Platform for autonomous risk assessment and quantification for cyber insurance policies
A system for autonomous risk assessment and quantification for insurance policies for computer and information technology related risks, including but not limited to losses due to system availability, cloud computing failures, current and past data breaches, and data integrity issues. The system will use a variety of current risk information to assess the likelihood of operational interruption or loss due to both accidental issues and malicious activity. Based on these assessments, the system will be able to autonomously issue policies, adjust premium pricing, process claims, and seek re-insurance opportunities with a minimum of human input.
1. A system for autonomous risk assessment and quantification for insurance policies for operational interruption and losses associated with computer and technology related risks, comprising:
a network-connected server comprising a memory and a processor;
a deep web extraction engine comprising a first plurality of programming instructions stored in the memory and operable on the processor, wherein the first plurality of programming instructions, when operating on the processor, cause the network-connected server to gather data about a plurality of potential risks related to use to computer and information technology;
a cyber risk analysis engine comprising a second plurality of programming instructions stored in the memory and operable on the processor, wherein the second plurality of programming instructions, when operating on the processor, cause the network-connected server to:
analyze the likelihood of operational interruption or loss from a plurality of computer and information technology related risks by utilizing machine learning to predict risk from both accidental events and deliberate malicious activity;
perform a plurality of predictive simulations using the analyzed data;
normalize the results of the analysis and predictive simulations for use in risk modeling; and
apply a plurality of predictive algorithms to the normalized data to produce a hazard model and a multi-peril model; and
an interactive display comprising a fourth plurality of programming instructions stored in the memory and operable on the processor, wherein the fourth plurality of programming instructions,
when operating on the processor, cause the network-connected server to:
display the hazard model for viewing by a human user;
display the multi-risk model for viewing by a human user; and
update the displayed models during a viewing session by a user, to reflect the user's actions and interactions in real-time.
2. The system of claim 1 , wherein at least a portion of the gathered data comprises client asset worth amounts.
3. The system of claim 1 , wherein at least a portion of the gathered data comprises expert opinion information.
4. The system of claim 1 , wherein at least one of the predictive simulation algorithms comprises a historical simulation.
5. The system of claim 1 , wherein at least one of the predictive simulation algorithms comprises a Monte Carlo simulation.
6. The system of claim 1 , wherein at least one of the predictive analytics algorithms employs information theory statistical calculations.
7. The system of claim 1 , wherein at least one of the risk assessment factors is environmental condition profile at one or more sites of client business operation.
8. The system of claim 1 , wherein at least one of the risk assessment factors is geo-political conditions at one or more sites of client business operation.
9. A method for autonomous risk assessment and quantification, comprising the steps of:
(a) gathering a variety of data from about a plurality of potential risks related to use to computer and information technology;
(b) analyzing the likelihood of operational interruption or loss from a plurality of computer and information technology related risks by utilizing machine learning to predict risk from both accidental events and deliberate malicious activity;
(c) performing a plurality of predictive simulations using the analyzed data;
(d) normalizing the results of the analysis and predictive simulations for use in risk modeling;
(e) applying a plurality of predictive algorithms to the normalized data to produce a hazard model and a multi-peril model;
(f) displaying the hazard model for viewing by a human user;
(g) displaying the multi-risk model for viewing by a human user; and
(h) updating the displayed models during a viewing session by a user, to reflect the user's actions and interactions in real-time.
10. The method of claim 9 , wherein at least a portion of the gathered data comprises client asset worth amounts.
11. The method of claim 9 , wherein at least a portion of the gathered data comprises expert opinion information.
12. The method of claim 9 , wherein at least one of the predictive simulation algorithms comprises a historical simulation.
13. The method of claim 9 , wherein at least one of the predictive simulation algorithms comprises a Monte Carlo simulation.
14. The method of claim 9 , wherein at least one of the predictive analytics algorithms employs information theory statistical calculations.
15. The method of claim 9 , wherein at least one of the risk assessment factors is environmental condition profile at one or more sites of client business operation.
16. The method of claim 9 , wherein at least one of the risk assessment factors is geo-political conditions at one or more sites of client business operation.