The Impact of Robo-Advisors on Human Financial Advisors: A Study of Zenith Bank Plc. Lagos Nigeria

The Impact of Robo-Advisors on Human Financial Advisors: A Study of Zenith Bank Plc. Lagos Nigeria

Akinleye Gideon Tayo¹ & Olatunji Opefolu Francis²

Department of Accounting, Ekiti State University. Ado Ekiti.^1,2

DOI: https://dx.doi.org/10.47772/IJRISS.2025.90400106

Received: 22 March 2024; Accepted: 26 March 2025; Published: 01 May 2025

ABSTRACT

Banks in Nigeria are facing a major change in their traditional advisory business. Many banks have recently started implementing technology to improve customer interactions. The study examined the impact of robo-advisors on human financial advisors in Zenith Bank head office, Lagos State. The specific objectives of the study were to; examine the influence of robo-advisors on the effectiveness of human financial advisors; analyze if the challenges faced by human financial advisors in the face of technological advancements affects the financial services industry. Purposive sampling was employed in this study to select 100 staff of the total population of 510 staff. A questionnaire that was validated by professionals was employed as research instrument. Pearson’s product moment coefficient correlation statistical tool was used to evaluate descriptive, basic tables and percentages created using the statistical packages for social sciences (SPSS) and to assess the two (2) hypotheses. The result of the Pearson correlation in this study found that the role and efficacy of human financial advisors are impacted by the influence of robo-advisors, as indicated by the Pearson correlation test (r = 0.616; α = 0.01), and that the financial services industry is impacted by the possible difficulties that human financial advisors may encounter when confronted with technological advancements (r = 0.965; α = 0.05). the study concludes that there is significant relationship between robo-advisors on the effectiveness of human financial advisors. The study further concludes that there is significant relationship between the challenges faced by human financial advisors and the financial services industry. The study recommends that financial advisors should think about diversifying their revenue streams and service offerings beyond traditional investment management, such as offering holistic financial planning, tax planning, estate planning, and insurance advisory services. To stay competitive in this study, financial advisors should also continuously upskill and stay up to date with the latest industry trends, technological advancements, and client preferences.

Keywords: Robo-advisors, Human financial advisors, Financial Services, Technological advancements.

INTRODUCTION

The banking industry is entering a revolutionary era with the introduction of Artificial Intelligence (AI), which promises previously unheard-of levels of efficiency and customer service enhancements. But there are drawbacks and difficulties to this integration. A thorough systematic assessment of the literature is given by Ghandour (2021), which highlights both important prospects and major obstacles, including the loss of personal touch in consumer encounters, job displacement, and privacy concerns. These difficulties highlight the intricacy of implementing AI in banking, requiring calculated measures to minimize any potential drawbacks. The emergence Artificial Intelligence in banking industry has brought about robo-advisors, an automated platforms that offer online investment management or financial advice with little human involvement, is one example of such innovation. A fascinating discussion about robo-advisors versus human advisors has been triggered by this development. Banking operations are now more successful and efficient because of the introduction of AI, which has transformed customer service by providing individualized banking experiences (Jaiwant, 2021).

The origins of robo-advisors can be found in the telephone trading of securities between brokers and their customers. Improved efficiency resulted from the emergence of electronic communication networks with the 1967 launch of Instinet (a brand name for an electronic system for buying and selling shares) and the 1971 launch of NASDAQ. One of the earliest retail trading platforms on America Online and CompuServe was introduced by Trade Plus in 1985 (Suhel et al. 2020). Soon after, a number more, including TD Ameritrade, joined. A greater proportion of Americans became share owners as a result of the introduction of such retail platforms, which allowed for increased inclusivity and efficiency (the NYSE census revealed that 4.2% of the U.S. population owned common stocks in 1952; by 1990, this had increased to 20%).

Suhel et al. (2020) use artificial machine intelligence language to analyze the shift in banking from traditional conversation to automation through robotic advising systems and electronic payment systems. This transition has not only altered how customers engage with businesses, but it has also been essential in the growth of the banking industry, highlighting the significance of artificial intelligence in adapting to the always evolving needs of consumers. Therefore, emerging technology-based providers that offer greater access, lower prices, or enhanced processes pose a serious threat to wealth management services offered by banks and other traditional providers. Traditional wealth managers face a number of challenges, including outdated legacy systems, high compliance costs brought on by stricter laws and enforcement, increasingly affluent and picky clients, and rapidly evolving technological advancements that alter the industry’s cost structure.

