Relevant bibliographies by topics / Robo-advisor

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Academic literature on the topic 'Robo-advisor'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 August 2024

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Journal articles on the topic "Robo-advisor"

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Filiz, Ibrahim, Jan René Judek, Marco Lorenz, and Markus Spiwoks. "Algorithm Aversion as an Obstacle in the Establishment of Robo Advisors." Journal of Risk and Financial Management 15, no. 8 (August 8, 2022): 353. http://dx.doi.org/10.3390/jrfm15080353.

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Within the framework of a laboratory experiment, we examine to what extent algorithm aversion acts as an obstacle in the establishment of robo advisors. The subjects had to complete diversification tasks. They could either do this themselves or they could delegate them to a robo advisor. The robo advisor evaluated all the relevant data and always made the decision which led to the highest expected value for the subjects’ payment. Although the high level of efficiency in the robo advisor was clear to see, the subjects only entrusted their decisions to the robo advisor in around 40% of cases. In this way, they reduced their success and their payment. Many subjects orientated themselves towards the 1/n-heuristic, which also contributed to their suboptimal decisions. As long as the subjects had to make decisions for others, they noticeably made a greater effort and were also more successful than when they made decisions for themselves. However, this did not have an effect on their acceptance of robo advisors. Even when they made decisions on behalf of others, the robo advisor was only consulted in around 40% of cases. This tendency towards algorithm aversion among subjects is an obstacle to the broader establishment of robo advisors.
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Kim, Seongsu David, Marty Cotwright, and Swarn Chatterjee. "Who Are Robo-Advisor Users?" Journal of Finance Issues 18, no. 2 (December 31, 2019): 33–50. http://dx.doi.org/10.58886/jfi.v18i2.2225.

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The purpose of this study is to explore the demand for robo-advising services by analyzing the participants’ behavioral characteristics and investment patterns. With the 2015 Financial Industry Regulatory Authority Investor data, we found that robo-advisor users were younger investors with high risk tolerance, whose self-assessment of financial knowledge is comparatively higher than their actual knowledge, and were independent decision-makers. By controlling for those behavioral attributes of robo-advisor users, we also found that robo-advisor users were reluctant to invest in individual stocks, while they showed the largest preference for investing in pooled investment products such as Exchange Traded Funds. Implications of this study’s findings can be beneficial to financial planning practitioners, academics, and regulators.
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Anshari, Muhammad, Mohammad Nabil Almunawar, and Masairol Masri. "Digital Twin: Financial Technology’s Next Frontier of Robo-Advisor." Journal of Risk and Financial Management 15, no. 4 (April 2, 2022): 163. http://dx.doi.org/10.3390/jrfm15040163.

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This research examines the concept of a robo-advisor with digital twin capabilities for personal financial management. Using an exploratory study, the researchers developed an interactive and interpretive model that analyses the most critical variables to consider when designing the next level of financial robo-advisor through integrating digital twin concepts and applications. Primarily, it conducts an assessment and then reviews the data to propose a model that can serve as a baseline for future research. Related literature was explored, including peer-reviewed journal articles, case studies, periodicals, newspaper articles, and books. This study aims to assess the concept of digital twin (DT) as the next frontier of robo-advisor as a new wave of intelligent financial advisors in supporting the personalisation and customisation of financial technology (FinTech) services and management. Individuals who use a DT-enabled robo-advisor may find a significantly greater value for their financial management and well-being. A robo-advisor with DT enabled will no longer be an ad hoc financial advisory service but will evolve into a comprehensive and dynamic financial advisory service for users. The research presents several critical insights on financial robo-advisory with DT capabilities, transforming and optimising smart financial advisory.
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Cheng, Xusen, Fei Guo, Jin Chen, Kejiang Li, Yihui Zhang, and Peng Gao. "Exploring the Trust Influencing Mechanism of Robo-Advisor Service: A Mixed Method Approach." Sustainability 11, no. 18 (September 9, 2019): 4917. http://dx.doi.org/10.3390/su11184917.

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As a typical application of fintech, the robo-advisor has increasingly gained attention over the last decade. However, most research regarding the robo-advisor has focused on its development issues such as performance improvement and regulation, while limited research has paid attention to trust. This research extends the literature by investigating the trust influencing mechanism of robo-advisors by a mixed method approach. Specifically, we identified six salient trust influencing factors by qualitative interviews and proposed the research model based on trust transfer theory. This model was tested via a survey of 230 investors. Our study finds the significant influencing role of supervisory control and validates the relationships among trust influencing factors, trust in technologies, trust in vendor and trust in robo-advisor. Moreover, several differences between junior investors and senior investors are also found in our research. This study examines trust transfer theory in the new context of the robo-advisor and contributes to further development of this increasingly utilized service.
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Faradynawati, Ida Ayu Agung, and Inga-Lill Söderberg. "Sustainable Investment Preferences among Robo-Advisor Clients." Sustainability 14, no. 19 (October 4, 2022): 12636. http://dx.doi.org/10.3390/su141912636.

