In an earlier blog, we talked about how computable contract technology can facilitate the management of insurance claims and thereby deal with insurance "sludge". In this blog, we discuss the prospects for applying this technology more broadly - from the management of individual insurance claims to the management of entire insurance portfolios - thereby eliminating redundant insurance while closing gaps in coverage.
We often think of insurance policies as being partitioned into distinct areas - home insurance, auto insurance, health insurance, travel insurance, and so forth; and we frequently buy different policies to provide coverage in these different areas. In reality, things are more complicated, with policies in different areas often providing overlapping coverage. For example, rental car damage may be covered by a policy purchased from a rental car company, a personal auto insurance policy, a credit card, a travel insurance policy, and even, in some cases, a home insurance policy. If we are unaware of these overlaps, we can end up paying more for insurance than we need; what's worse, there can be gaps between policies of which we are unaware.
Insurance portfolio management is the process of managing multiple, potentially overlapping insurance policies, with an eye to minimizing insurance costs while ensuring adequate coverage. By studying the contracts associated with insurance policies, we can avoid overlaps and ensure there are no gaps in coverage. For example, while renting a car, we may realize that we do not need to purchase collision insurance from Hertz because we are already covered if we use our Visa credit card. At the same time, we may realize that we need to purchase additional insurance for travel in Ireland, since our credit card insurance does not apply there.
The problem is that insurance portfolio management is not easy. Insurees usually do not have the time or patience to compare policies from multiple insurance providers; and, even if they have the time, they often do not have the legal background needed to understand the complex legal wording of the lengthy, 100-page contracts associated with those policies.
The good news is that, with advances in information technology, it is now possible to implement computer systems to help with this process. A computer-based insurance portfolio dashboard can provide its user with an overview of his current policies and needs, with an analysis of overlap and gaps. And an automated insurance portfolio advisor can help a user compare available insurance products and craft a portfolio of insurance products that meets his needs at minimal cost.
The key to building such systems is to formalize insurance policies as computable contracts. A computable contract is one that provides a computable specification for the terms and conditions of the contract.
One use of computable contracts is automated claims analysis. Given a specific computable contract, it is possible for a computer system to determine compliance of any specific situation with contract's terms and conditions in a purely mechanical way - without the help of human experts and without further clarification from the contracting parties.
As an example, consider a user with an insurance policy that covers his immediate family's expenses at US hospitals for injuries resulting from everyday activities. An automated claims analysis system would be able to determine that the policy covers his daughter's treatment at Johns Hopkins Hospital for the sprained ankle she sustained while dancing. At the same time, it would be able to determine that his daughter is not covered for treatment at a hospital in Europe. It could determine that she is not covered if she sprained her ankle while skydiving. And it could determine that his niece's recent hospitalization is not covered since she is not an immediate family member.
More generally, computable contracts enable automated insurance portfolio analysis and insurance portfolio design. Computable contracts allow computer systems to analyze multiple-policy portfolios to assess coverage over multiple hypothetical scenarios. And computable contracts enable systems to design or configure multiple-policy portfolios that cover the user's needs.
As a very simple example of this, consider an individual planning a family trip to the UK and Ireland. The individual could purchase an insurance policy for his entire family for all activities anywhere in the world. However, that is likely to be expensive. He might do better by creating an insurance portfolio tailored to his needs, e.g. combining his pre-existing personal travel insurance policy, the auto collision coverage supplied by his credit card, a new policy to cover his family's hospital expenses in Europe, and a new policy from his rental car company for travel in Ireland. This combination of policies is more complicated but is likely to be less expensive than a simpler comprehensive policy.
Automated Insurance Portfolio Management can provide benefit for all parties in the insurance ecosystem. It can benefit customers by analyzing their overall coverage and synthesizing portfolios of insurance products that meets their needs with minimal cost. It can help insurance companies increase transparency, decrease meritless claims, detect upsell opportunities, and craft customized insurance products. And it can help regulators support and enforce insurance regulations.
Citation: Genesereth, Michael: "Insurance Portfolio Management", Complaw Corner, Codex: The Stanford Center for Legal Informatics, 2022, http://complaw.stanford.edu/blog/ipm.html.