and wherein the information of the insurance customer comprises the interaction between the insurance customer and the insurance agent.

9 . The computer-implemented method of claim 1 , wherein the insurance change trigger recommendation comprises a trigger to recommending changing:

a life insurance policy;

a homeowners insurance policy;

a renters insurance policy;

an auto insurance policy;

an umbrella insurance policy; and/or

a disability insurance policy.

10 . The computer-implemented method of claim 1 , wherein the insurance change trigger recommendation comprises a trigger to recommend adding a new insurance policy, and/or canceling an insurance policy.

11 . The computer-implemented method of claim 1 , wherein the insurance recommendation machine learning algorithm determines that the insurance change recommendation trigger has occurred by determining that an event of the insurance customer has occurred, and wherein the event comprises:

a child change event;

a marital status change event;

a monetary income change event;

a possession change event; and/or

a home location change event.

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

the insurance recommendation machine learning algorithm determines that the insurance change recommendation trigger has occurred by determining that an event of the insurance customer has occurred;

the event comprises a child change event comprising that the insurance customer has had a child; and

the insurance change recommendation trigger comprises a trigger to recommend increasing life insurance coverage.

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

the insurance recommendation machine learning algorithm determines that the insurance change recommendation trigger has occurred by determining that an event of the insurance customer has occurred;

the event comprises a monetary income change event; and

the insurance change recommendation trigger comprises a trigger to recommend modifying coverage of an umbrella insurance policy.

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

the recommendation for the insurance policy change is based upon the determined insurance change recommendation trigger;

the insurance recommendation machine learning algorithm determines that the insurance change recommendation trigger has occurred by determining that an event of the insurance customer has occurred; and

one of:

the event comprises a possession change event comprising that the insurance customer has acquired a new automobile, and the recommendation for an insurance policy change comprises a recommendation to add a new automobile insurance policy;

the event comprises a marital status change event, and the recommendation for an insurance policy change comprises a recommendation to change a beneficiary of a life insurance policy; and

the event comprises a possession change event, and the recommendation for an insurance policy change comprises a recommendation to include a possession of the possession change event in an inventory of a homeowners insurance policy.

15 . The computer-implemented method of claim 1 , wherein the sending the recommendation for an insurance policy change causes a display device to display:

a name of the insurance customer;

an address of the insurance customer;

a list of insurance policies of the insurance customer;

a recommended insurance policy to add, remove or modify according to the recommendation for an insurance policy change; and/or

an insurance premium change of the recommendation for an insurance policy change.

16 . The computer-implemented method of claim 1 , further comprising:

training, via the one or more processors, the insurance recommendation machine learning algorithm by inputting historical data into the insurance recommendation machine learning algorithm; and

wherein the historical data comprises anonymized insurance policy claims data, and/or data from a ground truth insurance database; and

wherein the historical data comprising anonymized insurance policy claims data, and/or data from a ground truth insurance database comprises: (i) independent variables comprising historical events, and/or (ii) dependent variables comprising additions of new insurance policies, removals of insurance policies, and/or modifications to insurance policies.

17 . The computer-implemented method of claim 16 , wherein the historical events comprise historical:

child changes;

marital status changes;

monetary income changes;

possession changes; and/or

home location changes.

18 . The computer-implemented method of claim 1 , further comprising receiving, via the one or more processors, an indication from a computing device of the insurance customer that the insurance customer has opted into an insurance change recommendation program.

19 . A computer system for recommending a change in insurance coverage, the computer system comprising one or more processors configured to:

receive customer information of an insurance customer;

determine if an insurance change recommendation trigger has occurred by routing the customer information into an insurance recommendation machine learning algorithm; and

upon determination of the insurance change recommendation trigger, send a recommendation for an insurance policy change for the insurance customer.

20 . The computer system of claim 19 , wherein the one or more processors are further configured to send the recommendation for the insurance policy change as an email and/or a text message.

21 . The computer system of claim 19 , wherein the insurance recommendation machine learning algorithm comprises a neural network, and the one or more processors are further configured to:

train the neural network by inputting historical data into the neural network; and

wherein the historical data comprises anonymized insurance policy claims data, and/or data from a ground truth insurance database; and

wherein the historical data comprising anonymized insurance policy claims data, and/or data from a ground truth insurance database comprises: (i) independent variables comprising historical events, and/or (ii) dependent variables comprising additions of new insurance policies, removals of insurance policies, and/or modifications to insurance policies.

22 . A computer device for recommending a change in insurance coverage, 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:

receive customer information of an insurance customer;

determine if an insurance change recommendation trigger has occurred by routing the customer information into an insurance recommendation machine learning algorithm; and

upon determination of the insurance change recommendation trigger, send a recommendation for an insurance policy change for the insurance customer.

23 . The computer device of claim 22 , 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:

determine the recommendation for the insurance policy change by:

determining an optimal death benefit level of an optimal life insurance policy of the insurance customer; and

comparing the optimal death benefit level to a current death benefit level of a current life insurance policy of the insurance customer.

24 . The computer device of claim 22 , wherein:

the insurance recommendation machine learning algorithm is configured to determine the a recommendation for an insurance policy change based upon an insurance customer profile of the insurance customer; and

the insurance recommendation machine learning algorithm is trained based upon historical data comprising: (i) independent variables comprising historical insurance profiles of historical insurance customers, and/or (ii) dependent variables comprising (a) historical insurance claims payout data, and/or (b) insurance policies of the historical insurance profiles.

25 . A computer-implemented method for recommending a change in insurance coverage, the method comprising:

receiving, via one or more processors, customer information of an insurance customer;

determining, via the one or more processors, that an insurance change recommendation trigger has occurred by routing the customer information into an insurance recommendation machine learning and/or artificial intelligence algorithm; and

in response to determining the insurance change recommendation trigger, sending, via the one or more processors, a recommendation for an insurance policy change for the insurance customer.