Statement of the Problem

The function of the financial adviser is one that has been highlighted as being threatened by automation as a result of the introduction of robo-advisors into the investment business (Davenport & Kirby, 2016).  At the 2017 European Investment Conference, Randy Cass, the founder of the digital wealth platform Net Wealth, made the argument that financial advisors would become useless unless they could offer anything more than portfolio upkeep. The degree of customization that a robo-advice system may offer could make it hard to tell if a customer was interacting with a human or a machine in the future.

Nonetheless, a few of observers have maintained that human financial advisors will continue to be required. For instance, robo-advice won’t provide human comfort or assurance during a market crisis (Economist, 2015). Scott Smith from Cerlulli agrees, stating that clients seem to need basic human interaction and that human advisers give continuous support (Mosavi, 2018). The past researches on this topic have yielded conflicting results due to some factors which could be attributed to research methods used, source of data among others. However, this study will look at how robo-advisors improves the effectiveness of human financial advisors and also looked at the challenges faced by human financial advisors in the face of technological advancements. The factors which have been given little or no attention in the past studies. Hence, the specific objective of this study are to;

Examine the influence of robo-advisors on the effectiveness of human financial advisors.

Analyze if the challenges faced by human financial advisors in the face of technological advancements affects the financial services industry.

Research Hypotheses

The research objectives were hypothesized in a null form as follows

There is no significant relationship between robo-advisors on the effectiveness of human financial advisors.

There is no significant relationship between the challenges faced by human financial advisors and the financial services industry.

Literature Review

Conceptual Review

Robo-Advisors

Robo-advisors are automated investment platforms that use algorithms to provide investment advice and portfolio management services to clients. These digital platforms typically offer a hands-off approach to investing, making it accessible and affordable for a wider range of investors. Robo-advisory has adapted and digitalized traditional phases and fulfils basic functionalities of financial advice in wealth management (Cocca 2016).

One key concept of robo-advisors is their ability to democratize investing by providing low-cost, efficient, and transparent investment solutions for both novice and experienced investors. By automating the investment process, robo-advisors can offer personalized investment strategies and recommendations based on individual financial goals, risk preferences, and time horizons (Jung et al. 2018).

Robo-advisors use algorithms and software to automate the process of investment portfolio construction, monitoring, and rebalancing, based on the client’s risk profile and investment objectives (D’Acunto et al., 2019). This automation allows robo-advisors to provide investment management services at a lower cost compared to traditional human financial advisors (Chaudhry & Kulkarni, 2020). Robo-advisors typically use questionnaires and data gathering to assess a client’s financial situation, risk tolerance, and investment preferences, and then provide customized investment recommendations and portfolio management (Fisch et al., 2018).

Human Financial Advisors

Human financial advisors play an essential role in providing personalized financial advice and guidance to clients. Unlike robo-advisors, human advisors offer a more personalized approach to financial planning, taking into account individual circumstances, goals, and preferences (D’Acunto et al., 2019). Human advisors often build long-term relationships with their clients, providing ongoing support, education, and advice to help them navigate their financial journey.

Human financial advisors often take a holistic approach to financial management, considering various aspects of a client’s financial life, such as investments, retirement planning, tax strategies, estate planning, and risk management. Human financial advisors often possess advanced professional credentials, such as Certified Financial Planner (CFP) or Chartered Financial Analyst (CFA), which demonstrate their expertise and adherence to industry standards (Baker & Dellaert, 2017).

Nexus between Robo-Advisors and Human Financial Advisors

Having indulgent the nexus between Robo-Advisors and Human Financial Advisors serves as an important issue among researchers and practitioners and this can be understood in the following ways:

Complementary Roles:

Robo-advisors and human financial advisors can serve as complementary solutions, with robo-advisors handling the more automated, routine aspects of investment management and financial planning, while human advisors focus on the more complex, personalized, and relationship-driven aspects (Chaudhry & Kulkarni, 2020).

This division of labor can enable a hybrid approach where clients can benefit from the cost-effectiveness and scalability of robo-advisors, while also having access to the expertise and personalized guidance of human advisors (Fisch, Labouré & Turner, 2018).

