Digital Investment Advice - Should Financial Advisors start looking for another job?

1. Introduction

Digital Investment Advice Tools (also called IATs, Robo-Advisors, Automated Investment Advisors, Digital Investment Managers or Digital Wealth Management Tools) play an increasingly important role in the world of investment advice and wealth management.

These tools are already in use for decades in wealth management firms (often integrated in their portfolio management system, like e.g. Triple’A, eXimius, WealthManager…​), but always as tools supporting the advisors and portfolio managers in their tasks, never as client facing tools.

These robo-advisors started however to become client facing about ten years ago, when some Fintechs started to provide automated investment advice directly to customers, with most known players in the market being WealthFront (today approximately $11 billion in assets for about 250,000 customers), Betterment (today approximately $16 billion in assets for about 400,000 customers) and Personal Capital (today approximately $8.5 billion in assets and 19,000 paying users).

Then, about five years ago, some Fintech companies (like SigFig and FutureAdvisor), started to sell white-label Digital Investment Advice products, which could be used by wealth management firms to quickly offer a competitive "robo-advisor" and free up time of their advisors for more relationship-driven and complex tasks.

More recently the large wealth management firms have started to offer their own automated digital investment tools by

• Creating their own digital advice platform
  Most successful examples in this category are Vanguard (approximately $115 billion in assets) and Schwab (approximately $37 billion in assets). Many other large players (BBVA, Deutsche Bank, Merrill Lynch) are working or have recently launched their own tool as well
• Buying an existing Fintech company
  E.g. BlackRock bought in August 2015 the platform FutureAdvisor, Invesco in January 2016 the robo-advisor Jemstep, Goldman Sachs in March 2016 the retirement saving platform Honest Dollar and in July 2016 Legg Mason acquired Financial Guard LLC.
• Partnering with a white label Fintech company
  E.g. UBS and Well Fargo Advisors both partnered with SigFig in 2016 to provide a digital advisor.

The forecasts for assets under management by digital investment advisors are impressive, with a double-digit growth still expected, even though there have been some recent shutdowns (e.g. LearnVest was shut down in May 2018 by Northwestern Mutual insurance, UBS shutdown SmartWealth in August 2018…​).

Furthermore, where competition in the US (and to a lesser extend in the UK) is already fierce, the market is still rather immature in Europe and Asia.

2. What is Digital Investment Advice?

Digital Investment Advice refers to investment advice that is delivered by a computer rather than a human advisor. It combines technology and investment expertise to deliver investment advice at a much lower cost than with a traditional human advisor.

Digital Investment Advice Tools exist in many forms, but typically each tool will offer following functionalities:

• Ask the investor a series of questions to form a good understanding of the client’s financial knowledge, goals, risk appetite and preferences.
• Determine (via algorithms) several investment proposals to align the client’s portfolio with a well-diversified target portfolio, which is in line with those client financial objectives. Usually these target portfolios are built up of ETFs (= Electronic Traded Funds), but more active target portfolios exist as well.
• Rebalance the portfolio when the current portfolio deviates (too much) from the desired portfolio
• Execute the generated trades

3. Types of Digital Investment Advice Tools

Different types of Digital Investment Advice Tools exist. Roughly we can identify 2 categories:

• Client-facing tools: with 2 sub-categories:
  • Fully automated robo-advisor, where advice is fully automated and client has no contact with an advisor. There is only a human available for technical support. This category leads to the lowest investment commissions.
  • The hybrid model (bionic or cyborg model), in which a client interacts both with a human and an automated tool. The advisor can e.g. explain to a customer why a proposed investment is best suited for him, answer investment questions of the customer, fill in the investment profiling questionnaire to determine the investment profile of the customer or offer more complex services, like e.g. financial or estate planning. This model combines the best of both worlds, i.e. provide cheaper, more efficient and 24/7 available investment proposals, while still having an advisor for understanding context and nuances.
• Professional-facing tools: the traditional advisor-centric model, where customer interacts always via his advisor. However, the advisor himself is assisted by digital investment advice tools. Typically, these tools can offer more complex functionality (compared to the client-facing tools), since the end-user will be a trained, expert user.

The current trend in the market is to go towards the hybrid client-facing tools.

Apart from the above distinction, it is important to also make the distinction between the 3 service models, which can be offered to customers. Some digital advisors only offer 1 specific model, while others give the choice to the customer.

