  The uptake of health insurance has been poor in Nigeria, a significant step
to improving this includes improved awareness, access to information and tools
to support decision making. Artificial intelligence (AI) based recommender
systems have gained popularity in helping individuals find movies, books,
music, and different types of products on the internet including diverse
applications in healthcare. The content-based methodology (item-based approach)
was employed in the recommender system. We applied both the K-Nearest Neighbor
(KNN) and Cosine similarity algorithm. We chose the Cosine similarity as our
chosen algorithm after several evaluations based of their outcomes in
comparison with domain knowledge. The recommender system takes into
consideration the choices entered by the user, filters the health management
organization (HMO) data by location and chosen prices. It then recommends the
top 3 HMOs with closest similarity in services offered. A recommendation tool
to help people find and select the best health insurance plan for them is
useful in reducing the barrier of accessing health insurance. Users are
empowered to easily find appropriate information on available plans, reduce
cognitive overload in dealing with over 100 options available in the market and
easily see what matches their financial capacity.
