Natalie Monko Lead Project Manager

    Robo Advisor Development for Fintech: What You Need to Know

    Development of software for the fintech robo advisor sector is top requested nowadays. According to ResearchAndMarkets, in the period from 2022 to 2023 the global robo advisory market grew from $28.24 billion to $41.52 billion and is expected to grow to $205.84 billion in 2027. At the same time Statista shows that the number of users in the robo-advisors market is expected to amount to 234.30m users by 2027 while the average assets under management per user is expected to amount to US$8.05k in 2023.

    In the fintech industry, robo advisors are automated solutions based on Artificial Intelligence (AI) and Machine Learning (ML) technologies as well as algorithms that help with financial management. A growing interest in stock trading and other types of investment among less-wealthy individuals lead to digital advice platforms becoming one of the key trends among wealthtech applications, which are focused on helping people with finance management and investing. It is estimated that the size of assets managed by automated investment advisors is going to reach $4.6 trillion by 2022. While many retail investors don’t have a minimum balance required by personal wealth managers, digital tools present an affordable way to get regular personalized investment advice, thanks to recent advancements in AI algorithms.

    A robo advisor integrated with an investment mobile product is a great way to deliver financial advice services directly to customers since more and more people manage their money via mobile applications with convenient and easy-to-use interfaces.

    We at Surf have been developing custom software for over 12 years and have worked with fintech startups, banks, and trading platforms, helping to refine the mobile experience for their clients. We offer our assistance at any software development stage: starting from pre-development activities to UX/Ui design, from mobile and web development to end to end testing, including third-party integrations and AI-based solutions.

    In this article, we’ll review the benefits and drawbacks, types and approaches to create a robo advisor for a fintech app.

    How robo advisors work

    The technology behind robo advisors is based on using algorithms together with data on investors’ goals, preferences and risk tolerance to help them make informed decisions. Most advisors use passive indexing strategies: instead of buying shares of particular companies, they suggest investing in funds that copy market indexes, such as S&P 500, for example. Passive investing strategy is characterized by low-frequency trading (buy-and-hold approach), long-term (1-3 years), low risks (due to high diversification) and average market return.

    In the past, automated investment management was often regarded as ineffective solution with low personalization. However, innovative technologies, such as Machine Learning and Big Data, change this — modern tools can quickly analyze big and diverse data (including the ever-changing market situation, clients’ transactions and behavior), improve via self-learning algorithms and, as a result, offer comprehensive personalized investment advice.

    OpenAI solutions have boosted another wave of interest in artificial intelligence, and many financial institutions have already started testing the technology for internal use. While JPMorgan Chase is working on a ChatGPT-like software service for their customers to help them select investments.

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    Robo advisors vs human advice

    Since it is highly unlikely for robots to completely replace human financial advisors in the foreseeable future, let’s take a look at the advantages and drawbacks of both approaches.

    Pros of robo advisors

    Low fees. The ultimate benefit of digital advisors that makes them so appealing to both companies and clients is affordability. Annual fees usually amount to one-third of a personal wealth manager’s commission or even less, which equals to approximately 0.2-0.4% of a client’s balance.

    No minimum. Since a wealth manager’s income is directly related to the client’s wealth and they can only support a limited number of customers at the same time, it is unprofitable for them to advise clients with an account balance below a certain threshold. Being infinitely scalable, a digital advice platform doesn’t have such an issue: the more clients they have, the better.

    Real-time analytics and advice. No matter how good a wealth manager is, it is impossible for a human to monitor markets 24 hours a day and advise all clients instantly and simultaneously. In contrast, automated advisors are available 24/7 and react to the market situation, adjusting their recommendations, right away.

    No emotions. In the world of finance, strong emotions are never recommended. Robo advisors select and present investment ideas in a completely unbiased and objective way, without favoring or neglecting any of their customers.

    Fully documented. It is important to track any investment advice given to a client, and with wealth managers, it requires recording all communication channels: emails, phone and face-to-face conversations. With the technology we describe, it is much easier because all advice is provided via a mobile app.

    Cons of robo advisors

    No 100% personalization. If a client has too specific goals, robo advisors might not be the best choice: based on algorithms that suit the majority of investors, they lack flexibility when it comes to unorthodox solutions and individual preferences of a client. In such cases, depending on the client’s balance, a human manager can be more helpful.