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The increasing role of individual investors in supporting the achievement of sustainable development goals through sustainable investment has gained growing interest from financial authorities and the research community. Digitalization in the financial sector, e.g., robo-advisors, enables lay-investors to make sustainable investments in a simple and convenient way. This study investigates whether investment-related attitudes and demographic profiles are related to robo-advisor clients’ sustainable investment choices. This paper describes an empirical study that uses a logistic regression model to investigate sustainable investment preferences at the individual investor level. Cross-sectional data consisting of 27,771 individual investors in Sweden, Norway, and Finland, who purchased investment products through a robo-advisor application, are used in this study. The results suggest that, concerning investment-related attitudes, robo-advisor clients with low-risk tolerance and a short investment horizon are more likely to choose to become sustainable investors. Furthermore, sustainable investments are preferred by robo-advisor clients who are less wealthy, female, and older.
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Kim, Chang Ki. "Robo-Advisor and Risk Management." Global Financial Review 02, no. 01 (March 31, 2021): 47–72. http://dx.doi.org/10.51265/gfr.2021.2.1.47.

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Yi, Tan Zi, Noor Ashikin Mohd Rom, Nurbani Md Hassan, Mohamad Shaharudin Samsurijan, and Andrew Ebekozien. "The Adoption of Robo-Advisory among Millennials in the 21st Century: Trust, Usability and Knowledge Perception." Sustainability 15, no. 7 (March 30, 2023): 6016. http://dx.doi.org/10.3390/su15076016.

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Robo-advisor has become the new personal wealth management and investment method. Nonetheless, certain predicaments are faced by robo-advisor companies as a tech-savvy young group of individuals seems to be less willing to adopt robo-advisory. This study investigates millennials’ adoption of robo-advisory in terms of financial knowledge, trust and usability perception in the 21st century to enhance sustainability. This quantitative study focuses on individuals belonging to the millennial generation who were born between 1981 and 1996. The findings indicate that the millennials who possess financial knowledge, as well as perceived usability and trust have a significant positive effect on the willingness to embrace robo-advisory as a tool for wealth management. The higher the financial knowledge of an individual, the more likely they are willing to adopt a robo-advisor. Government may provide appropriate avenues to enhance financial knowledge, and credible and user-friendly platforms with resources to boost the millennials’ usage of robo-advisors for their wealth management. With robust artificial intelligence, robo-advisory continues to support users, especially millennials, through three dimensions of sustainable development: environment, society, and economy.
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Hasanah, Eneng Nur, Sudarso Kaderi Wiryono, and Deddy P. Koesrindartoto. "Financial Robo-Advisor: Learning from Academic Literature." Jurnal Minds: Manajemen Ide dan Inspirasi 10, no. 1 (February 14, 2023): 17–40. http://dx.doi.org/10.24252/minds.v10i1.33428.

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Financial Robo-Advisor is the technology that integrates machine learning and self-identification to determine investment decisions. This study explores the financial robo-advisor based on bibliometric analysis and a systematic literature review. The method used three steps: determining the keyword, bibliometric analysis of literature metadata using VOSviewer, then collecting and analysing the articles. The bibliometric analysis results show five cluster keywords defined with different colors. In the network visualization, the robo-advisor connects to other keywords: investment, fintech, and artificial intelligence. Furthermore, the systematic literature review shows that the articles are divided into seven research objectives: (1) Law, Regulation, and Policy; (2) Investment Literate and Education; (3) Offered Services; (4) Present Risk-Portfolio Matching Technology; (5) Optimal Portfolio Methods; (6) Human-Robo Interaction; (7) Theoretical Design and Gap. Furthermore, this study can be used by academicians and practitioners to find out about robo-advisors based on an academic perspective.
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Sabir, Asrar Ahmed, Iftikhar Ahmad, Hassan Ahmad, Muhammad Rafiq, Muhammad Asghar Khan, and Neelum Noreen. "Consumer Acceptance and Adoption of AI Robo-Advisors in Fintech Industry." Mathematics 11, no. 6 (March 8, 2023): 1311. http://dx.doi.org/10.3390/math11061311.

