An Assessment of the Adoption of Robotic Process Automation in Kenyan Insurance Companies

Abstract

Among the technologies perceived as providing great opportunities to scale and transform traditional work paradigms in the digital age is Robotic Process Automation (RPA). Iinsurers are looking at ways of increasing their operational digital footprint and optimizing their business process automation. Insurers handle a high volume of processes manually which creates delays and affects customer satisfaction and profitability. Insurance can take advantage of RPA to handle the high volume, structured and repetitive processes. Although RPA provides numerous benefits, it has not yet achieved conventional adoption. Organizations are still gathering information and creating a business case for RPA implementation. The adoption of RPA has not progressed hence the need to investigate the factors relevant to insurers when making technology adoption decisions. As RPA-related innovations are one of the recent disruptive forces, there is interest for businesses to understand what drives such decisions to facilitate the uptake of RPA technology. The study sought to assess the adoption of RPA in insurance companies in Kenya, identify the opportunities for RPA adoption, establish the factors to be taken into account to stimulate the uptake of RPA, and validate a suitable model for RPA adoption. The Technological, Organizational, and Environmental (TOE) framework was used as the conceptual parameter. A descriptive survey was used where quantitative data was collected using questionnaires. Data was collected from twenty-six life insurance companies licensed by Insurance Regulatory Authority (IRA) and statistically analyzed using SPSS. Nearly all the respondents agreed they perform manual and repetitive tasks in their daily operations. The technical capabilities of the RPA are seen to improve operational efficiency and improve the quality of work produced. The study revealed that many insurers in Kenya are still at the stage of deciding to adopt RPA. This research found clear links between the three elements of the TOE framework and RPA adoption decisions. The model analysis validated the relationship between Technological factors, Organization Factors, and Environmental factors significantly influencing the respondent’s intention to adopt RPA. The findings show that relative advantage, compatibility, top management support, competitive pressure, and legal & regulatory requirements are positively related to the intention to adopt RPA with a negative relationship established between perceived costs and intention to adopt RPA.