US 12,217,313 B2
Systems and methods for generating on-demand insurance policies
Ryan Michael Gross, Normal, IL (US); Jody Ann Thoele, Bloomington, IL (US); Joseph Robert Brannan, Bloomington, IL (US); and Eric R. Moore, Heyworth, IL (US)
Assigned to State Farm Mutual Automobile Insurance Company, Bloomington, IL (US)
Filed by State Farm Mutual Automobile Insurance Company, Bloomington, IL (US)
Filed on Feb. 23, 2023, as Appl. No. 18/173,421.
Application 18/173,421 is a continuation of application No. 17/127,410, filed on Dec. 18, 2020, granted, now 11,599,951.
Claims priority of provisional application 62/984,664, filed on Mar. 3, 2020.
Claims priority of provisional application 62/960,395, filed on Jan. 13, 2020.
Prior Publication US 2023/0206342 A1, Jun. 29, 2023
Int. Cl. G06Q 40/08 (2012.01); G06F 3/0482 (2013.01); G06Q 10/10 (2023.01); G06Q 50/14 (2012.01); G06Q 50/26 (2012.01); G06Q 50/40 (2024.01); G09B 19/00 (2006.01); G06N 20/00 (2019.01); G06Q 30/0645 (2023.01)
CPC G06Q 40/08 (2013.01) [G06F 3/0482 (2013.01); G06Q 10/10 (2013.01); G06Q 50/14 (2013.01); G06Q 50/26 (2013.01); G06Q 50/40 (2024.01); G09B 19/00 (2013.01); G06N 20/00 (2019.01); G06Q 30/0645 (2013.01)] 20 Claims
OG exemplary drawing
 
1. An on-demand insurance (ODI) server comprising at least one processor coupled to a memory device and a communication interface, the at least one processor operable to execute a risk assessment module and a pricing module, the at least one processor configured to:
generate a user profile associated with a user by processing telematics data received using the communication interface from a user computing device associated with the user;
determine, based upon the user profile, a plurality of transportation modes available for a trip to be taken by the user;
receive, using the communication interface, real-time contextual data associated with the trip and the user profile;
train one or more machine learning tools using the real-time contextual data;
generate, by executing the risk assessment module and based upon at least the real-time contextual data and the user profile, at least one risk score, each associated with use of one of the plurality of transportation modes;
generate, using the at least one risk score, a dynamic pricing model associated with the plurality of transportation modes and at least one travel route to be taken by the user during the trip;
apply, by executing the pricing module, the trained one or more machine learning tools to the dynamic pricing model to generate an insurance offering;
generate, by executing the pricing module and based upon the application of the trained the one or more machine learning tools to the dynamic pricing model, an insurance offering associated with the use of at least one of the plurality of transportation modes; and
transmit, using the communication interface, the insurance offering in real time to the user computing device for purchase by the user.