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Artificial intelligence (AI) has provided significant help in many fields of life. This study proposed a framework that helped in understanding customers’ attitudes about the adoption of Robo-advisors. The role of the Technology Readiness Index moderated as one of the primary relationships. A total of 208 potential users of Robo-advisor services provided the data that confirmed the validity of the model. This model provided the input for structural equation modeling and analysis of the study hypotheses. The results indicated that consumers showed positive attitudes about Robo-advisor services, with the moderating effect of Technology Readiness Index dimensions, namely, contributors and inhibitors. Perceived ease of use, perceived usefulness, and perceived convenience influenced consumers in developing positive attitudes about this service. Financial businesses can design better AI Robo-advisor services to fulfill the requirements of a wide range of consumers. This proposed framework contributes to the consumers’ understanding of behavioral intentions for the use of Robo-advisors in FinTech.
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Junhui, WENG. "Comparison of Fund Robo-advisor and Manual Decision-making Focused on China Securities Examples." Advances in Economics, Management and Political Sciences 44, no. 1 (November 10, 2023): 140–50. http://dx.doi.org/10.54254/2754-1169/44/20232210.

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As a major achievement in the field of Fintech, intelligent investment has gradually become popularized in China due to its low-cost and low-barrier advantages. However, few studies have compared the income gap between robo-advisor and manual decision-making. As a well-known securities company in China, China Securities is at the forefront of the development of intelligent investment and has achieved good results in fund business and intelligent investment business. This study compares fund products managed by China Securities' fund manager with those on the robo-advisor trading platform "Qingting Butler". By comparing its cumulative rate of return during the period and daily yield, calculating the Adjusted R-square, average value, and overall variance, using the unary linear regression analysis method, to explore the gap between manual decision-making and robo-advisor. Based on the comparison between the two major decisions, it will preliminarily explore the development of robo-advisor in the Chinese market and provide a quantitative basis for investors when facing artificial and intelligent investment choices.
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Dissertations / Theses on the topic "Robo-advisor"

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Pascu, Vasile Alin <1991&gt. "Evoluzione del wealth management: i robo advisor." Master's Degree Thesis, Università Ca' Foscari Venezia, 2020. http://hdl.handle.net/10579/16773.

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La crescita di strategie passive nell’asset management, i cambiamenti nelle preferenze dei clienti e l’innovazione tecnologica stanno favorendo la nascita di start-up che si occupano di robo-advisory. L’idea di base del seguente elaborato è quella di indagare se le strategie adottate dai Robo Advisor sono in grado di creare valore per gli investitori comuni e di individuare i possibili sviluppi futuri. Nella prima vengono individuati i principali operatori a livello globale e successivamente viene descritto in modo dettagliato come operano i Robo Advisor. Nella seconda parte invece, vengono analizzate le performance dei principali operatori rispetto al mercato.
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Nelde, Matthias Michael [Verfasser]. "Anlageentscheidungen privater Investoren : Robo-Advisor als Instrument zur Rationalitätssicherung / Matthias Michael Nelde." Düren : Shaker, 2019. http://d-nb.info/1196492395/34.

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Theis, Ricarda [Verfasser]. "Der Einsatz automatischer und intelligenter Agenten im Finanzdienstleistungsbereich. : Eine aufsichtsrechtliche und zivilrechtliche Einordnung am Beispiel sog. Robo-Advisor. / Ricarda Theis." Berlin : Duncker & Humblot, 2021. http://d-nb.info/1238493823/34.

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Bertrand, Astrid. "Misplaced trust in AI : the explanation paradox and the human-centric path. A characterisation of the cognitive challenges to appropriately trust algorithmic decisions and applications in the financial sector." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAT012.

