Methods and systems for insurance investment product decision modeling

• US 9,928,552 B1
• Filed: 03/13/2009
• Issued: 03/27/2018
• Est. Priority Date: 03/13/2009
• Status: Active Grant

• Current Assignee: New York Life Insurance Company
• Original Assignee: New York Life Insurance Company
• Inventors: Berlin, Scott L., Gordon, Michael J., Richter, Michelle D., Bak, Aryeh J.
• Primary Examiner(s): Liu, I Jung
• Application Number:
  US12/403,474
• Time in Patent Office: 3,301 Days
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

Methods and systems for insurance investment product decision modeling are disclosed. The methods and systems provide means for determining an objectively appropriate insurance investment product or funding level for a customer including inputting a set of customer data including at least certain customer criteria such as age, gender and policy face amount, selecting insurance products for comparison, calculating an expected investment in each of the selected insurance products or funding levels, calculating an expected benefit from each of the selected insurance products or funding levels using at least an economic model, calculating a value for each of the types of insurance based on the expected investment and respective expected benefits and recommending an insurance product or funding level based at least in part on a comparison of the value or net gain for the selected insurance products or funding levels being compared.

Claims

1. A computerized method for linking a user device to websites based on a determination of objectively appropriate insurance investment products for a customer, the method comprising:

electronically receiving a set of customer data by a processing device invoking the set of customer data from one or more databases over a communications network, the set of customer data including at least age, gender, policy face amount and an investment risk tolerance which indicates propensity of the customer to invest in equities versus fixed income products;

selecting, via the processing device, at least two insurance products for comparison based on the set of customer data;

calculating, by the processing device, an expected investment in each of the selected insurance products, the expected investment including a sum of premiums to be paid for a given duration multiplied by a mortality factor;

calculating, by the processing device, an expected benefit from a first insurance product and from a second insurance product, each of the expected benefits including a sum of a net present value of an insurance benefit and investment return multiplied by the mortality factor, the investment return calculated using at least an economic model, wherein the economic model comprises a stochastic economic scenario generator that simulates multiple different market return scenarios for the set of customer data;

calculating, by the processing device, a value for each of the first and the second insurance products based on the expected investment and respective expected benefit; and

generating, via the processing device, recommendation data for an insurance product, the recommendation generated based at least in part on a comparison of the value for the first insurance product and the value of the second insurance product, a comparison of results from the economic scenario generator for the set of customer data, and a highest expected return from among the first and second insurance products compared subject to a determination that a ratio of an excess gain divided by standard deviation is in a specified range based on the investment risk tolerance, the excess gain including gains in the investment returns in excess of a required return specified by the customer;

selecting, via the processing device, one of the first insurance product and the second insurance product based on the recommendation data; and

providing, via the processing device, links configured to direct a user device of the customer to websites based on the recommendation data, the websites including electronic application data for the selected one of the first insurance product and the second insurance product.

2. The method of claim 1, comprising receiving more than one set of customer data.

3. The method of claim 1, wherein the investment risk tolerance is specified by the customer.

4. The method of claim 1, wherein the selection of insurance product types is based at least in part on the investment risk tolerance assigned to the customer.

5. The method of claim 1, wherein the two insurance products are variations of a single type of insurance product.

6. The method of claim 1, comprising selecting a variable universal life insurance product.

7. The method of claim 1, comprising selecting a term life insurance product.

8. The method of claim 1, wherein calculating an expected investment in the selected insurance product comprises calculating expected premiums to be paid based at least in part on a mortality assumption corresponding to the set of customer data.

9. The method of claim 1, wherein calculating an expected investment in the selected insurance product comprises calculating expected premiums to be paid based at least in part on characteristics of the selected insurance product.

10. The method of claim 1, wherein calculating an expected benefit from a first type of insurance product or a second type of insurance product comprises calculating an expected benefit based at least in part on mortality weighted death benefits and mortality weighted distributions.

11. The method of claim 1, wherein calculating an expected benefit from a first type of insurance product or a second type of insurance product comprises calculating an expected benefit based at least in part on a market return scenario.

12. The method of claim 1, wherein calculating an expected benefit from a first type of insurance product or a second type of insurance product comprises calculating an expected benefit based at least in part on mortality weighted death benefits, mortality weighted withdrawals and loans from the policy to generate income after age 65, gradually reducing a value of a given insurance product until the policy is fully consumed at age 100.

14. The method of claim 1, comprising presenting a ranked set of risk classes, each of the risk classes representing a predefined ratio of equity and fixed income investments, wherein the investment risk tolerance is input as a selection of one of the risk classes.