Blended Service Models:

Some financial advisory firms are adopting blended service models, where they combine the capabilities of robo-advisors and human financial advisors to provide a more comprehensive and tailored financial advisory experience (Kitces, 2016). Robo-advisors handle the routine investment management tasks, while human advisors focus on more complex financial planning, tax strategies, and client relationships (Chaudhry & Kulkarni, 2020).

Client Segmentation and Targeting:

Robo-advisors may be more suitable for certain client segments, such as those with smaller account balances or less complex financial needs, who may value the cost-effectiveness and convenience of automated investment management (D’Acunto et al., 2019). Human financial advisors, on the other hand, may be better equipped to serve clients with more complex financial situations, higher net worth, or a greater need for personalized advice and emotional support (Kitces, 2016).

Coexistence and Collaboration:

Rather than view robo-advisors and human financial advisors as competitors, some experts suggest that they can coexist and even collaborate to provide a more comprehensive and integrated financial advisory service (Fisch et al., 2018). This collaboration could involve referrals, joint client servicing, or the integration of robo-advisory tools and human expertise (Chaudhry & Kulkarni, 2020).

Technological Enhancements for Human Advisors:

The rise of robo-advisors has also prompted human financial advisors to adopt and leverage various technologies, such as financial planning software, portfolio management tools, and client portals, to enhance their services and improve efficiency (Kitces, 2016). This technological integration can help human advisors streamline their operations, freeing up time to focus on more value-added services and building stronger client relationships (Chaudhry & Kulkarni, 2020).

The Rise of Robo-Advisors and the Role of Human Financial Advisors

The rise of robo-advisors and the role and effectiveness of human financial advisors has been a topic of significant interest in the financial industry. Robo-advisors are digital platforms that provide automated, algorithm-driven financial planning services with little to no human intervention (Fisch et al., 2019). The growth of robo-advisors has been driven by several factors, including the increasing use of technology in financial services, the desire for more affordable and accessible investment advice, and the perceived limitations of traditional financial advisory services (Reher & Sokolinski, 2020).

According to a study by PricewaterhouseCoopers (2021), the global assets under management (AUM) of robo-advisors are expected to reach $16.3 trillion by 2025, up from $1.7 trillion in 2020. This growth highlights the significant influence of robo-advisors in the financial industry. Robo-advisors offer several advantages compared to traditional financial advisory services. These include (Bianchi, 2022).

i. Lower fees: Robo-advisors typically charge lower fees than traditional financial advisors, making investment advice more accessible to a wider range of investors.

ii. Automated portfolio management: Robo-advisors use algorithms to automatically rebalance and optimize client portfolios based on their risk tolerance and investment goals.

iii. Accessibility: Robo-advisors are available 24/7 and can be accessed through mobile devices, making them convenient for investors.

iv. Scalability: Robo-advisors can serve a large number of clients simultaneously, which allows them to offer their services to a broader customer base.

Despite their advantages, robo-advisors also have certain limitations (Bhattacharya et al., 2021):

– Lack of personalized advice: Robo-advisors may not be able to provide the same level of personalized advice and tailored financial planning as human financial advisors.

– Limited scope: Robo-advisors are typically focused on investment management and may not offer comprehensive financial planning services, such as tax planning, estate planning, or retirement planning.

– Reliance on algorithms: Robo-advisors’ recommendations are based on algorithms, which can have biases or may not perform well in unexpected market conditions.

– Lack of emotional support: Investors may miss the emotional support and guidance that human financial advisors can provide during times of market volatility or personal financial challenges.

Theoretical Review

In this study, two important theories that underpin the study are Technology Acceptance Model (TAM) and the Disruptive Innovation Theory.

Technology Acceptance Model (TAM):

The Technology Acceptance Model (TAM) is a widely used theory in the field of information systems that explains how users come to accept and use a new technology (Davis, 1989). According to TAM, the adoption of a new technology, such as robo-advisors, is determined by two key factors: perceived usefulness and perceived ease of use (Davis, 1989).

In the context of robo-advisors, if human financial advisors perceive that the technology is useful in enhancing their efficiency, productivity, or the overall client experience, and if they find the technology easy to use, they are more likely to accept and adopt robo-advisory tools (Hasan et al., 2017). The TAM framework can help understand the factors that influence the adoption of robo-advisory services by human financial advisors and the potential impact on their traditional practices (Hasan et al., 2017).