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L'IA devenant de plus en plus présente dans nos vies, nous sommes soucieux de comprendrele fonctionnement de ces structures opaques. Pour répondre à cette demande, le domaine de la recherche en explicabilité (XAI) s'est considérablement développé au cours des dernières années. Cependant, peu de travaux ont étudié le besoin en explicabilité des régulateurs ou des consommateurs à la lumière d'exigences légales en matière d'explications. Cette thèse s'attache à comprendre le rôle des explications pour permettre la conformité réglementaire des systèmes améliorés par l'IA dans des applications financières. La première partie passe en revue le défi de prendre en compte les biais cognitifs de l'homme dans les explications des systèmes d'IA. L'analyse fournit plusieurs pistes pour mieux aligner les solutions d'explicabilité sur les processus cognitifs des individus, notamment en concevant des explications plus interactives. Elle présente ensuite une taxonomie des différentes façons d'interagir avec les solutions d'explicabilité. La deuxième partie se concentre sur des contextes financiers précis. Une étude porte sur les systèmes de recommandation et de souscription en ligne de contrats d'assurance-vie. L'étude souligne que les explications présentées dans ce contexte n'améliorent pas de manière significative la compréhension de la recommandation par les utilisateurs non experts. Elles ne suscitent pas davantage la confiance des utilisateurs que si aucune explication n'était fournie. Une autre étude analyse les besoins des régulateurs en matière d'explication dans le cadre de la lutte contre le blanchiment d'argent et le financement du terrorisme. Elle constate que les autorités de contrôle ont besoin d'explications pour établir le caractère répréhensible des cas de défaillance échantillonnés, ou pour vérifier et contester la bonne compréhension de l'IA par les banques
As AI is becoming more widespread in our everyday lives, concerns have been raised about comprehending how these opaque structures operate. In response, the research field of explainability (XAI) has developed considerably in recent years. However, little work has studied regulators' need for explainability or considered effects of explanations on users in light of legal requirements for explanations. This thesis focuses on understanding the role of AI explanations to enable regulatory compliance of AI-enhanced systems in financial applications. The first part reviews the challenge of taking into account human cognitive biases in the explanations of AI systems. The analysis provides several directions to better align explainability solutions with people's cognitive processes, including designing more interactive explanations. It then presents a taxonomy of the different ways to interact with explainability solutions. The second part focuses on specific financial contexts. One study takes place in the domain of online recommender systems for life insurance contracts. The study highlights that feature based explanations do not significantly improve non expert users' understanding of the recommendation, nor lead to more appropriate reliance compared to having no explanation at all. Another study analyzes the needs of regulators for explainability in anti-money laundering and financing of terrorism. It finds that supervisors need explanations to establish the reprehensibility of sampled failure cases, or to verify and challenge banks' correct understanding of the AI
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Rodrigues, Alessandra Alves. "A mean-variance look at robo-advising." Master's thesis, Instituto Superior de Economia e Gestão, 2019. http://hdl.handle.net/10400.5/19635.

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Mestrado em Finanças
Nos últimos anos, a indústria de gestão de riquezas enfrentou desafios significativos e tendências impactantes, tais como a diminuição da confiança dos clientes nos serviços financeiros tradicionais, novos encargos regulatórios e aumento da concorrência. Neste contexto, a ascensão de gestores de investimento automatizados, conhecidos como "roboadvisors" e a nova combinação de ciência e capital humano tem desafiado a indústria de gestão de capital a encontrar novas formas de criar valor para beneficiar o cliente. Sobre esse assunto, esse projeto contribui para uma análise de risco-retorno e analise das fronteiras eficientes do portfólio recomendado de cinco plataformas online nos Estados Unidos em março de 2017: Charles Schwab, SigFig, Wealthfront, ToleRisk e RiskAlyze. Nessa análise, são realizados "backtesting" para avaliar o desempenho, a volatilidade, o valor em risco e os índices de Sharpe. Esse projeto é baseado na Teoria da Variação Média e é baseado em preços históricos de fechamento semanal de fundos de investimento abertos negociados em bolsa. Os resultados indicam que a prática atual de utilizar questionários para determinar o perfil de risco do investidor é de confiabilidade limitada. Os resultados também mostram que o modelo "robo-advisory" aparentemente beneficia investidores conservadores. Assim, esta dissertação contribui para uma visão sobre os benefícios e limitações das plataformas de investimento online, fornecendo um parâmetro para uma melhor compreensão do seu potencial futuro.
In the last few years the wealth management industry has experienced significant challenges and impactful trends, such as a decrease in customers' trust of traditional financial services, new regulatory burdens and increase of competition. In this context, the rise of automated investment managers, well known as "robo-advisors" and the new combination of science and human capital has been challenging the wealth management industry to find new ways to create value benefiting the client. On this matter, this project contributes to a analysis of risk-return look and efficient frontiers of the recommended portfolio of five online platforms in United States in March 2017: Charles Schwab, SigFig, Wealthfront, ToleRisk and RiskAlyze. In this analysis, back-testing is conducted to assess performance, volatility, value at risk and sharpe ratios. This project is based on the Mean-Variance Theory and uses historical weekly closing prices of exchanged traded-funds. Results indicates that the current practice of using questionnaires to determine investor risk profiles is of limited reliability. It also benefits investing that the robo-advisor model is seemingly benefits investingting conservative investors the most. Thus, this dissertation contribute to a view on Robo-advisors benefits and limitations, providing a parameter for better understanding its future potential.
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Smith, Jacques. "Constructing low cost core-satellite portfolios with multiple risk constraints: practical applications to Robo advising in South Africa using active, passive and smart-beta strategies." Master's thesis, Faculty of Commerce, 2020. http://hdl.handle.net/11427/32985.

