Efficiencies and Pitfalls of Robo-Advisors


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Robo-advisors put the assets of financial businesses in sync to make everything work perfectly. They deliver the precision and speed which are critical to digital financial services. But as with every boon, there are also banes.

FinTech today is becoming a single-click solution to the complexities in managing tasks, jobs, and overall businesses.

With the advent of technology, new tools today allow banks and financial services to engage in multiple functions and develop new solutions much faster. But customer service, or financial advice that has traditionally been left to experts is also transforming today. Robotic financial advisors can now deliver accurate and actionable insights for customers to make sound financial decisions.

Robo-advisors are online platforms that track investment trends, follow automated algorithms, and recommend opportunities. They advise and support investors in their decisions to create, balance or upgrade their portfolios.  In fact, they can suggest more diversified portfolios to customers by getting analytics using advisors and getting higher returns.

Importance of Robo-advisors

Providing trustworthy advice, robo-advisors help boost the relationship between wealth management firms, banks, financial service companies, and their customers.

One aspect of a great relationship is their cost-effectiveness. Costly wealth managers can now be reliably replaced by very insightful but much cheaper robo-advisers, allowing the company and customers to cut costs to a fraction.

Their adoption will grow with all these advantages they offer.

A report by Research and Markets, “Robo Advisory Global Market Report 2024“, says the overall Robo advisory market will grow from $41.63 billion in 2023 to $61.99 billion in 2024 at a CAGR of 48.9%.

Clearly, the demand for robo-advisors is increasing in the financial industry.

So, it will be interesting to look at its efficiencies closely here.

Efficiencies of Robo-advisors

  • Robo-advisors are Cost-Effective

Robo-advisors run on automation, and are regulated by AI algorithms. It eliminates manual efforts or data collation, helping financial companies cut costs on human skills.

Companies can pass this advantage to their customers by removing entry fees for investment advisory. Essentially, they can increase their customer base, while providing better advisory services.

  • Provide Accessibility and Transparency to Clients

Robo-advisors deliver advantages on two key features—accessibility and transparency.

This adds value and convenience so they can easily make well informed investment decisions. Since the AI bot has a much higher information base than a human wealth manager would, it can help customers visualize important dimensions of an investment, such as liquidity and the degree of diversification.

It will also allow them to have clarity on the estimate of risks in the future.

Also Read: Ways Robotic Process Automation Has Disrupted Banking

  • Around the clock support

Robo-advisors are accessible to investors for their accounts 24×7.

This way, investors can diversify their portfolios across asset classes and sectors at any time during the working hours of the markets to invest and manage their trades efficiently.

Clients also get complete access to multiple portfolio management tools, offering flexibility and security.

  • Offer Easy and accurate information for Investment and account management

Many banks and financial companies offer online platforms for investors and traders. Third-party platforms are complex and offer fewer features or market information in a transparent manner.

So, banks and financial service companies now deploy robo-advisors to provide their clients with accurate financial market trends, reports, and positions. This clear data will help their customers invest in the best options in a timely manner.

Being cost-effective, accurate, and constant support, robo-advisors attract customers to choose digital online financial management systems.

Despite an array of benefits, there are some reasons why Robo-advisors may cause challenges and pitfalls for banks and financial service companies.

Pitfalls of Robo-advisors

  • Less Scope of Personalization and Flexibility offered

Most robo-advisors are limited by their experience with human customers. Since they have learning algorithms, the more information they share, the better their personalization will be. So, at the outset, when a customer starts using a robo advisor, there may not be the required level of customization available.

With time, users can set and edit their investment goals on platforms. This means the robo-advisors are now programmed and configured to meet their needs.

As machines, personalization lacks the understanding of human conditions which a human advisor would have. For instance, it won’t understand the limitation of a user’s funds at some point and won’t be able to invest going forward.

It also won’t be intuitively aware of the financial planning imperatives for a person- education, marriage or any such personal need for funds.

This is where investors may need human intervention to solve these issues. Customers may benefit from talking to human advisors who can help modify investment plans for their situation.

  • Offers Narrow Investment Choices

Investors may not be able to choose some specific investments when using a robo-advisor. Even if they use customized options for investments or allocation within their portfolio, it may still provide limited options and features of pre-selected funds.

It may not be accurately clear on the type of investments to be done or provide suitable options per investors’ needs.

For instance, a robo-advisor can suggest and manage an investment account based on its information. Still, it won’t have complete information on assets added to the accounts for investment purposes.

This may trigger complexities of financial status, route a different way to invest (which won’t be suitable), and may have some other unprecedented repercussions at scale.

  • Dependence on Data:

However, what is important while using these platforms is that they run on data. So, if banks or customers are considering it, it will be all about trusting investment decisions to an algorithm.

Data is key, which can be both advantageous and disadvantageous. It’s because robo-advisors gain insights from the past, and as they function, they also collect new data. Their learning is continuous, and that’s why over the period, they become more accurate and focused.

It may be possible that both data won’t sync at some point, which can be unsuitable for investors.

So, determining whether a robo-advisor is right will depend on the goals and preferences of investors. Determining the type of investment guidance, they need will be a key factor to use a robo-advisor.

Are Robo-Advisors Safe to Use in the Future?

The demand for robo-advisors to automate most financial services like customer financial planning is increasing. They are creating strategies for traders and investors, data insights on market position, market analysis, and more.

It’s becoming a game changer for the industry as it transforms digitally. Deloitte’s blog mentions that the future of the Robo-advisory market is rise from USD 3.7 trillion to USD 16.0 trillion asset under management (AuM) by 2025.

Despite its limitations, Robo-advisors are a good option for investors seeking a low-cost, convenient, personalized investment advisory solution.

Apoorva Kasam
Apoorva Kasamhttps://talkfintech.com/
Apoorva Kasam is a Global News Correspondent with TalkCMO. She has done her master's in Bioinformatics and has 18 months of experience in clinical and preclinical data management. She is a content-writing enthusiast, and this is her first stint writing articles on business technology. She specializes in marketing technology, data-driven marketing. Her ideal and digestible writing style displays the current trends, efficiencies, challenges, and relevant mitigation strategies businesses can look forward to. She is looking forward to exploring more technology insights in-depth.


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