Thoughtful workforce transitions in higher education
One way higher education institutions are responding to financial challenges caused by the COVID-19 pandemic is to rethink their staffing models and reduce faculty and staff costs.
In June–July 2012, together with a commercial insurance company active in Sub-Saharan Africa, Milliman consultants developed a set of underwriting guidelines for a hospital cash microinsurance product in Tanzania. The client currently offers a daily income replacement policy for its customers who undergo hospital stays. The policy is guaranteed renewable, although the carrier has the option of increasing the premium in renewable years based on claim history. The company had been using only basic underwriting requirements and was experiencing problems with adverse selection, because individuals were purchasing policies when they anticipated a need for hospitalization and then letting them lapse when they no longer needed care.
The challenge was to develop a set of underwriting guidelines that the client could use as part of the sales process, which would include questions that would determine whether the applicant had medical conditions relevant to predicting future inpatient hospital utilization. In addition, the client requested advice on how to design the rating structure, that is, how to determine whether to offer an applicant unrestricted coverage, decline coverage, or offer coverage with a 12-month exclusionary period for specific conditions.
There were two complications in developing applicant questions. First, the language in the questions had to be simple, because at the point of purchase, there are no agents or brokers to help customers with their application. Second, Tanzanian customers purchase this coverage in a cellular phone store—a nonconfidential environment. That ruled out sensitive personal questions about applicants' medical conditions.
To tackle the underwriting issues, we used the Milliman Medical Underwriting Guidelines (MUGs) database, making adjustments for the fact that the MUGs data is U.S.-specific. Among other things, we added in conditions (such as malaria) that are common in Tanzania but not in the U.S. In addition, the MUGs deal with total medical costs, whereas the Tanzanian insurance product pays a lump sum in cash on a per diem basis when there is a hospitalization. This meant that our analysis needed to focus not on estimating the total claim costs but on estimating the average inpatient length of stay for each condition.
A further challenge was that there was no Tanzania-specific data for us to work with. We augmented our analysis by researching a substantial number of sources and receiving input from a clinician with experience in Sub-Saharan African markets.
Our client is now in a position to gather direct data as it grows its business in the Tanzanian market. We strongly advised monitoring claims and loss ratios over time, and we expect that the information may inform adjustments in the insurance product, in terms of adding or subtracting conditions and fine-tuning the language in applicant questions.
In addition, our client is better positioned to apply the new data to its rate structures. This should produce revenues in the future that lessen the company’s risk and set the stage for higher, and more predictable, profits.
Besides the author of this report, Mary van der Heijde, Sudhanshu Bansal, and Jill Van Den Bos also participated in this project.