Geo-Banking Data

Information flow (both large and small), in dynamic interactions with local geographic conditions, can leave a strong imprint on the way customers access reliable financial information, eventually improving their daily lifestyles. Such a context is important in geographically and socio-economically challenged economies, such as Africa. The challenges are acute when the information flow is very large, as the increasing availability of big data in these economies requires resilient and need-based adaptive innovation solutions. In this paper, we propose a location-aware recommender algorithm called Geo-Banking which uses a Geographical Information System (GIS) approach. We created a series of questionnaires and distributed them using Google Forms to a purposively sampled group of respondents, totaling thirty-two, to assess our suggested Geo-Insurance technique. We verified the respondents' background information, including gender. Ten (10) men, or 31.25% of the participants, and twenty-two (22) women, or 68.75%. Before the assessment, the research participants in Table I were acquainted with the Geo-Insurance App and had utilized it. The technology was also made available to the participants throughout the pilot phase so they could use it directly.