• Discretionary: in this service model, the client signs a mandate with the financial institution, allowing the automatic execution of the proposals. This model fits very well with the fully automated robo-advisor, although often human control is built in for special situations (e.g. extreme volatility), where the automated algorithm is likely to react incorrectly.
• Advisory: in this model, we can identify 2 sub-categories:
  • Active Advisory: an advisor will pro-actively contact the customer with interesting investments. The client should however still approve the execution of the order. Since this model is very advisor-centric, usually a "Professional-facing tool" would be used.
  • Passive Advisory: in this model, the financial institution will give advice, but only in a reactive way (i.e. when client asks for it). This model fits perfectly with the hybrid model, where proposals are showed online to the customer, but customer still has the possibility to discuss the proposals with his advisor.
• Execution-Only: in this model, the client does not have an advisor and is fully self-directed. When the customer has filled in his investment profile, it is however still possible to show proposals to the customer. Since the customer will not have an advisor, this fits well with the model of the automated robo-advisor.
  Of course, different gradations between execution-only and passive advisory exist, in which customer is still self-directed, but has nonetheless the possibility to ask questions to an advisor.

4. Market Enablers

As explained in the first paragraph, Digital Investment Advice tools already exist for decades, but only started to become popular and mainstream in the last few years (thanks to the success of the Fintech robo-advisors).
This chapter provides some market trends, which enabled this success:

• There is a growing demand for investment services from less-wealthy, retail investors. Due to the high costs of an advisor, often services of an advisor are too expensive for this group of customers (these customers are even rejected by the minimum balances required by wealth managers). Digital Investment Advice tools provide an answer here by providing good quality investment advice at very low costs (and fully scalable).
• The Financial Crisis led to a loss of confidence in the good practices of the financial industry. Many customers don’t have confidence anymore in the good intentions of their advisor and look for other models.
• The general rise of Fintech companies has generated the necessary publicity and funding for small startups to grow very quickly.
• The recent technological advancements in creating simple and intuitive web-based user interfaces has allowed to leverage on the existing investment advice tool components and build an offering directly for the customer.
• The growth and maturity of the ETF market has led to a broad range of funds, covering almost all asset classes, markets, sectors, geographical regions, themes…​ The usage of such ETF funds simplifies considerably the investment advice algorithm (compared to investments in traditional equity, bonds and mutual funds), which led to most of robo-advisors proposing portfolios filled with these ETF funds.

5. Comparison Digital versus Traditional Investment Advice

With the rise of these digital tools, the debate on the pros and cons between digital investment advice and the traditional advisor-based advice is very active.

In summary, we can identify following pros and cons of Digital Investment Advice:

5.1. Pros

• Low fees due to very low-cost base (no branches, no advisors or reduced number of advisors, high level of automation of all back-end processes…​), making the advisory services accessible to the mass. Typically, fees of robo-advisors are about 1/3 of the fees charged by a traditional advisor.
• Lower entry minimums to be serviced by digital advisor. This allows to acquire customers already very early (i.e. before they have built up their wealth) in their life and allows to attract investors of all income categories. Traditional advisors need to impose this minimum, otherwise (since fee is normally a % of the assets under management), the efforts do not outweigh the received income.
• Scalability: where a human advisor has a maximum number of customers he can manage, there is no such limitation for a digital advisor. Once the digital advisor is setup, there is no limitation to the number of customers it can serve.
• Real-time, instant answers and investment decisions, i.e. in case of market correction an advisor can never call all his customers at the same time, but a digital advisor can rebalance thousands of customers in the matter of minutes.
  Also, portfolios can be tracked on a daily basis to ensure they stay within certain risk thresholds and even the smallest cash deposits can be immediately invested.
• 24/7 availability, i.e. investors have access (via internet and mobile) to their digital advisor at any time (day or night).
• Excellent intuitive user experience, including elements of gamification (improving the "fun-aspect" for the user)
• Service is transparent, i.e. when the investment algorithm is fully explained to the customer, the investment philosophy and provided service is very transparent to the customer. Furthermore, digital advisors use a much simpler fee structure, in contrast to the often very complex and tailored fee structures of traditional advisors.
• Digital advisors analyze data in a non-emotional way, i.e. always selecting the best investment in an objective way. Furthermore, they are not biased, i.e. traditional advisors often receive commissions on certain products they sell. A digital advisor (unless centrally decided to include in the algorithm) will not have this bias.
  Finally digital advisors are never distracted or tired, meaning that risk of operational errors is lower compared to human advisors.
• Advice across multiple customers will become more consistent and predictable. This ensures that all customers receive the same level of service, in contract to human advisors, who tend to favor certain relationships over the other.
• All proposed investments are fully documented and audited, which is very important in today’s highly regulated landscape (much easier than for traditional investment advice where advice is given face-to-face, over the phone, via email…​ meaning a tracking solution is required for each of these channels).

