Real-World Examples

This week, I began the research phase of my final product planning process. In order to begin this process, I wanted to extend my scope beyond the reach of simple insurance policies and processes. My mentor astutely pointed out that risk management and construction of feasible business models is not unique to the insurance industry. From banking in collateralized debt obligations to mortgage backed securities, many industries take advantage of the scale of collectivized risk in order to statistically apply the law of large numbers. Thus, they can create a relatively accurate business model that ensures profits for the provider while maintaining the lowest rates possible even though there is a level of risk involved in the service. In the case of banking and finance, this occurs in investments and debt/loans, where in insurance, this occurs in policies, claims, premiums, and incidents. Ultimately, this decision is a relatively pivotal point in my final product research that I need to decide in order to design my final product. However, there is also the possibility of creating a more generalized AI that specializes in risk management that extends to all of these potential industries. As for my plan for next week, I plan to conduct additional research into this risk management and the math behind it in order to reinforce my technical knowledge in this field for my final product. Additionally, I plan to research existing implementations of this AI technology using companies like Lemonade Insurance in order to serve as an example for my future model for my AI and serve as a practical example of a competitive AI in the business world. Ultimately, I have a more descriptive roadmap for my product and I am looking forward to carrying it out in the coming weeks with the help and advice of my mentor and other sources.