The Knowledge Gap in Workplace Retirement Investing and the Role of Professional Advisors

The dramatic shift from traditional pension plans to participant-directed 401(k) plans has increased the obligation of individual investors to take responsibility for their own retirement planning. With this shift comes increasing evidence that investors are making poor investment decisions. This Article seeks to uncover the reasons for poor investment decisions. We use a simulated retirement investing task and a new financial literacy index to evaluate the role of financial literacy in retirement investment decisionmaking in a group of nonexpert participants. Our results suggest that individual employees often lack the skills necessary to support the current model of participant-directed investing. We show that less knowledgeable participants allocate too little money to equity, engage in naive diversification, fail to identify dominated funds, and are inattentive to fees. Over the duration of a retirement account, these mistakes can cost investors hundreds of thousands of dollars. We then explore the capacity of professional advisors to mitigate this problem. Using the same study with a group of professional advisors, we document a predictable but nonetheless dramatic knowledge gap between professionals and ordinary investors. The professional advisors were far more financially literate and made better choices among investment alternatives. Our results highlight the potential value of professional advice in mitigating the effects of financial illiteracy in retirement planning. Our findings suggest that, in weighing the costs of heightened regulation against the value of reducing possible conflicts of interest, regulators need to be sensitive to the knowledge gap

Artificial Intelligence for the Financial Services Industry: What Challenges Organizations to Succeed?

As a research field, artificial intelligence (AI) exists for several years. More recently, technological breakthroughs, coupled with the fast availability of data, have brought AI closer to commercial use. Internet giants such as Google, Amazon, Apple or Facebook invest significantly into AI, thereby underlining its relevance for business models worldwide. For the highly data driven finance industry, AI is of intensive interest within pilot projects, still, few AI applications have been implemented so far. This study analyzes drivers and inhibitors of a successful AI application in the finance industry based on panel data comprising 22 semi-structured interviews with experts in AI in finance. As theoretical lens, we structured our results using the TOE framework. Guidelines for applying AI successfully reveal AI-specific role models and process competencies as crucial, before trained algorithms will have reached a quality level on which AI applications will operate without human intervention and moral concerns

Uncertainty and risk: politics and analysis

In environmental and sustainable development policy issues, and in infrastructural megaprojects and issues of innovative medical technologies as well, public authorities face emergent complexity, high value diversity, difficult-to-structure problems, high decision stakes, high uncertainty, and thus risk. In practice, it is believed, this often leads to crises, controversies, deadlocks, and policy fiascoes. Decision-makers are said to face a crisis in coping with uncertainty. Both the cognitive structure of uncertainty and the political structure of risk decisions have been studied. So far, these scientific literatures exist side by side, with few apparent efforts at theoretically conceptualizing and empirically testing the links between the two. Therefore, this exploratory and conceptual paper takes up the challenge: How should we conceptualize the cognitive structure of uncertainty? How should we conceptualize the political structure of risk? How can we conceptualize the link(s) between the two? Is there any empirical support for a conceptualization that bridges the analytical and political aspects of risk? What are the implications for guidelines for risk analysis and assessment