5.2. Cons

• Human advisors can provide an "emotional blanket", which digital advisors can’t, i.e. in case of market corrections, human advisors can better help customers to maintain their calm and explain them that the future will look better, thus avoiding the customer to sell during a correction (which is often the worst time to liquidate a position).
  This con can partially be mitigated by sending tailored messages to customers in case of market corrections.
• There exists no emotional connection (personal touch) between a digital advisor and its customers, i.e. digital advisors cannot give the comfort of an in-depth conversation with a human advisor.
• Digital investment advisors cannot provide investment advice considering the unique facts and circumstances of the customer, i.e. a digital advisor cannot improvise. If the customer’s unique situation is not covered by the profiling questionnaire and/or by the algorithm, the case will not be treated
  This con which is today still significant will become more marginal, when digital advisors provide more advanced profiling methods and are better integrated with other tools of the financial institution.
• Digital advisors typically provide only basic investment services. More complex investment services, like e.g. estate management, still require a human advisor.

6. Challenges

Building a well-performing Digital Investment Advice tool is far from easy (both for Fintechs and banks). Especially the algorithm to determine the desired investment portfolio (derived from the answers filled in the "Customer Profiling" module) and the timing of rebalancing should be sufficiently personalized to the customer’s needs and preferences and robust enough to cope with different market conditions.

Furthermore, with algorithms evolving, the obtained financial returns of different digital advisors will converge. At that moment, the competitive advantage of a digital advisor should come from the user experience and from new innovative functionalities.

The challenge for digital advisors will therefore lie in:

• Defining a state-of-the-art algorithm, which can be easily tuned (based on decisions of the investment committee) to the market trends
• Defining a state-of-the-art user experience
• Easy extension with new functionalities
• Seamless integration of the digital advisor with involvement of a human advisor
• Quality (correct and up to date) of the securities referential and pricing data (any error in this data might lead to wrong proposals of the digital advisor).
• Full automatisation of securities processing (e.g. trade execution)

7. Functionality

7.1. Standard functionalities

A digital wealth manager typically offers following functionalities:

• Customer Profiling: customers should complete a questionnaire, which asks the customer questions about his financial goals, individual preferences, risk tolerances…​
• Investment Selection: determine via an algorithm the desired portfolio, which is optimized to meet the customer’s needs (determined in the "Customer Profiling" step). Afterwards derive propositions from this desired portfolio.
• Rebalancing: (automatic) proposing trades to align the customer’s portfolio with the desired investment portfolio.
• Trade Execution: execution of the proposed trades. This includes all steps a customer should do to convert the proposed trades into real market orders and sending them to the market.
• Portfolio Analysis: with functionalities like portfolio dashboard, valuated positions, performance analysis, alignment with investment objectives, cash flow forecast…​ Since these functionalities are usually already offered by financial institutions in their portfolio management service offering, they will not be further described in this white paper.

Apart from those core functionalities, a digital advisor should also offer supporting functionalities like:

• Visualize securities information, like securities referential information, online market quotes, market research and news
• Live chat with personal human advisor (if available) or with the technical support team
• Educational tools, like links to definitions, articles or newsletters
• Automated email campaigns to inform customers about certain market trends
• Integration with CRM tools to capture all interactions with the customer
• Integration with the account opening process (allowing to open new securities account / investment portfolio)

7.2. Future functionalities

As indicated above, with the market of digital advice evolving strongly and obtained financial results converging, in order to stay competitive, it will be required to offer new innovative functionalities to the customer. This chapter provides a few examples:

