Methods and systems for smart claim routing and smart claim assignment
A method of assigning and/or routing an auto claim to an appropriate claim handling tier to mitigate delay may include training a machine learning model using historical claim data to determine a severity corresponding to an injury claim, receiving a loss report corresponding to an auto accident, analyzing the loss report using the trained machine learning model to determine the severity of at least one injury corresponding to the loss report, determining an injury segment, and storing the indication of the injury segment in association with the loss report.
1. A computer-implemented method of determining an injury segment based on the severity of the injury, comprising:
training, via a processor, a machine learning model using historical claim data to determine a severity corresponding to an injury claim,
receiving, via a processor, a loss report corresponding to an auto accident,
analyzing the loss report corresponding to the auto accident using the trained machine learning model to determine the severity of at least one injury corresponding to the loss report,
determining, based on the severity of the at least one injury claim corresponding to the loss report, an injury segment, and
storing, via a processor, an indication of the injury segment in association with the loss report.
2. The computer-implemented method of claim 1 , wherein determining, based on the severity of the at least one injury claim corresponding to the loss report, an injury segment includes assigning the loss report to one or more tiers.
3. The computer-implemented method of claim 2 , wherein the one or more tiers are hierarchically related.
4. The computer-implemented method of claim 1 , wherein determining, based on the severity of the at least one injury claim corresponding to the loss report, an injury segment includes assigning the loss report to one or more ordered tiers, to create a routing.
5. The computer-implemented method of claim 4 , wherein the one or more ordered tiers are hierarchically related.
6. The computer-implemented method of claim 1 , wherein the severity is expressed by a numeric severity level.
7. The computer-implemented method of claim 1 , wherein the machine learning model is an artificial neural network.
8. The computer-implemented method of claim 1 , wherein the loss report corresponding to the auto accident includes one or both of (i) a photograph corresponding to the accident, and (ii) a textual description corresponding to the accident.
9. The computer-implemented method of claim 1 , wherein analyzing the loss report corresponding to the auto accident using the trained machine learning model to determine the severity of the at least one injury corresponding to the loss report includes analyzing electronic claim records corresponding to the accident.
10. The computer-implemented method of claim 9 , further comprising:
analyzing vehicle telematics information.
11. A computer system configured to determine an injury segment based on the severity of the injury, the system comprising one or more processors configured to:
train, via the one or more processors, a machine learning model using historical claim data to determine a severity corresponding to an injury claim,
receive, via the one or more processors, a loss report corresponding to an auto accident,
analyze the loss report corresponding to the auto accident using the trained machine learning model to determine the severity of at least one injury corresponding to the loss report,
determine, based on the severity of the at least one injury claim corresponding to the loss report, an injury segment, and
store, via the one or more processors, an indication of the injury segment in association with the loss report.
12. The computer system of claim 11 , further configured to:
assign the loss report to one or more tiers.
13. The computer system of claim 11 , further configured to:
determine a routing and route the injury claim via the routing.
14. The computer system of claim 11 , wherein the machine learning model is an artificial neural network.
15. The computer system of claim 11 , further configured to:
analyze vehicle telematics information.
16. A non-transitory computer readable medium containing program instructions that when executed, cause a computer to:
train, via the one or more processors, a machine learning model using historical claim data to determine a severity corresponding to an injury claim,
receive, via the one or more processors, a loss report corresponding to an auto accident,
analyze the loss report corresponding to the auto accident using the trained machine learning model to determine the severity of at least one injury corresponding to the loss report,
determine, based on the severity of the at least one injury claim corresponding to the loss report, an injury segment, and
store, via the one or more processors, an indication of the injury segment in association with the loss report.
17. The non-transitory computer readable medium of claim 16 , containing further program instructions that when executed, cause a computer to:
assign the loss report to one or more tiers.
18. The non-transitory computer readable medium of claim 16 , containing further program instructions that when executed, cause a computer to:
determine a routing and route the injury claim via the routing.
19. The non-transitory computer readable medium of claim 16 , containing further program instructions that when executed, cause a computer to:
analyze vehicle telematics information.
20. The non-transitory computer readable medium of claim 16 , wherein the machine learning model is an artificial neural network.