The findings suggest that technology does not eliminate behavioral biases but instead reshapes their magnitude depending on the market context, and supports the need to reinforce financial education in emerging markets and to promote greater algorithmic transparency within advanced financial systems.
Abstract
The growing adoption of algorithmic financial technologies, including robo-advisors, automated trading platforms and artificial-intelligence-based decision tools, raises a fundamental question regarding their actual contribution to investor rationality. This study investigates the extent to which algorithmic overconfidence, understood as an excessive reliance on automated systems, affects the quality of financial decisions. It also evaluates the direct and moderating role of financial literacy in this relationship. A comparative research design is employed to contrast Morocco, an emerging market characterized by lower literacy levels and a developing regulatory environment, with France, a mature financial ecosystem marked by stronger institutional structures and advanced digital integration. The empirical analysis relies on data collected through a questionnaire administered to 312 individual investors, split almost evenly between the two countries, and the relationships are tested using partial least squares structural equation modeling. The results show that algorithmic overconfidence significantly undermines financial decision quality, whereas financial literacy improves it and bmitigates the negative effect of overconfidence. Multi-group comparisons reveal that this harmful effect is more pronounced in Morocco, while the protective influence of literacy is stronger in France. Overall, the findings suggest that technology does not eliminate behavioral biases but instead reshapes their magnitude depending on the market context. The study contributes to behavioral finance by incorporating the technological dimension into the analysis of cognitive mechanisms and by highlighting financial literacy as a key protective factor. From a practical perspective, the evidence supports the need to reinforce financial education in emerging markets and to promote greater algorithmic transparency within advanced financial systems.
BNPL-specific financial literacy moderated the associations between algorithmic nudging, impulsive buying, and adverse financial outcomes, with the highest-literacy quartile exhibiting substantially attenuated debt trajectories.
Osama Wagdi, Walid Abouzeid, Heba Farid et al.· Journal of Theoretical and A...· 0 citations
The development of global financial markets, the digitalization of investment services, and the increasing participation of retail investors have changed the characteristics of investment decision-making. Under these conditions, investment decisions are no longer solely influenced by rational analysis as assumed in traditional financial theory, but are also influenced by various psychological biases, particularly overconfidence. This bias encourages investors to overestimate their abilities, knowledge, and predictive accuracy, potentially resulting in suboptimal investment decisions. This study aims to systematically synthesize the development of literature on the influence of overconfidence on investment decisions from a behavioral finance perspective, identify dominant research themes, evaluate the consistency of empirical findings, and uncover research gaps that still require development. The study used a Systematic Literature Review (SLR) approach with reference to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The literature selection process was carried out on articles published between 2015 and 2024 through the Scopus, ScienceDirect, SpringerLink, Taylor & Francis, and Google Scholar databases, resulting in ten articles that met all inclusion criteria for analysis.
The synthesis results indicate that overconfidence is a significant determinant of investment decision-making. Five key themes were identified: the influence of overconfidence on investment activity intensity, increased risk appetite, the influence of demographic characteristics such as gender and generation, the role of investment digitalization in reinforcing behavioral biases, and the consistency of overconfidence across developing countries. In addition to strengthening the relevance of behavioral finance as an approach capable of explaining the limitations of investor rationality assumptions, this study also demonstrates that digital transformation has the potential to reinforce the illusion of knowledge and the illusion of control, thereby increasing investors' tendency to make more aggressive investment decisions. This study provides theoretical contributions by mapping the development of the literature on overconfidence and provides practical implications for investors, regulators, and digital investment platform developers in designing strategies to mitigate behavioral biases and strengthen financial literacy. Furthermore, this study identifies the need for longitudinal research and the development of models that integrate financial literacy, financial technology, artificial intelligence, and risk tolerance to broaden understanding of investment behavior in the era of digital transformation.
Ni Luh Reni Martini· The Journal of Financial, Ac...· 0 citations
The rapid growth of financial technology (FinTech) has changed the way people invest, making financial markets more accessible, convenient, and driven by technology. Mobile trading apps, robo-advisory tools, algorithm-based recommendations, social trading platforms, and instant market alerts now allow investors to act on decisions almost as soon as they are made. This ease of access has widened participation in financial markets, but it has also created new psychological pressures that shape how investors think and behave. This paper looks at the psychological side of instant investing through a behavioral finance lens, drawing on existing academic work on investor conduct in digital settings. In particular, it considers how FinTech platforms interact with familiar behavioral biases, including overconfidence, herd behavior, loss aversion, confirmation bias, fear of missing out (FOMO), and present bias, and how this interaction can intensify irrational decisions.