• Offer customers the ability to join online investment communities to share data and insights with each other, track others’ progress (e.g. track behavior of the bank’s top-rated investors) and compare their investment decisions.
• Account aggregation, i.e. retrieve a holistic view of all client assets and liabilities and income and expenses and use this information to adjust the investment selection algorithm
• Big data collection and usage of analytics to adjust the investment selection algorithm. Some examples:
  • Collect data based on a customer’s online behavior (e.g. customers who look at their account frequently are often more risk adverse than others)
  • Collect data from the Personal Financial Management module (i.e. the mapping of all income & expenses on accounts to categories)
  • Collect data of past investment decisions
  • Collect data from outside sources like social media
  • Collect data gathered when selling other financial products (e.g. credit scoring, insurance request forms…​)
  • Cluster customers, using the above collected data and machine learning algorithms. This allows to identify "People (Investors) Like Me", which allows to propose to a customer investments, which were already perceived successful by similar people as the customer.
• More advanced performance analysis functions, like performance attribution and performance/risk analysis
• More advanced risk management, with functionalities like portfolio VaR calculation, Monte Carlo simulations, what-if scenarios (e.g. oil price fall or global recession), crisis detection radar…​ This should allow a customer to visualize online the impact of market fluctuations on his investment portfolio and long-term investment objectives.
• Simulations that provide insights of the impact of doing certain investments or cash/securities deposits/withdrawals or of pursuing a different investment strategy. This functionality could also be used for simulating the behavior of the digital advice tool for prospects.
• Provide additional services linked to the long-term goals of the customer, like insurance services, health care services, holiday reservation services, searching houses…​

In the next sections, we will describe in more detail the 4 main components of a digital investment advisor, i.e. customer profiling, investment selection, rebalancing and trade execution.

8. Customer Profiling

The first step for a digital advisor is to perform the customer profiling, i.e. determine the investment profile and investment scope of the customer based on a series of questions.

Apart from asking these questions, the profiling module should also:

• Resolve contradictory or inconsistent answers. This is done by averaging the answers, taking the most conservative answer or by giving an error message, requesting the customer to correct one of the answers.
• Assess whether customer should be investing and not just save his money on a saving account or pay off debt (e.g. someone with almost no financial cushion or with a very short-term investment horizon)
• Manage periodic reviews of the customer profile

The questions themselves should typically obtain following information:

• General client characteristics (personal information), like age, gender, profession, civil status, tax status, residence country
• Financial Situation:
  • Assets (liquid and non-liquid)
  • Liabilities (mortgages, debts…​)
  • Income (professional income, rent income, capital income…​)
  • Expenses (debt repayment, rent…​)
  • Liquidity needs
• Investment scope, i.e. which cash and securities accounts should be considered by the digital advisor
• Financial Goals: investment goals (e.g. buying first/second home, holiday, pension…​) and investment time horizon
• Investment experience: educational level, knowledge and experience in different investment products…​
• Risk Willingness: determine the customer’s willingness to take risk (i.e. his attitude towards risk). Typically, this part will question the customer for the maximum loss percentage he is willing to absorb. This can be done by asking this information directly to the customer, by proposing the customer a few scenarios or hypothetical questions or by looking at past decisions of the customer (if available).
• Individual Preferences: preferences for certain investment products or specific ethical (e.g. no weapon or tabaco industry), legal (e.g. certain companies in which customer might have insider trading information) or religious (e.g. Islamic banking) restrictions.

From these answers the system can derive:

• Monthly net income, i.e. calculate the monthly total income and subtract the monthly total expenses
• Risk Capacity, i.e. the investor’s ability to take risk or absorb loss. Typically, a function of an investor’s time horizon, liquidity needs, investment objectives and financial situation. The risk willingness should be capped to the risk capacity.
• If investing is appropriate for the customer or if he should stick to saving. This is typically determined by the monthly net income of the customer and the amount of available assets and the customer’s investment horizon.
• The proposed investment profile, i.e. one or more parameters which will be used by the "Investment Selection" module to determine the desired investment portfolio.

9. Investment Selection

After the investment profile of a customer is determined, the module "Investment Selection" will determine

• the desired (= target) portfolio for the customer and/or
• the proposed buy and sell orders specifically adapted to the customer.

This module is the heart of the digital advisor and contains the specific algorithm to determine best-suitable investments for the customer. The module should furthermore provide a clear explanation to the customer, why a specific investment is proposed (i.e. is currently best suited for the customer).