    No education or empathy. Automated investment management usually does not provide in-depth knowledge or education on finance, as well as any emotional support in case of stressful events. Such straightforward recommendations and lack of human touch might not appeal to some clients.

    While choosing the most appropriate robo advisory tool  people may take into account various criteria. Some focus on minimum opening deposit requirements, others need customized robo-portfolios or personalized support. Anyway, before you start developing your own product start with market and competitor analysis to find out the needs and expectations of your audience. This is a part of a Zero Sprint option that we offer to our clients, especially for long-term and complex projects.


    A pioneer in robo advisory, Betterment app uses AI algorithms to automate the investment process, helping customers to rebalance their portfolio and reinvest dividends. The application lets users classify investments into short and long-term ones, and invest easily into a sustainable future by using the Socially Responsible Investing feature. The Betterment app has a 0.25% annual fee and no minimum deposit requirement, while the Premium plan is available for a 0.4% annual account fee (free for those with at least $100k on balance). The Betterment also acts as a budget app, helping users with tracking their finances, reminding them about bills due and taxes.


    Another popular automated invested management solution, Wealthfront, charges the same 0.25% annual fee for its services and has a $500 account minimum requirement. Wealthfront’s solution has robo advisor tools for both beginners and experienced investors, helping with financial planning, diversification and tax optimization, including tax-harvesting (reduction of taxes on capital gains). The app uses a questionnaire to identify the client’s risk tolerance and choose suitable asset classes.

    SoFi Invest

    One of the newer companies on the market, SoFi Invest (previously known as SoFi Wealth) was established in 2017 and began business in the field of student loans. The company offers zero commission account management with no minimum, a diverse selection of exchange-traded funds (ETFs), as well as free access to certified human advisors. SoFi is one of pioneers in offering IPO and SPAC IPO investing to its members while traditionally, such access has been reserved for large institutional investors.

    Types of robo advisors

    In fintech, automated advice can be focused either on clients or finance professionals and support different degrees of automation. 

    There are two main categories of client-oriented solutions:

    • Fully automated ones that communicate with the client. Human assistance is provided only in case of technical issues.
    • Hybrid model means that while most investment advice is supplied by the robot, human assistants are always there to explain available solutions in detail and give personalized support.

    Client-oriented robo advisors can operate using one of the following service models:

    • discretionary one that allows a digital advisor to execute trades for a customer, providing fully automated portfolio management.
    • active advisory model means that a customer receives regular suggestions and recommendations from robo advisor but executes trades themself.
    • passive model excludes direct contact with the customer, letting them just browse available trading advice in a dedicated section of the app.

    Another category of digital advice platforms, professional-oriented, helps wealth managers with delivering investment advice and analyzing the market. Usually, they require more knowledge from a user but offer more complex functionality.

    Developing robo advisor for fintech app

    Understanding how customers would be using automated investment management software is the best way to determine its functionality. Let’s see how it can be used in a typical investing app.

    Customer profiling

    Robo advisor becomes quite useful right from the start, collecting customers’ data and understanding their goals. During onboarding, the app requests the user to complete a questionnaire about their basic demography, investment goals, risk tolerance and individual preferences. Additionally, the app can collect data about the client’s past investment decisions, credit scoring and even analyze their social media to obtain a more complete picture of the investor.

    While many apps focus questionnaires on the user’s risk profile and base recommendations on their willingness to risk, we at Surf strongly believe that to acquire a long-time customer it is more important to learn about their personal goals instead of risk appetite. In our investment app concept, for instance, the customer is asked to choose a goal for their investment portfolio.

    Asset allocation

    Using the customer’s profile data and special algorithms, the robo advisor determines an optimal investment strategy. Picking particular instruments is based on a multitude of factors, such as risk analysis of a security, bond credit rating, diversification requirements, portfolio size, tax criteria (while some foreign securities have great potential, high local taxes render them far less profitable), securities in line with customer’s vision (for example, some people don’t invest in companies with unethical practices). 

    Generally, the more criteria considered by the algorithm, the more accurate and personalized a piece of advice will be. For example, for clients with higher returns expectations and of relatively young age the advisor might suggest allocation part of their funds into stocks with high above-average risks, while for the customers aimed at building a retirement portfolio, it is safer to invest heavily into bulletproof retirement savings.

    A robo advisor should also suggest dividing a client’s investments into categories. For example, set up a ‘Retirement’ portfolio category, ‘New house’ and ‘High-risk stocks’. Portfolio categorization not only helps with finance management, but also decreases user’s stress levels: in times of volatility, high-risk categories might become ‘red’, but the safest (and usually the bigger ones) investments would remain ‘green’.