Disruptive Innovation Theory:

The Disruptive Innovation Theory, developed by Clayton Christensen in 1997, explains how new, often simpler and more affordable technologies can disrupt and transform existing industries (Christensen, 1997). In the financial advisory industry, robo-advisors can be seen as a disruptive innovation, as they provide a more cost-effective and accessible alternative to traditional human financial advisors, particularly for clients with smaller account balances (Fisch et al., 2018).

The Disruptive Innovation Theory suggests that while robo-advisors may initially target the lower-end of the market, they can gradually move upmarket and displace traditional human financial advisors, especially for more standardized and commoditized financial services (Christensen, 1997; Fisch et al., 2018). This theory explains the potential long-term impact of robo-advisors on the financial advisory industry and how human financial advisors may need to adapt their business models and service offerings to remain competitive (Chaudhry & Kulkarni, 2020).

Empirical Review

Unfortunately, there is limited empirical research specifically on the impact of robo-advisors on human financial advisors in Nigeria. Nigeria is still in the early stages of the adoption of robo-advisory services, and the existing literature tends to focus more on the broader Fintech landscape and the potential benefits of robo-advisory services for Nigerian investors.

However, here are a few relevant studies that provide insights into the potential impact of robo-advisors on human financial advisors in the Nigerian context: A study carried out by Adekoya and Adekoya (2020) examined the adoption of Fintech solutions, including robo-advisory services, among Nigerian investors. The findings suggest that Nigerian investors are relatively open to using robo-advisory services, particularly for their simplicity, convenience, and potential cost-effectiveness. The authors note that the adoption of robo-advisory services in Nigeria could disrupt the traditional financial advisory industry, as investors may be drawn to the automated and cost-effective nature of these services.

A study carried out by Adegbite and Mabawonku (2019) investigated the factors influencing the adoption of Fintech innovations, including robo-advisory services, among Nigerian financial institutions. The results indicate that perceived usefulness, perceived ease of use, and regulatory support are key factors that influence the adoption of Fintech solutions by Nigerian financial institutions. The authors suggest that the adoption of robo-advisory services by Nigerian financial institutions could lead to changes in the traditional financial advisory business models and the way financial advice is delivered.

Another study carried out by Ogunleye, Ogundipe & Okafor. (2020) explored the potential benefits of robo-advisory services for Nigerian investors, particularly in terms of accessibility, cost-effectiveness, and personalized investment management. The findings suggest that the availability of robo-advisory services in Nigeria could increase the number of Nigerians who have access to professional investment management, potentially impacting the traditional financial advisory industry.

RESEARCH METHODS

This study employed a survey research design for its investigation. The population of the study comprises of all the 510 staff of Zenith bank PLC situated at Plot 84, Ajose Adeogun Street, Victoria Island, Lagos. A purposive sampling technique was used to select a total of one hundred (100) staff who made the sample size for this study, respondents were grouped into strata according to department, sex, and work status. In order to meet participation criteria. Data for the study was gathered once from a sample of the population in the form of a cross-sectional survey. Basically, primary and secondary used for this study. The primary data were sources through the use of questionnaires. While the secondary data were sourced from bulletins of the aforementioned bank. The study tools were validated through the use of content validity approach. Three experts from the accounting and communication departments at Lagos State University, Ojo Lagos, received the instrument. Initially, the relevance of the questionnaire items to the subject matter was examined. The final draft that was used for the paper was created under their careful inspection before its final used. The questionnaires were then administered to the respondents (100) and all were duly filled and returned back to the researcher.

Data Presentation and Analysis

Simple percentage was employed as the foundation for the data analysis and interpretation process. This means classifying the respondents based on their varied responses in order to determine the represented percentage for each group. Their answers were examined using these percentages, which are presented in tabular form. To test the study’s hypotheses, data were analyzed statistically utilizing tools including tables, percentage distributions, and Pearson product moment correlation.

Demographic Characteristics of Respondents and Classification

This section covers the demographic characteristics of respondents. The variables used in this study such as respondents’ sex, Age distribution, Marital Status, Educational qualifications, Work/Learning Experience and Managerial Levels of the respondents in the study and organizational characteristics are presented in Table II and III below.

