ASSESSING THE EFFECT OF CHATBOTS ON MANAGING BRAND REPUTATION AMONG COMMERCIAL BANKS IN MALAYSIA

Abstract

Commercial banks in Malaysia are facing increasing competition from non-bank financial institutions, such as mobile money operators and microfinance institutions. To maintain their market share and reputation, banks need to find ways to improve customer service and engagement. Traditional customer support channels may be insufficient to meet the evolving expectations of tech-savvy customers in a digitally driven era. The reliance on manual customer service processes, which can be time-consuming and prone to human error, may lead to delayed response times, inconsistent messaging, and inadequate handling of customer inquiries and complaints. This can negatively impact brand reputation, as customers value prompt and accurate support experiences. The objective of this study was to assess the effect of chatbots on managing brand reputation among commercial banks in Malaysia. This research was based on the communication accommodation theory and the technology acceptance model to explain the relationship between the study variables. A descriptive survey design was adopted. The target population included the 26 commercial banks operating in Malaysia.  A census was conducted on all the 26 commercial banks. The unit of observation was the brand managers and communication managers in each of the commercial banks. Primary data was collected through structured questionnaires. The study reveals a strong positive correlation between the effective integration of chatbots and the management of brand reputation in commercial banks in Malaysia. The regression analysis further confirms the significant impact of chatbots on brand reputation, emphasizing their role in shaping favorable customer perceptions. The study concludes that as banks prioritize the seamless implementation of chatbots, they can enhance customer service experiences, contributing to a positive brand image. To leverage this potential, recommendations include refining chatbot efficiency to address perceived response time, investing in ongoing training, and monitoring interactions to strike a balance between automation and personalized service, thereby ensuring sustained and improved brand reputation in the competitive financial sector.