Insurance recommendation computer system and method

• US 20150199765A1
• Filed: 02/16/2015
• Published: 07/16/2015
• Est. Priority Date: 02/16/2015
• Status: Abandoned Application

• Current Assignee: Simon John Noonan
• Original Assignee: Simon John Noonan
• Inventors: Noonan, Simon John
• Application Number:
  US14/623,267
• Publication Number:
  US 20150199765A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

An insurance recommendation computer system and method to create insurance recommendations for individuals taking into account the circumstances of their household. Data inputs are gathered from the user which allow the user to generate recommendations that enhance their ability to understand and buy insurance coverage appropriate to their needs. Each recommendation generated falls into one of 277 categories. It has been implemented using C# code on a computer running Microsoft Windows and for typical household the generation or regeneration of ideas using the latest data takes 1 second or thereabouts. The system and method is designed to get the user up and running quickly by pre-populating almost all data elements except the user'"'"'s email and password, and encourages the user to iterate through inputting data and updating the recommendations repeatedly by providing more information and illustration in the recommendations than in the questions around data inputs.

Claims

1. An insurance recommendation computer system and method consisting of computer hardware and software that provides a user interface for a user to enter information about their household that is relevant for the development of insurance recommendations for that household, a data structure to validate and store the information, and a method for developing insurance recommendations and presenting them to the user.

2. The method of claim 1 further comprising almost completely prepopulating data for each household with plausible data, so for example if a user creates an account (email+password) and then logs in, they are able to generate an initial set of recommendations without entering any more data.

3. The method of claim 1 further comprising using default data selected to create recommendations that tend to highlight issues frequently faced by households.

4. The method of claim 1 further comprising performing most data validation when the user enters the data, but performing certain validations when the user creates the recommendations.

5. The method of claim 1 further comprising correcting problematic data to something that is plausible when creating recommendations and alerting the user to what has been done.

6. The method of claim 1 further comprising employing data validation with a focus on someone who likes to plan.

7. The method of claim 1 further comprising anticipating that policy expiration dates are likely to be incorrect when recommendations are generated and both rolling them forward and alerting the user to the implications of an expired policy in developing recommendations.

8. The method of claim 1 further comprising combining multiple policies insuring one residence (homeowners, condo, renters insurance) into one virtual policy where appropriate.

9. The method of claim 1 further comprising removing the constraints on the number of items that can be added to a policy that exist with most insurers.

10. The method of claim 1 further comprising protecting users against mistakenly deleting data that they have entered, prohibiting cascading deletes.

11. The method of claim 1 further comprising focusing on dates to help people get better organized.

12. The method of claim 1 further comprising producing indicators showing whether implementation of the recommendation will increase or decrease premium, or leave it more or less unchanged.

13. The method of claim 1 further comprising not optimizing premium at too granular a level.

14. The method of claim 1 further comprising showing the user an estimate of annual insurance premiums with an appropriate caveat about endorsement activity distorting the calculation.

15. The method of claim 1 further comprising using “

find the weakest link”

logic in auto insurance limits.

16. The method of claim 1 further comprising allowing the user to select household risk tolerance.

17. The method of claim 1 further comprising using for each of the lines of non-life insurance where a policy is present, an array of standard deductibles plus the one they have to compute the maximum financially feasible deductible.

18. The method of claim 1 further comprising that when simulating liability losses for a situation protected by an insurance policy but not covered by umbrella insurance, developing a loss that exceeds the combination of the actual underlying insurance policy limit plus a hypothetical low limit umbrella policy.

19. The method of claim 1 further comprising selectively departing from what is actually available in the marketplace to better illustrate the recommendations.

20. The method of claim 1 further comprising systematically searching for things that can go wrong with insurance.

21. The method of claim 1 further comprising encouraging users to take a household view of risk, not an insurance product by insurance product view of risk.

22. The method of claim 1 further comprising describing the financial implications of a loss at a more granular level than that implied by 277 recommendation categories.

23. The method of claim 1 further comprising providing more information in the recommendations than in the questions for data inputs, encouraging the user to iterate through the system and method, rather than trying to answer all the questions perfectly and then running the recommendations once.