Table 4.1: Classification of Respondents’ Background Data

Source: Field Survey, 2024

The above table shows the sex distribution of respondents that 38 respondents representing 38% of the respondents are males while 62 representing 62% are females. This implies that Zenith Bank Plc employ more female than male. The result gathered from respondents used to make reasonable conclusion in this study. The above table also shows the marital status of respondents that 72 respondents representing 72% are single, 18 respondents representing 18% are married while 10 respondents representing 10% are divorced. This implies that majority of the respondents are married. The result gathered from respondents used to make reasonable conclusion in this study.

The age distribution of respondents as presented in above table, 09 representing 9 respondents that  are below 20 years,55 representing 55% are in the age of 21-30, 23 representing 23% are in the age range of 31-40, 8 respondents representing only 8% of the respondents are aged between 41-50 while 5 respondents representing. This implies that 55% of the respondents are over 25 years of age. Furthermore, the table shows that out of 100 respondents, 29(29%) have OND/NCE, 54(54%) have B.Sc/HND, 9(9%) have M.Sc/MBA while 8(8%) have others certificates. This shows that majority of the respondents B.Sc/HND holders. The implication is that more than half of the employees will pay serious attention to impact of robo-advisors on human financial advisors.

Moreover, the table shows that 07(7%) of the respondents have less than 1year working experience. 86(86%) have put in over 4 years of service to the organizations and 7(7%) of the respondents have put in over 9 years of service to the organizations. This implies that between 2-5 years of the employees used to make reliable conclusion in the study. From that the above table, out of 100 respondents, 13(13%) are management staff, 14(14%) are senior staff while 73(73%) are junior staff. This shows that more of the Zenith Bank Plc employees fall within the junior staff rank that helped to make appropriate conclusion in this study.

Selection Procedure of Robo-Advisors and Human Financial Advisors

The areas of activities of respondents were categorized into 2. The selected electronics company was fairly represented by the sampled firms. The selected financial institution had staff strength ranging from 10-510.

Table 4.2:        Measure of Internal Consistency

Source: Field Survey, 2024

The reliability of the instrument was ascertained using the internal consistency method. In order to ensure the instrument is reliable, it was subjected to pre-test administration. This was done by administering the instrument to a similar group and expert on the field for their grading based on 4-point Likert scale. The researcher used the Cronbach’s alpha correlation matrix to test the reliability of the instrument as ranked by the experts in Accounting and it indicated an index of 0.919. This process helps the researcher to measure the consistency of the instrument.

The descriptive statistics of pattern of Robo-Advisors on Human Financial Advisors of selected bank illustrated in Table 4.3 below:

Table 4.3: Impact of Robo-Advisors on Human Financial Advisors in Selected Electronics Company

Source: Field Survey, 2024

Pearson Correlation Matrix

The combinations of all variables were correlated for all] the 100 responding Zenith Bank Plc in this study. The dimensions of robo-advisors were summed as a single variable. The inter-correlational matrix for all the study variables: role and effectiveness of human financial advisors and financial services industry, demographic profiles and organizational characteristics are showed in the table below.

Table 4.4:Means, Standard Deviations and Inter-correlation among All Variables of the Study

*          P <0.05

**        P <0.01, N =   100

Table 4.4 above presents correlations among all study variables. The result denotes that there is significant relationship between robo-advisors and the role and effectiveness of human financial advisors of selected Zenith Bank.

Test of Hypotheses

The two hypotheses formulated in this paper were tested using Pearson moment product correlation.

Hypothesis One

The above Pearson Correlation (r = 0.616; α = 0.01) test reveals a strong positive relationship between robo-advisors and the role and effectiveness of human financial advisors. Therefore, the null hypothesis (H₀) is forgone and we go for alternative hypothesis (H₁) which states that the influence of robo-advisors affects the role and effectiveness of human financial advisors. The acceptance of (H₁) is because it receives statistical support while the (H₀) is rejected.

Hypothesis Two

The above Pearson Correlation (r = 0.965; α = 0.05) test reveals a strong positive relationship between potential challenges faced by human financial advisors in the face of technological advancements and financial services industry. Therefore, the null hypothesis (H₀) is forgone and we go for alternative hypothesis (H₁) which states that the potential challenges faced by human financial advisors in the face of technological advancements do affect the financial services industry. The acceptance of (H₁) is because it receives statistical support while the (H₀) is rejected.

