US 11,657,460 B2
Using historical data for subrogation on a distributed ledger
William J. Leise, Normal, IL (US); Douglas A. Graff, Mountain View, MO (US); Anthony McCoy, Normal, IL (US); Jaime Skaggs, Chenoa, IL (US); Shawn M. Call, Bloomington, IL (US); Stacie A. McCullough, Bloomington, IL (US); Wendy H. Clayton, Franklin, TN (US); Melinda Teresa Magerkurth, Utica, IL (US); Kim E. Flesher, Normal, IL (US); and Travis Charles Runge, 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 Aug. 19, 2022, as Appl. No. 17/892,040.
Application 17/892,040 is a continuation of application No. 16/999,260, filed on Aug. 21, 2020, granted, now 11,475,527.
Application 16/999,260 is a continuation of application No. 15/957,438, filed on Apr. 19, 2018, granted, now 11,386,498.
Claims priority of provisional application 62/609,644, filed on Dec. 22, 2017.
Claims priority of provisional application 62/555,358, filed on Sep. 7, 2017.
Claims priority of provisional application 62/554,907, filed on Sep. 6, 2017.
Claims priority of provisional application 62/555,030, filed on Sep. 6, 2017.
Prior Publication US 2022/0405857 A1, Dec. 22, 2022
Int. Cl. G06Q 40/08 (2012.01); G06F 16/27 (2019.01); G06N 20/00 (2019.01)
CPC G06Q 40/08 (2013.01) [G06F 16/27 (2019.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method of handling an insurance claim via a shared ledger, the method comprising:
receiving, at one or more processors, historical sensor data associated with a past vehicle collision;
inputting, at the one or more processors, the historical sensor data into an algorithm, the algorithm being a machine learning algorithm that is trained by the historical sensor data to determine a percentage of fault for human drivers or self-driving vehicles;
receiving, at the one or more processors, current sensor data associated with a vehicle collision;
inputting, at the one or more processors, the current sensor data into the machine learning algorithm to determine a percentage of fault of the current vehicle collision for a human driver or a self-driving vehicle;
adding, at the one or more processors, a block to a blockchain with an indication of the determined percentage of fault determined by the trained machine learning algorithm; and
automatically processing and/or adjusting, at the one or more processors, an insurance claim via the blockchain.