    By analyzing statistical information and market situation, the robo advisor can predict how the client’s portfolio performance would change over time and suggest rebalancing — reallocation of funds from one type of instrument into another. For example, if the government increases the interest rate, bond prices tend to fall, while stocks of the financial sector may see a rise (banks profit from higher interest rates), so a timely portfolio rebalance can save the client’s level of returns or even increase it. In rebalancing, it is important to find an optimal balance between too many operations (which may lead to additional fees, taxes and even losses due to bad timing) and keeping in line with the investor’s profile and their return level expectations.

    To make portfolio rebalance suggestions easier to understand, it is a good practice to present a curve of expected balance growth along with a diagram of proposed allocations.

    Automated purchases

    Since many investors tend to invest funds every month or at other regular intervals, as well as reinvest dividends, the robo advisor should be able to help with these routine purchases and allocate new funds according to the investor’s profile. Automatic Investment Plans are popular strategies for both employer-sponsored (for instance, company’s employees can automatically invest a percentage of their paycheck in an employer-sponsored 401(k) retirement plan) and individual investing (for example, a popular budget application Acorns deducts and invests round-ups from client’s every purchase). 

    Whether the robot executes the trades itself or only sends them to a client for confirmation depends on its type (discretionary or advisory) and the client’s preferences. In both situations, by grouping orders of multiple customers in the same security, the automated investment management can cut down brokerage fees by sending block orders to the market.

    Taxes optimization

    When it comes to investing, taxes on capital gains are one of the permanent factors that diminish investors’ returns. For example, in the US, tax rate on short-term capital gains (from selling an instrument held for less than a year) may be as high as 37%, while tax rate on long-term gains (instrument held for more than a year) can reach 20%, depending on the person’s tax bracket. Using a data-driven approach, robo advisors can efficiently optimize taxation by suggesting the best time to sell securities, setting up a retirement plan to avoid immediate taxes and other options, such as donation or gifting.

    Tax-loss harvesting is another tax-optimization strategy where digital advice can be helpful: the robot automatically sells some securities to deliberately incur losses and offset the client’s capital gains or taxable income. Also, robo advisor’s algorithm can help pick up a similar instrument without violation of IRS wash-sale rule that prevents re-purchasing the same or an identical instrument within 30 days from its sell date.
    As well as optimizing taxes, the digital advice platforms can help with document management, which is a quite tedious process if an investor trades on multiple foreign markets. An easy-to-use section, where tax reports and other documents are stored, is a must for any digital investment solution, and the robo advisor can help navigate and fill out the required documents. For example, when Surf took up a banking app project, we developed a ‘repeat’ feature that allowed clients to create documents using existing templates in just a couple of clicks.


    Starting an insurtech company (a startup that uses digital technology to revolutionize the insurance market) is one of the popular ways to make it in the fintech industry. A great variety of insurance offerings makes choosing the best one a rather difficult process. Robo-advisors can help on every step, from picking the best plan to receiving the payment on a claim. Since the robot has access to the customer’s financial data, it can quickly analyze all insurance offers on the market and select the most beneficial and personalized plan. Then, the robo advisor can help prepare the necessary documents, auto-filling them with details already provided by the user. Finally, the robot can be used in case of insurance claims to speed up and automate the process.

    Summing things up 

    Until recently, automated investment management has been regarded as inferior in quality of their investment advice compared to human advisors. The introduction and evolution of AI and Machine Learning considerably improved automated investment management capabilities for personalized wealth management. Following more progressive fintech startups, large corporate banks also introduce such solutions as a cheaper and more scalable alternative to human employees. The ongoing democratization of the sphere of finance makes digital advisory the best choice for individuals who don’t have deep investment knowledge and large amounts of funds.

    Today, mobile apps are the main way of interacting with clients for many brokerages and trading platforms, while the mobile-first approach is one of the hottest fintech trends. Robo advisor’s integration in the investment or trading software is gradually becoming an essential feature that helps companies attract new clients, assist them with trading and benefit from their gains. How helpful and convenient it is, depends on multiple factors, from choosing suitable technologies to designing a user-friendly interface. We at Surf have over a decade of experience building native and cross-platform mobile apps, and recently have worked with banks, trading platforms and other fintech companies building apps for their clients.

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