DISCUSSION OF FINDINGS

This study investigates the impact of robo-advisors on human financial advisors. In testing hypothesis one, it was discovered that the Pearson Correlation (r = 0.616; α = 0.01) test, reveals a strong positive relationship between robo-advisors and the role and effectiveness of human financial advisors.in this study. This study is in line with the study carried out by Chaudhry & Kulkarni, (2020) that robo-advisors have disrupted the traditional financial advisory industry in the U.S., leading to the adoption of hybrid models that combine robo-advisory services with human financial advisors. A study also carried out by Adekoya and Adekoya (2020) examined the adoption of Fintech solutions, including robo-advisory services, among Nigerian investors. The findings suggest that Nigerian investors are relatively open to using robo-advisory services, particularly for their simplicity, convenience, and potential cost-effectiveness. The authors note that the adoption of robo-advisory services in Nigeria could disrupt the traditional financial advisory industry, as investors may be drawn to the automated and cost-effective nature of these services.

The result of the test of hypothesis two shows Pearson Correlation (r = 0.965; α = 0.05) test, reveals a strong positive relationship between potential challenges faced by human financial advisors in the face of technological advancements and financial services industry in this study. This study is in line with the study carried out by A study carried out by Adegbite and Mabawonku (2019) investigated the factors influencing the adoption of Fintech innovations, including robo-advisory services, among Nigerian financial institutions. The results indicate that perceived usefulness, perceived ease of use, and regulatory support are key factors that influence the adoption of Fintech solutions by Nigerian financial institutions. The authors suggest that the adoption of robo-advisory services by Nigerian financial institutions could lead to changes in the traditional financial advisory business models and the way financial advice is delivered.

In the context of robo-advisors and human financial advisors, this theory help to explain the potential long-term impact of robo-advisors on the financial advisory industry and how human financial advisors may need to adapt their business models and service offerings to remain competitive (Chaudhry & Kulkarni, 2020). The Disruptive Innovation Theory highlights and supports the findings and relevant to this work the nexus between robo-advisors and human financial advisors and role play globally in collaborating and challenges encountered in the implementation of robo-advisors and human financial advisors.

CONCLUSION

This study validates previous scholars’ assertions about the impact of robo-advisors on human financial advisors in Nigeria. The influence of robo-advisors in the financial industry is undeniable, and they offer several advantages to investors. However, human financial advisors continue to play a crucial role in providing personalized advice and guidance, particularly in areas where robo-advisors have limitations. The hybrid approach, which combines the strengths of both, is emerging as a promising solution for investors seeking a more comprehensive and effective financial advisory service. By applying the Technology Acceptance Model and the Disruptive Innovation Theory, researchers and industry professionals can better understand the factors that influence the adoption of robo-advisory services by human financial advisors, as well as the potential disruptive impact of robo-advisors on the traditional financial advisory industry. It is important to note that the adoption of robo-advisory services in Nigeria is still in its early stages, and further research is needed to understand the specific impact on human financial advisors and how they can adapt to this emerging technology.

The study provides positive insights into the elements driving the adoption of robot advisors. According to the findings, organizations who plan to deploy robot advisors believe that people would profit from their lower rates, round-the-clock advising service, and openness. Additionally, those who plan to utilize robot advisers believe that using robot advisors will take less work than using human advisors. This could make it more difficult for the Robo-Advisors platform’s simple and practical user interface to draw in new clients, particularly from the elderly and others who are not familiar with new technologies. Additionally, those surveyed expressed a strong desire to employ Robo-Advisors if they were recommended by important or close individuals. Interestingly, dangers associated with losses resulting from Robo-Advisors’ malfunctioning algorithm system do not substantially impair respondents’ intention to adopt them.

Recommendations

Based on the potential research findings and the theoretical frameworks in this study, the study recommends that:

Human financial advisors should focus on providing highly personalized and customized advisory services that cater to the unique needs and preferences of their clients. This could involve offering in-depth financial planning, investment management, and wealth management services that go beyond the automated capabilities of robo-advisors. Leveraging their expertise, emotional intelligence, and client relationships, human advisors can provide value-added services that are difficult for robo-advisors to replicate.

Financial advisors should explore ways to integrate technological solutions, such as robo-advisory platforms, into their practice to improve operational efficiency, data analysis, and client engagement. This could involve using robo-advisory tools for routine investment management tasks, allowing human advisors to focus on more complex financial planning and relationship-building activities. By incorporating technology, human advisors can enhance their service delivery, reduce costs, and provide a more seamless and personalized client experience.