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Risk and tracking error budgeting was originally adopted by large institutional investors, including pension funds, plan sponsors, foundations, and endowments. More recently, risk and tracking error budgeting have gained popularity among financial advisors, multi-managers, fund of funds managers, high net worth individuals as well as retail investors. These techniques contribute to the portfolio optimisation process by limiting the extent to which a portfolio can deviate from its benchmark with regards to risk and tracking error. This is an ambitious paper that attempts to determine the optimal strategy to practically implement risk and tracking error budgeting as a portfolio optimisation technique in South Africa. This study attempts to bridge the gap between active, passive, and smart-beta investment management styles by introducing a low-cost portfolio construction technique, for core-satellite portfolio management, which contributes to the risk and tracking error budgeting process. Core-satellite portfolios are designed to expose the portfolio to a low-cost primary “core” consisting of passive and enhanced index funds, thus systematic risk “beta”, limiting the tracking error of the portfolio. The secondary “satellite” component is allocated to active and smart-beta managers to exploit expected excess return “alpha”. The primary aim of this research is to construct a rule-based product range of core-satellite portfolios called “replica portfolios”. The product range builds on the foundation of the Association for Savings & Investments South Africa (ASISA) framework. The study identifies three “target portfolios” from ASISA's framework, namely (1) High Risk: SA General Equity, (2) Medium Risk: SA Multi-Asset High Equity and (3) Low Risk: SA Multi-Asset Low Equity. Through this framework, active managers from each category are shortlisted using a Sharpe and Information Ratio filter. A secondary filtering technique, namely Returns Based Style Analysis (RBSA) is used to determine the style, R-squared and alpha-generating ability of active managers versus the passive asset classes and style indices they seek to replicate. Applying Euler's theorem for homogenous functions, we decompose the risk of the coresatellite portfolio into the risk contributed by each of its components. The primary mandate of the core-satellite portfolios in the product range is to allocate risk and tracking error efficiently across several investment management styles and asset classes in order to maximise returns while remaining within the specified risk parameters. iii The results highlighted that active managers, after fees, predominantly failed to outperform their benchmarks and passive building blocks, as identified through RBSA over the sample period (October 2009 – September 2019). However, only a small number of active managers generated superior risk-adjusted returns and were included in the core-satellite range of products. This study recommends to investors that they exploit the “hot-hands effect” by investing in specialised, benchmark agnostic active managers who consistently produce superior risk-adjusted returns. By blending active, passive and smart-beta strategies, investors are exposed to less total risk, less risk per holding and a lower tracking error. The three coresatellite portfolios developed in this study generated absolute and risk-adjusted returns that are more significant than their active and passive counterparts. Fee arbitrage was derived through the range of core-satellite products, resulting in tangible alpha over the sample period. The study encourages investors to use smart-beta strategies alongside active and passive funds since it improves Sharpe and Information ratios while enhancing the original portfolio's characteristics.
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Stenberg, Alexander. "Finansiell robotrådgivning : Faktorers effekt på svenska konsumenters intention till användning. UTAUT2 med uppfattad risk och tillit." Thesis, Uppsala universitet, Institutionen för informatik och media, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-437422.

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In times when traditional saving accounts are no longer attractive due to the current interest rates, robo-advisors appears to be an alternative investment utility. Robo-advisor has made investment advisory services available to the general public by offering automated system to allocate assets that is tailored to each individual’s investment needs and risk profile. The successful implementation of robo-advisors depends heavily on the extent of how much customers are fully motivated to use these services. The purpose of this study is to identify factors that affect Swedish consumers intention to use robo-advisors using UTAUT (unified theory of acceptance and use 2) with the extended factors perceived risk and trust. The results indicate that performance expectancy, facilitating conditions, hedonic motivation and perceived risk influence how Swedish consumers formulate their behavioral intention to use robo-advisors.
I samband med det låga ränteläget har traditionella sparkonton blivit mindre attraktiva och genererat en ökad efterfråga bland konsumenter på nya investeringsalternativ. Finansiell robotrådgivning har gjort investeringsrådgivning tillgängligt för allmänheten genom att erbjuda automatiserade system för portföljförvaltning. Framgångsrik etablering av finansiella robotrådgivningstjänster beror i vilken utsträckning potentiella kunder är motiverande att börja använda dessa system. Syftet med denna studie är att undersöka vilka faktorer som påverkar svenska konsumenters intention till användning av finansiella robotrådgivningstjänster. Studiens undersökningsmodell är baserad på the unified theory of acceptance and use 2 (UTAUT2), med adderade faktorer: uppfattad risk och tillit. Data samlades in via en surveyundersökning och tolkades med hjälp av Partial Least Square Structual Equation Modelling (PLS-SEM). Resultatet indikerar att förväntad prestation, underlättande förutsättningar, hedonisk motivation och uppfattad risk har betydande effekt för hur intention till användning formas.
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Thomas, Tomas, and Tobil Poli. "Bankernas utmaningar under digitaliseringens framfart : En kvalitativ studie om hur banker hanterar förtroenderelaterade frågor gentemot sina kunder under den digitala utvecklingen." Thesis, Södertörns högskola, Företagsekonomi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-32927.