15. The method of claim 14, wherein the expected investment for each of the insurance products is calculated assuming an allocation of an investable amount of customer contributions between equity and fixed income investments in proportion to the predefined ratio of the selected investment risk class and wherein the value for each of the first and second insurance product is a sum of a net present value of the expected investment and a net present value of the expected benefit.

13. A system for linking a user device to websites based on a determination of objectively appropriate insurance investment products for a customer, the system comprising:

a computer effective to receive one or more sets of customer data by invoking the one or more sets of customer data from one or more databases, the one or more sets of customer data including for each customer at least age, gender, policy face amount and an investment risk tolerance which indicates propensity of the customer to invest in equities versus fixed income products;

the one or more databases for storing the customer data set, insurance product data and economic data;

the computer including a processor, the processor configured to;

calculate an expected investment in each of two insurance products selected for comparison based on the set of customer data wherein the expected investment includes a sum of premiums to be paid for a given duration multiplied by a mortality factor, an expected benefit from each of the first insurance product and the second insurance product where each of the expected benefits includes a sum of a net present value of an insurance benefit and investment return multiplied by the mortality factor and where the investment return is calculated using at least an economic model, and a value for each of the first and the second insurance products based on the expected investment and respective expected benefit, wherein the economic model comprises a stochastic economic scenario generator that simulates multiple different market return scenarios for the set of customer data;

generate a recommendation for an insurance product based at least in part on a comparison of the value for the first insurance product and the value of the second insurance product, a comparison of results from the economic scenario generator for the set of customer data, and a highest expected return from among the first and second insurance products compared subject to a determination that a ratio of an excess gain divided by standard deviation is in a specified range based on the investment risk tolerance, the excess gain including gains in the investment returns in excess of a required return specified by the customer;

select one of the first insurance product and the second insurance product based on the recommendation data; and

provide links configured to direct a user device of the customer to websites based on the recommendation data, the websites including electronic application data for the selected one of the first insurance product and the second insurance product.

16. A computerized method for linking a user device to websites based on a determination of objectively appropriate insurance investment product for a customer, the method comprising:

receiving as input in electronic form by a processing device invoking a set of customer data from one or more databases over a communications network, the set of customer data including at least age, gender, a policy face amount and a selection of an investment risk tolerance class of a plurality of ranked investment risk tolerance classes, wherein each of the investment risk tolerance classes indicate a relative propensity for the customer to invest in equities versus fixed income products, and wherein each of the investment risk tolerance classes represents a predefined ratio of equity to fixed income investments,

selecting, via the processing device, at least two insurance products for comparison based on the set of customer data, wherein at least a first of the at least two insurance products is a variable universal life product and at least one a second of the at least two insurance products is a term life insurance product;

calculating, by the processing device, an expected investment in each of the selected insurance products, the expected investment including a sum of premiums to be paid for a given duration multiplied by a mortality factor and wherein the expected investment for each of the insurance products is calculated assuming an allocation of an investable amount of customer contributions between equity and fixed income investments in proportion to the predefined ratio of the selected investment risk tolerance class;

calculating, by the processing device, an expected benefit from the first insurance product and from the second insurance product each of the expected benefits including a sum of a net present value of an insurance benefit and investment return multiplied by the mortality factor, the investment return calculated using at least an economic model, wherein the economic model comprises a stochastic economic scenario generator that simulates multiple different market return scenarios for the set of customer data;

calculating, by the processing device, a value for each of the first and the second insurance products based on the expected investment and respective expected benefit, wherein the value for each of the first and second insurance product is a sum of a net present value of the expected investment and a net present value of the expected benefit; and

generating, via the processing device, recommendation data for an insurance product, the recommendation generated based at least in part on a comparison of the value for the first insurance product and the value of the second insurance product, a comparison of results from the economic scenario generator for the set of customer data, and a highest expected return from among the first and second insurance products compared subject to a determination that a ratio of an excess gain divided by standard deviation is in a specified range based on the selected investment risk tolerance class, the excess gain including gains in the investment returns in excess of a required return specified by the customer;

selecting, via the processing device, one of the first insurance product and the second insurance product based on the recommendation data; and

providing, via the processing device, links configured to direct a user device of the customer to websites based on the recommendation data, the websites including electronic application data for the selected one of the first insurance product and the second insurance product.

17. The method of claim 16, wherein the expected benefit is calculated based at least in part on mortality weighted death benefits, mortality weighted withdrawals and loans from the policy to generate income after age 65, while gradually reducing a value of a given insurance product until the policy is fully consumed at age 100.