Financial advisors should consider diversifying their revenue streams and service offerings beyond traditional investment management, such as providing holistic financial planning, tax planning, estate planning, and insurance advisory services. This can help human advisors differentiate themselves from robo-advisors and cater to a broader range of client needs, enhancing their overall value proposition. Diversification can also help mitigate the potential impact of robo-advisor competition on the core investment management business.

Human financial advisors should focus on building and strengthening their client relationships, emphasizing the personal touch, trust, and emotional connection that they can provide. Enhancing their brand positioning and visibility, as well as developing a strong online presence and digital marketing strategies, can help human advisors attract and retain clients in the face of robo-advisor competition.

Financial advisors should continuously upskill and stay abreast of the latest industry trends, technological advancements, and client preferences to remain competitive. Engaging in ongoing professional development, such as obtaining relevant certifications, attending industry conferences, and participating in training programs, can help human advisors enhance their expertise and adaptability.

REFERENCES

1. Baker, T. & Dellaert, B. (2017). Regulating robo advice across the financial services industry. ERIM report series research in management in Erasmus Research Institute of Management. https://repub.eur.nl/pub/ 98312. Accessed 10 Jul2017.
2. Bhattacharya, T. K., Lam, K. Y., & Mukhopadhyay, A. (2021). Robo-advisors versus human financial advisors: Evidence from a situational experiment: Journal of Behavioral and Experimental Finance, 3(2), 100-121.
3. Bianchi, M., Brière, M., & Verdonck, T. (2022). Robo-advisors versus traditional investment advisors: A comparison of risk and portfolio choice: Journal of Banking & Finance, 13(7), 106-117.
4. Chaudhry, S., & Kulkarni, V. (2020). Robo-advisors and the future of financial planning: Journal of Financial Planning, 33(3), 48-55.
5. Cocca, T. D. (2016). Potential and Limitations of Virtual Advice in Wealth Management. The Capco Institute Journal of Financial Transformation, 44(3), 45–57.
6. D’Acunto, F., Prabhala, N., & Rossi, A. G. (2019). The promises and pitfalls of robo-advising: The Review of Financial Studies, 32(5), 1983-2020.
7. Davenport, T. H. & Kirby, J. (2016), “Beyond Automation” Harvard Business Review, June 2016 Issue
8. Fisch, J. E., Labouré, M., & Turner, J. A. (2018). The emergence of the robo-advisor: In the Disruptive Impact of FinTech on Retirement Systems, 13-37
9. Fisch, J. E., Labouré, M., & Turner, J. A. (2019). The emergence of the roboadvisor. In J. E. Fisch, M. Labouré, & J. A. Turner (Eds.), The Oxford Handbook of Pensions and Retirement Income, Oxford University
10. Hoffmann, A. O., & Plotkina, D. (2021). The impact of financial advisors on the investment decisions of individual investors: Journal of Banking & Finance, 12(4), 106-117.
11. Jaiwant, S. V. (2022). Artificial intelligence and personalized banking. Research Journal on Innovative Management Using AI in Industry, 2(4), 74-87.
12. Jung, D. Dorner, V. Glaser, F. & Morana, S. (2018). Catchword Robo-Advisory – Digitalization and Automation of Financial Advisory, Business & Information Systems Engineering (BISE).
13. Kaya, O. (2020). Robo-advice – a true innovation in asset management. Deutsche Bank Research.
14. Kinniry, F. M., Jaconetti, C. M., DiJoseph, M. A., Zilbering, Y., & Bennyhoff, D. G. (2016). Putting a value on your value: Quantifying Vanguard Advisor’s Alpha. Vanguard Research.
15. Mosavi, B.F., (2018). The transformative power of artificial intelligence in banking client service. South Asian of Social Studies and Economics, 21(3), 93-105.
16.  PwC.(2021). Global fintech report 2021. Price water house Coopers.
17. Reher, M., & Sokolinski, S. (2020). The rise of robo-advising. In P. Gluchowski, S. Seufert, & J. Thiele (Eds.), Digitale Transformation von Dienstleistungen im Gesundheitswesen. 23-47.
18. Suhel, S.F., Shukla, V.K., Vyas, S. and Mishra, V.P., (2020). Conversation to automation in banking through chatbot using artificial machine intelligence language. In 2020 8th international conference on reliability, infocom technologies and optimization (trends and future directions) (ICRITO). 3(6), 611-618.