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Bakgrund: Banksektorn genomgår en digital utveckling och förändringen sker i en allt snabb takt. Nya marknadsförhållanden med regelverk, en förändrad konkurrenssituation och ett förändrat kundbeteende har ställt banksektorn inför nya utmaningar och möjligheter som bankerna behöver förhålla sig till för att upprätthålla och stärka förtroendet gentemot sina kunder. Syfte: Studiens huvudsyfte är att undersöka hur banker hanterar förtroenderelaterade frågor under den ökade digitaliseringen inom banksektorn. Vidare syftar studien till att skapa en djupare förståelse för robotiserade rådgivningsprocesser och dess påverkan på bankkundernas förtroende i samband med att den fysiska kontakten mellan bank och kund minskar. Metod: Studien är utav en kvalitativ karaktär med en abduktiv forskningsansats och baseras på intervjuer med fem respondenter med relevanta yrkesroller som berör digitalisering- och förtroendefrågor inom den svenska banksektorn. Slutsats: Studiens resultat påvisar att digitaliseringen medför nya möjligheter och utmaningar som bankerna kan dra nytta av förutsatt att dem hanterar den digitala utvecklingen på ett korrekt sätt. Resultatet tyder vidare på att bankerna behöver förhålla sig till dem förändrade marknadsförhållandena och ständigt bemöta kundernas förväntansbild.
Background: The banking industry is facing a digital transformation and the change is taking place at a rapid pace. New market conditions, a changing competitive situation and a changing customer behavior have put the banking industry in front of new challenges and opportunities that banks needs to manage to maintain and strengthen their customers trust towards themselves. Purpose: The main purpose of the study is to investigate how banks handles trust-related issues in the context of the increased digitalization in the banking industry. Furthermore, the study aims to create a deeper understanding of robo-advising and its impact on banking customers' trust while the physical contact between banks and customers decreases. Method: The study is of a qualitative character and follows an abductive research effort. The study is based on interviews with five respondents with relevant professional roles that concern digitalization and trust within the Swedish banking industry. Conclusion: The study's results show that digitalization brings new opportunities and challenges that banks can benefit from, given they handle the digital development properly. The result further indicates that banks need to manage the changing market conditions and constantly respond to customers' expectations.
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CHEN, YU-HAN, and 陳郁涵. "The Current Status of Robo-Advisor." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/892k63.

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碩士
國立高雄第一科技大學
金融系碩士班
105
Robo-advisor, an emerging service provided by the financial holdings and Internet companies, tries to act proactively and offer more instant financial consultancy. With in-depth advisory service, the public enjoys the fast and dedicated financial consultancy; therefore, this trend potentially becomes one of the key focuses for financial holdings and Internet companies to grab more market share in such an intense competitive financial world. Acknowledging that personal financial consultants might provide their portfolio suggestion based on their subjective judgment and ethical decision, in this thesis, financial researches and papers about robot financial advisors at home and abroad are collected and analyzed for the purpose of finding out how to combine the latest data science and machine learning - together with the traditional financial consultancy and construct the suitable and correspondent financial portfolio for the public. The rise of Robo-advisor becomes one of the key services for the financial holdings. Such brand-new business model will bring enormous effect in the financial industry; therefore, by analyzing its business models, development plan and guideline, this thesis is keen to find out the best collaboration between the traditional financial consultant and the Robo-advisor.
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LIU, CHING, and 劉晴. "Factors Influencing Customer Acceptance of Financial Robo-Advisor." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/8gwu39.

