Can Artificial Intelligence (AI) Manage Behavioural Biases Among Financial Planners?

Introduction

Traditional economic theories assume that individuals act rationally, and the role of emotions or psychological issues is kept at bay in financial decision-making situations. In this decision-making process, the economic agents consider all the available information, process the collected information judiciously, and arrive at optimal financial decisions. The optimal decisions lead to the most desired outcome and help attain the financial goals of the individuals. However, behavioural finance and neuroeconomics research reveals that individuals are not entirely rational and susceptible to various biases. There are constraints in the decision-making process leading to biased decisions. The decision-making process occurs in the human brain through a mutual communication between the prefrontal cortex and hippocampus with neural connectivity (Weilbächer & Gluth, 2016; Moghadam, Khodadad & Khazaeinezhad, 2019). Wang (2008) suggests that the prefrontal cortex estimates the required information for the decision-making process and then obtain this information from the hippocampus. However, along with the cognition process for decision making, the hippocampus channels emotional experience during this procedure. Consequently, the decision-making process is susceptible to biases. In his ground-breaking research, Simon (1967) contends that the system will be incomplete without taking emotions and situational constraints into the decision-making process producing sub-optimal decisions. Financial planners who regularly take financial decisions for their clients also exert biases in their decision-making process (Akhtar & Das, 2020). Baker et al. (2017) assert that financial planners’ psychological biases can lead to flawed economic decisions. Understanding personality traits and effective behaviour management techniques positively influence financial decisions, but unfortunately, this is not effectively explored (Pompian, 2012).