A state-of-the-art algorithm should consider following aspects:

• Determine the As-Is situation of the investment portfolio:
  • Is the portfolio in line with the investment profile (i.e. in line with all answers provided by the customer in the "Customer Profiling" module)?
  • What is the diversification of the portfolio?
  • What is the market risk of the portfolio?
• Determine the investments to be included in the To-Be situationof the investment portfolio:
  • Which investments present in the As-Is situation should be removed from the investment portfolio?
  • Which investments should be added to the investment portfolio?

The investments to be included in the To-Be situation are determined by:

• Asset Allocation targets, i.e. the targets defined by the investment committee in the different asset categories (e.g. asset classes, regions, sectors, rating of bonds, duration of bonds…​). This includes indirectly any recommendations made by research departments on region/country, sector, asset classes.
• Security risk analysis (liquidity risk, credit risk, market risk…​), i.e.
  • Securities which have a minimal risk by themselves, e.g. minimizing the VaR or Index Tracking Error.
  • Securities which minimize the overall portfolio risk, i.e. by introducing securities with negative covariances and via back-testing and Monte Carlo simulations.
• Market Research, i.e. stock picking done by the research department of the bank or based on e.g. MorningStar rating for funds.
• Bond credit rating (S&P, Moody’s and Fitch), e.g. policy of the bank might be not to sell bonds with a S&P rating lower than "CC"
• Diversification requirements at security level, issuer level, sector level and country level
• Size of the portfolio, i.e. large portfolios allow to invest more in individual lines, while smaller portfolios best invest in funds, in order to have an optimal consensus between maximizing diversification and minimizing transaction and management costs
• Pricing, Fee and Tax criteria, i.e. minimize bid-ask spreads and optimize the level of fees (e.g. transaction costs, annual management fees…​) and taxes paid (i.e. optimize tax efficiency)
• Securities appropriate to the customer, i.e. securities in which customer has knowledge and experience
• Securities in line with the customer’s profile, i.e. in line with his risk profile or maximum risk drawdown (e.g. do not invest in derivative products if defensive risk profile), investment horizon (e.g. do not invest in long-term product if customer has a short-term investment horizon for his money) and preferences (e.g. do not invest in securities considered to be unethical by the customer)
• Securities in line with past decisions of the customer, i.e. based on collected investment history of the customer only propose products in line with this. E.g. if customer is clearly a domestic investor, don’t start proposing all foreign securities.
• Propose buy and sell recommendations based on peer investment decisions (investors the customer decided to follow).

Note: Most client-facing digital advisors work exclusively with Exchange-Traded Funds (ETFs). This allows to simplify the security selection process, since some of the above criteria are not applicable to these securities.

High level these algorithms should consider the "Pyramid of Needs" from Maslow, i.e. they need to ensure in descending order of priority following investment needs:

• Survival Money (Physiological): ensure that typically 6 months of the customer’s monthly expenses are available on a fully liquid cash account (i.e. account in home currency)
• Capital Protection (Safety Net): ensure the customer can deal with any unexcepted expense that might happen (e.g. car accident, illness, loss of job…​). The digital advisor should ensure that the safety cushion is protected, but also that the purchasing power of the cushion is guaranteed (i.e. not impacted by inflation). Typically, this layer will be invested in a few insurance products and high-quality obligations in home currency.
• Financial Freedom (Love/Belonging): generate extra income from assets to be used for enjoyment and fulfilment. This is extra money, which should not be used for the basic needs or as safety net. Typically, this money will be used for holidays, buying a 2nd house…​ Therefore, it will be invested over the medium term in distribution funds or obligations, which are of lower quality (but no high-yield bonds) or foreign currency obligations.
• Capital Growth (Esteem): grow the assets of the customer, so the customer has more assets in the future. This money will typically be invested for the long-term, so (capitalization) funds and equity are the logical choice here.
• Wealth (Self Actualisation): this layer is all about introducing rules to the investments, which provide a better feeling to the customer. Typical examples here are not investing in weapon or tabaco industry or investments in the green-energy sector or non-profit social sector. It also includes plans to use the customer’s investments for charity (if supported by the digital advisor).