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碩士
國立中正大學
資訊管理系研究所
106
Under the increasing influence of FinTech, traditional financial institutions are facing the new reforms. Due to the rapid development and applications of artificial intelligence, many traditional concepts have been subverted. Financial robo-advisor is one of the most popular applications in FinTech services. The technology of big data and artificial intelligence has changed the traditional financial operations, which relied heavily on financial specialist in the past. Since the customer acceptance is a key factor of success, this study aims to examine the factors that influence the customer acceptance of financial robo-advisor. The theoretical model was developed based on the mode of attitude. We used an Web survey to collect the data. The questionnaire contains 73 questions related to 12 factors, namely, involvement in financial, financial relevance, trust, compatibility, personal innovativeness, perceived value, perceived risk, playfulness, social presence, past experience, attitude and intention to use. Consequently, 287 valid responses were collected. The analytical results show that the key factors that affect the customer acceptance of financial robo-advisor are trust, compatibility, perceived value, playfulness and social presence. Finally, implications for academics and practitioners are also provided.
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Books on the topic "Robo-advisor"

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Ranin, Aki. Robo-Advisor with Python: A Hands-On Guide to Building and Operating Your Own Robo-advisor. de Gruyter GmbH, Walter, 2023.

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MBA, Dan Keppel. Best Robo-Advisor: Ultimate Automatic Wealth Management. Createspace Independent Publishing Platform, 2016.

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Build a Robo Advisor with Python (from Scratch). Manning Publications Co. LLC, 2024.

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Mian, Shahnawaz. Robo Advisor Im Vergleich Zum Klassischen Anlagegeschaft Im Retail Banking. GRIN Verlag GmbH, 2017.

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Demuth, Fabian. Robo Advisor. Die Digitale Zukunft der Vermögensverwaltung in der Finanzbranche? GRIN Verlag GmbH, 2018.

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Schalich, Cedric. Anlageberatung in Zeiten der Digitalisierung. Wie Können Robo Advisor Die Traditionelle Anlageberatung Verändern? GRIN Verlag GmbH, 2018.

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Müller, Florian. Digitale Wandel in der Finanzbranche: Wie Fintechs, Robo Advisor und Blogger Die Banken Schlagen. Independently Published, 2018.

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Müller, Florian. Digitale Wandel in der Finanzbranche: Wie Fintechs, Robo Advisor und Blogger Die Banken Schlagen. Independently Published, 2017.

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Theis, Ricarda. Einsatz Automatischer und Intelligenter Agenten Im Finanzdienstleistungsbereich: Eine Aufsichtsrechtliche und Zivilrechtliche Einordnung Am Beispiel Sog. Robo-Advisor. Duncker & Humblot GmbH, 2021.

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Book chapters on the topic "Robo-advisor"

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Sennewald, Daniel. "Ginmon: Robo Advisor." In FinTechs, 111–18. Wiesbaden: Springer Fachmedien Wiesbaden, 2017. http://dx.doi.org/10.1007/978-3-658-14187-5_11.

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Zhao, Dawei, and Wenting Zhang. "Robo-advisor and Expert Advisor." In Financial Mathematics and Fintech, 117–27. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5592-0_6.

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Schabicki, Theodor, Yvonne Quint, and Soeren Schroeder. "(Re-)Launching a Robo-Advisor as a Bank." In Palgrave Studies in Financial Services Technology, 163–86. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40818-3_9.

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Xue, Jingming, En Zhu, Qiang Liu, Chuanli Wang, and Jianping Yin. "A Joint Approach to Data Clustering and Robo-Advisor." In Cloud Computing and Security, 97–109. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00006-6_9.

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Kobets, Vitaliy, Oleksandr Petrov, and Svitlana Koval. "Sustainable Robo-Advisor Bot and Investment Advice-Taking Behavior." In Lecture Notes in Business Information Processing, 15–35. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-23012-7_2.

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Canoz, Ismail. "An Exploration into the Posture of Robo-Advisor Globally." In Artificial Intelligence Systems and the Internet of Things in the Digital Era, 197–205. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77246-8_20.

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Zeng, Zhuoyu. "Research on Legal Risk and Regulation of Robo-advisor in China." In Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022), 1914–22. Dordrecht: Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-098-5_215.

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Prozorova, Katarina. "How Emerging Technologies Will Change Emerging Markets - Welcome Robo-Advisor X.0!" In The WealthTech Book, 71–73. Chichester, UK: John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781119444510.ch17.

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Savchenko, Serhii, and Vitaliy Kobets. "Development of Robo-Advisor System for Personalized Investment and Insurance Portfolio Generation." In Communications in Computer and Information Science, 213–28. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-14841-5_14.