Using a narrative review of peer-reviewed articles, books, and institutional reports, the paper traces how investor behavior has evolved during the FinTech era. The review shows that features such as one-click investing, gamified interfaces, personalized alerts, social media integration, and AI-generated recommendations speed up decision-making, leaving less room for careful analysis. As a result, many retail investors now lean more heavily on emotion, mental shortcuts, and peer influence than on objective financial assessment. Recent studies also suggest that while digital platforms have improved access and participation, they can just as easily encourage speculative trading and overtrading when financial literacy and platform design are not adequate to the task.
The paper concludes that digital investing needs to strike a balance between technological progress and behavioral awareness. Investor education, responsible platform design, regulatory attention, and behavioral interventions all have a role to play in encouraging informed, sustainable investment decisions. By pulling together these threads, the paper adds to the growing literature on the psychological consequences of instant investing within the evolving FinTech ecosystem.
Keywords: Behavioral Finance, FinTech, Instant Investing, Investor Psychology, Behavioral Biases, Retail Investors, Digital Investing, Financial Technology
Dr. Roshanpreet Kaur Dr. Roshanpreet Kaur· International Journal of Cre...· 0 citations
Artificial Intelligence (AI) has significantly reshaped the landscape of the financial services sector by enabling advanced investment platforms that offer automated portfolio management, customized financial advice, and continuous market monitoring. These AI-driven platforms have become increasingly popular among retail investors as they simplify complex investment processes, lower operational costs, and enhance decision-making efficiency. Despite these technological benefits, investors often remain influenced by psychological biases that affect their judgment and overall portfolio outcomes. This study aims to examine how AI-enabled investment platforms impact the quality of investment decisions made by retail investors, while also analyzing the role of behavioral biases such as overconfidence, herd behavior, anchoring effect, and loss aversion. Additionally, the study considers investor trust as a key mediating factor linking the adoption of AI platforms with improved decision-making quality. The research framework is based on the integration of the Technology Acceptance Model (TAM), Behavioral Finance principles, and Trust Theory to better understand investor behavior in a technology-driven environment. Data collection is proposed through a structured questionnaire using established measurement scales targeting retail investors. For analysis, the study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 4 software. The measurement model focuses on assessing reliability and validity through indicators such as Cronbach’s alpha, Composite Reliability (CR), and Average Variance Extracted (AVE), along with discriminant validity tests like the Fornell–Larcker criterion and HTMT ratio. The structural model evaluates relationships using path coefficients, coefficient of determination (R²), predictive relevance (Q²), effect size (f²), and bootstrapping techniques.
D. Goyal, D. Jindal, Dr Sanam Sharma et al.· International Journal of Eco...· 0 citations
With the penetration of financial technology, artificial intelligence and big data into wealth management, robo-advising has been one of the useful instruments for individual investors. This review discusses whether robo-advisors can mitigate behavioral biases of individual investors from a behavioral finance perspective. Through a review of relevant literature on robo-advising, modern portfolio theory, prospect theory, disposition effect, overtrading and limited attention, this paper finds that robo-advisors may enhance investor behavior via risk profiling, diversified asset allocation, automatic rebalancing and rule-based execution. These mechanisms could reduce overconfident trading, chasing returns, concentration of holdings and emotional decisions. Nevertheless, robo-advising is unable to completely eradicate irrational behavior. Its efficacy is subject to the validity of risk questionnaires, algorithmic transparency, platform incentives, investor financial literacy and regulatory scrutiny. Inspired by The Man Who Solved the Market and A Man for All Markets, this review also contends that the value of models does not reside in delivering returns, but in fostering probability thinking, discipline and risk control. Finally, this paper proposes enhancements in transparency, risk disclosure, investor education and conflict-of-interest regulation.
This study aims to analyze the influence of financial literacy on investment decision-making among Generation Z in Bengkulu Province, with herding behavior and loss aversion as moderating variables. This research employs a quantitative approach with an associative design. Data were collected through questionnaires from 133 Generation Z respondents who have experience investing in the capital market. After outlier detection and data cleaning, 124 valid samples were analyzed using multiple linear regression and Moderated Regression Analysis (MRA) with SPSS version 27. The results show that financial literacy has a positive and significant effect on investment decision-making. Herding behaviour and loss aversion were found to moderate this relationship in a negative direction, meaning that the higher the levels of herding behaviour and loss aversion, the weaker the influence of financial literacy on the quality of investment decision-making. This study contributes to the development of behavioral finance theory by demonstrating that behavioral biases can reduce the effectiveness of financial knowledge in forming rational investment decisions among young investors. The findings are expected to serve as a reference for developing more effective financial literacy programs for Generation Z, particularly in regional areas.
Dhiya mufidah erya kamila, Lisa martiah nila Puspita· Journal of Creative Power a...· 0 citations