10. Rebalancing

This module will trigger the actual comparison of the As-Is and To-Be (target) investment portfolio and generate the necessary buy and sell orders. Apart from the automated triggering to realign the portfolio, this module should also support:

• Periodic investments (auto investing), i.e. invest automatically a pre-defined amount from an account at a pre-defined frequency (i.e. investment plan)
• Investment of new deposits (cash or securities) done by the customer
• Request of a customer to free up cash for cash withdrawal. This can be a one-time ad-hoc request of the customer or an automated request to free up a pre-defined amount at a pre-defined frequency (e.g. to complement the customer’s pension)
• Dividend and Interest reinvestment, i.e. automatic reinvestment of the received dividends/interests.
• A gradual buildup of the investment portfolio to the target portfolio for new customers or customers who had a radical change in their investment profile. This to avoid exchanging a too high percentage of the portfolio’s positions (for other positions) on the same date (thus increasing the risk of a bad timing of the rebalancing).

The automatic triggering of the rebalancing process should find the right compromise between:

• Keeping the investment portfolio as best as possible in line with the desired investment portfolio (and consequently with the customer’s investment profile)
• Avoiding too many rebalancing operations, which would result in excessive fees and taxes (thus reducing the net return of the investments).

This compromise is hard to find, especially when considering:

• Avoid rebalancing during sharp temporary market movements, by identifying them properly
• Avoid consistently selling outperforming securities, i.e. if the desired investment portfolio is defined by fixed percentage in target securities, there is a tendency to do so. E.g. if target portfolio proposes 5% in equity A, but equity A outperforms all other securities in position, the portfolio will soon have a position of larger than 5%. Without extra measures, the outperforming position A would be partially sold to get back to 5%. This adverse effect should be compensated, while still taking profit in time and avoiding too large exposures in 1 position.
• Use cash flows (i.e. deposits and withdrawals of the customer or received dividends and interests) as best as possible for rebalancing, since cost impact is lower (i.e. only 1 buy or sell transaction, rather than 2 in case of an arbitrage). Of course, cash flows should be sufficiently high, to avoid creating too many small orders.
  • All cash inflows (i.e. client cash deposits and dividends/interests) are used to purchase underweighted asset classes / positions.
  • All requested cash outflows are created by selling over-weighted asset classes / positions.
  • Of course using only the cash flows to keep a portfolio in line, is only possible when misalignment is small or when the customer has a lot of cash flows.

11. Trade Execution

Once the orders are generated by the rebalancing algorithm, it is required to execute those trades.

Since the digital advisor will only propose orders which are suitable within the customer’s investment profile, the generated trades are in principle suitable. However, if the customer or employee can modify the proposed orders, it is still required to perform a suitability check, to see if the resulting portfolio is in line with their investment profile, or at least that the trades do not worsen the suitability (e.g. if portfolio is not suitable at the start, the created trades might result in a portfolio which is still unsuitable, but improves the situation).

Afterwards the customer or employee must input the details of the trades for execution. This consists of providing:

• Order details, like order type (market, limit, stop or stop-limit order), limit/stop price, limit date…​
• Cash account selection (if not automated)
• Securities account selection (if not automated)
• Securities market selection

Note: The digital advisor should (partially) automate the cash and securities account selection, especially to optimize taxes (e.g. taxable and tax-deferred accounts).

Afterwards an order confirmation form (containing a simulation of the expected fees and taxes for the orders) should be generated and signed by the customer.

The next step is the actual sending of the order to the market. In case of a digital advisor for a discretionary portfolio, there will first be a bundling (grouping) of the orders (with orders in same securities of other customers), allowing to send the order as a block order to the market (thus lowering brokerage fees for the bank and ensuring that all customers in the same discretionary service receive the same execution price).

Once trades are sent to the market, it should be possible to request an overview of the pending orders, with a possibility to cancel or modify an order (if not yet executed).

Note: Since suitability of the proposed trades is done for all proposed orders together, it might be necessary to limit the possibility of cancelling a pending order (i.e. cancelling all proposed orders or none). Otherwise it is possible that the resulting portfolio will not be suitable.

12. Opportunities for banks

Where Digital Investment Advice was mainly a business of Fintech companies up to a few years ago, more recently banks have started investing heavily in this technology (i.e. by buying an existing digital advice Fintech company, by building their own digital advisor or by partnering with an existing Fintech company).