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Singh, Jagjit, and Shikha Sharma. "Factors affecting eco-friendly hotel selection: A Robo-Advisor on customer’s perception." In Proceedings of the International Conference on Innovation and Regenerative Trends in Tourism and Hospitality Industry (IRTTHI 2024), 537–46. Dordrecht: Atlantis Press International BV, 2024. http://dx.doi.org/10.2991/978-94-6463-437-2_36.

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Conference papers on the topic "Robo-advisor"

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Day, Min-Yuh, Jian-Ting Lin, and Yuan-Chih Chen. "Artificial Intelligence for Conversational Robo-Advisor." In 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2018. http://dx.doi.org/10.1109/asonam.2018.8508269.

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Chen, Liping, Kun Liu, Yanwei Wang, and Haoming Zhang. "A Portfolio Selection Model for Robo-Advisor." In 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS). IEEE, 2018. http://dx.doi.org/10.1109/ccis.2018.8691258.

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Luo, Xiaoqing, Ke Feng, and Xiaoli Fang. "A Framework for Robo-advisor Based on Knowledge Fusion." In 2021 International Conference on Intelligent Computing, Automation and Applications (ICAA). IEEE, 2021. http://dx.doi.org/10.1109/icaa53760.2021.00059.

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"Research on the Development Direction of the Robo-Advisor Platform in China——Compared with the Robo-advisor Platform in the United States." In 2021 International Conference on Society Science. Scholar Publishing Group, 2021. http://dx.doi.org/10.38007/proceedings.0001951.

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Day, Min-Yuh, Tun-Kung Cheng, and Jheng-Gang Li. "AI Robo-Advisor with Big Data Analytics for Financial Services." In 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2018. http://dx.doi.org/10.1109/asonam.2018.8508854.

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Gu, Chen-Sheng, Hong-Po Hsieh, Chung-Shu Wu, Ray-I. Chang, and Jan-Ming Ho. "A Fund Selection Robo-Advisor with Deep-learning Driven Market Prediction." In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, 2019. http://dx.doi.org/10.1109/smc.2019.8914183.

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Wang, Pei-Ying, Chun-Shou Liu, Yao-Chun Yang, and Szu-Hao Huang. "A Robo-Advisor Design using Multiobjective RankNets with Gated Neural Network Structure." In 2019 IEEE International Conference on Agents (ICA). IEEE, 2019. http://dx.doi.org/10.1109/agents.2019.8929188.

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Xia, Yuyan, Yanchun Chen, Huiyuan Luo, Yuer Yang, and Xiangjie Wang. "Research and Improvement on the Development of Robo-Advisor: Present and Prospect." In IVSP 2022: 2022 4th International Conference on Image, Video and Signal Processing. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3531232.3531257.

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Ma, Cong. "Robo-advisor: A Deep Reinforcement Learning Algorithm with the Risk Tolerance Regularization for Portfolio Management." In Hradec Economic Days 2023, edited by Jan Maci, Petra Maresova, Krzysztof Firlej, and Ivan Soukal. University of Hradec Kralove, 2023. http://dx.doi.org/10.36689/uhk/hed/2023-01-039.

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Muganda, Brian Wesley, and Bernard Shibwabo Kasamani. "Parallel Programming for Portfolio Optimization: A Robo-Advisor Prototype using Genetic Algorithms with Recurrent Neural Networks." In 2023 International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS). IEEE, 2023. http://dx.doi.org/10.1109/iccns58795.2023.10193396.

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Reports on the topic "Robo-advisor"

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Filiz, Ibrahim, Judek Jan René, Marco Lorenz, and Markus Spiwoks. Algorithm Aversion als Hindernis bei der Etablierung von Robo Advisors. Sonderforschungsgruppe Institutionenanalyse, 2022. http://dx.doi.org/10.46850/sofia.9783947850006.

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Within the framework of an economic laboratory experiment, we investigate how Algorithm Aversion impedes the establishment of Robo Advisors. The participants have to cope with diversification tasks. They can do this themselves or they can entrust a Robo Advisor with this task. The Robo Advisor evaluates all relevant data and always makes the decision that leads to the highest expected value of compensation for the participant. Although the high performance of the Robo Advisor is obvious, the participants only trust the Robo Advisor in around 40% of all decisions. This reduces their success and their compensation. Many participants are guided by the 1/n heuristic, which contributes to their suboptimal decisions. Insofar as the participants have to decide for others, they noticeably put more effort into it and are also more successful than when they decide for themselves. However, this does not affect the acceptance of the Robo Advisor. Even in the case of proxy decisions, the Robo Advisor is only used in around 40% of cases. The propensity of economic agents towards algorithm aversion stands in the way of a broad establishment of Robo Advisors.
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