Telematics as a Transformative Agent for the Zimbabwean Auto Insurance Ecosystem

Zimbabwe has witnessed the evolution of Information Communication Technology (ICT). The vehicle population soared to above 1.2 million hence rendering the Transport and Insurance domains complex. Therefore, there is a need to look at ways that can augment conventional Vehicular Management Information Systems (VMIS) in transforming business processes through Telematics. This paper aims to contextualise the role that telematics can play in transforming the Insurance Ecosystem in Zimbabwe. The main objective was to investigate the integration of Usage-Based Insurance (UBI) with vehicle tracking solutions provided by technology companies like Econet Wireless in Zimbabwe, aiming to align customer billing with individual risk profiles and enhance the synergy between technology and insurance service providers in the motor insurance ecosystem. A triangulation through structured interviews, questionnaires, and literature review, supported by Information Systems Analysis and Design techniques was conducted. The study adopted a case study approach, qualitatively analyzing the complexities of the Telematics insurance ecosystem in Zimbabwe, informed by the TOGAF framework. A case-study approach was applied to derive themes whilst applying within and cross-case analysis. Data was collected using questionnaires, and interviews. The findings of the research clearly show the importance of Telematics in modern-day insurance and the positive relationship between technology and insurance business performance. The study, therefore revealed how UBI can incentivize positive driver behavior, potentially reducing insurance premiums for safe drivers and lowering the incidence of claims against insurance companies. Future work can be done on studying the role of Telematics in combating highway crime and corruption.

Studying Driving Risk Factors using Multi-Source Mobile Computing Data

Traffic congestion can largely be attributed to the issues related with driving behavior,which may cause vehicle crash,stop-and-go traffic due to frequent lane changing behaviors,etc.,and makes the driving behavior research also of significance in the realm of traffic management and demand management.The emergence and subsequent rapid advances with new information and communication technologies(ICT)now offers the capability of collecting high-fidelity and high-resolution trajectory data in a cost-effective manner.In this research,we use a smartphone app to collect data for the purpose of studying driving risk factors.What’s unique about the data in this research is its backend server also estimates traffic speed and volume for each link that the vehicle traverses.In order words,the data collected with build-in GPS modules in the smartphone include not only the vehicle spatial-temporal dimension location,which could be used to correlate the network geography attributes and/or real-time traffic condition,but also the detailed information about the vehicle dynamics including speed,acceleration,and deceleration,whereby a driver’s control and maneuver of a vehicle can be analyzed in detail.Such type of dataset combining both user trajectory and link speed/volume information is rarely seen in prior research,permitting a unique opportunity to link critical traffic congestion factors leading to driving behavior and crash potential.In this paper,the overall research framework used in this research is presented,which mainly includes data collection,data processing,calibration and analysis methodology.A preliminary case study-including data summary statistics and correlation analysis-is also presented.The results of our study will further existing knowledge about driving exposure factors that are closely linked to crash risk,and provide the foundation for advanced forms of Usage Based Insurance.