The consensus is that if banks can deliver digital investment advice platforms, which have similar functionality and user experience as the FinTech companies, banks should easily be able to outcompete the Fintech companies for several very good reasons:

• Banks already have a well-known brand
• Banks already have a large customer base, with often a lot of underserved customers, who don’t receive the investment advice they would like to receive, since they don’t meet the minimum asset amounts currently required for this type of service.
• Banks have a large number of distribution channels (contrary to the Fintechs)
• Banks can build on the existing investment knowledge and research departments, to define the optimal parameterisation for a digital advisor, given the present economic climate.
• Banks can use their existing well-trained investment advisors to complement the digital advice, e.g. to tailor to specific situations of customers, to offer additional more complex services (e.g. estate planning) and to explain to the customer why a specific investment proposal (calculated by the digital advisor) is best suited for him.
• Banks have existing economies of scale for cheap execution of trades
• Banks have existing securities information data feeds, which can easily be integrated in the digital advice platform.
• Banks can integrate the digital advisor with their other financial services and products, e.g.
  • Integration with Personal Financial Management and Saving Goals Management modules, e.g. automated suggestion to free up cash from the investment portfolio, if budget plan shows that there will be an upcoming shortage in liquidity.
  • Management of corporate actions with choice, e.g. show alerts in digital advisor on positions with upcoming corporate actions. When clicking on alerts, customer should be able to directly input his choice. The digital advisor could even do suggestions for the best choice for the customer’s situation (e.g. in case of choice dividend, advisor might suggest opting for securities dividend if position should be increased or to opt for cash if liquidity position is currently too low)
  • Offering life insurances as investment product
  • Offering Lombard Credits, i.e. granting a credit to the customer, by pledging securities positions, as an additional liquidity mean or to leverage the investment return.
  • Pre-filling of the investment profiling questionnaire, based on the info available in the Personal Financial Management module or in past credit or insurance requests, CRM system…​

Once banks have positioned a state-of-the-art digital advice tool, it will provide them a lot of commercial opportunities:

• Increase number of customers to which investment advice can be offered (without increasing the number of human advisors)
• Better compliance with regulations, i.e. improved alignment of the customer portfolios with their investment profile, more transparency to the customer on the investment process and the costs and a better audit trail of all proposed investments.
• Improved customer service, e.g. by 24/7 real-time availability of digital advisor
• Easier central enforcement of a common investment strategy, resulting in
  • Improved overall investment results for the customers
  • Easier customer marketing campaigning (since customers will be better clustered)
  • Smaller securities universe (i.e. smaller number of different securities), lowering operational costs (e.g. fees to data providers, costs for managing corporate actions…​)

13. Impact for banks

Digital investment advice offers a lot of opportunities for banks, but certainly also several challenges for traditional banks:

• The role of a traditional investment advisor will change:
  • Rather than making investment choices himself, the advisor’s primary focus should become managing the customer relation and explaining the customer why an investment proposed by the tool is the right one for him. The advisor will also play an important role in filling in the "Customer Profiling" module, since human advisor might identify certain needs or assets, on which the customer himself might not think off.
  • An advisor, liberated of a lot of the investment related activities and administration, should be able to manage larger amounts of customers.
  • Since customers will be able to see proposed investments directly online on their mobile or internet banking, the contact between the advisor and the customer will also shift more to the digital channels.
  • The advice role of an advisor will shift to matters which are (highly) emotional, e.g. wealth transfer to the next generation, providing for a disabled child who can’t support himself…​
• The IT applications of the bank will require a significant investment, allowing to offer similar functionalities and user experience as the innovative Fintechs in this space and to offer a fully integrated solution with the other financial services and products offered by the bank.
• Digital investment advice will further reduce the fees a bank can ask for investment advice. To cope with this loss in revenues, the bank should offer their digital investment advice services to the retail segment (allowing to compensate this loss in revenues by increasing the customer base to which advisor services are offered) and provide new innovative investment services.

14. Conclusion

The market of digital investment advise is slowly maturing and consolidating, but growth opportunities are still impressive.

Banks should however not copy/paste the Fintechs but compete from their own strength. Via a hybrid client-facing model, which is well integrated with other bank product and service offers, traditional banks can provide a much more competitive offering than any Fintech in the industry.