sankeysolutions

Digital transformation is radically impacting the financial sector being information and service-based industry. The financial advisory business is no exception: as demand continues to increase due to various aspects such as geopolitical uncertainty, ultra-low or negative interest rates, and increasing life expectancy, robo-advisors are becoming an essential part on how services are provided and delivered to clients.

Traditionally financial advice is provided by a financial advisor based on a client-specific investment policy statement which includes his return expectations, liquidity requirements, time horizon, tax concerns, regulatory and legal factors, ability, and willingness to take risks as well as any other unique circumstance. Upon final agreement with the client, the investment policy statement builds the basis for all investment decisions of the client’s assets. The investment portfolio is monitored on an ongoing basis and rebalanced if required. Its performance is reported to the client in a compliant and timely manner.

1+ Trillion AUM by robo-advisors and growing

The robo-advisory market grew out of the 2008 financial crisis as small investors looked for wealth managers who charged lower fees, at a time of historic low interest rates on savings. According to Statista, AUM at robo-advisers surpassed 1+ trillion and are expected to experience strong growth over the next years as they can be a great solution for various types of investors – from beginners not having yet the financial knowledge to professionals lacking the time to actively manage their wealth.

Different use of automated, algorithm-driven financial planning services

Robo-advisors are digital platforms providing automated, algorithm-driven financial planning services with minimal human intervention. They provide customers with tailor-made services with a digital point of contact and a standardized system in a compliant and affordable manner. Information about their current financial situation as well as goals are collected and the data is used to offer advice and invest automatically a client’s assets. This allows us to benefit from passive management lower fees with the advantages of more adaptive and active asset allocation than just pure indexing.

Robo-advisors can have different forms. They can be made directly available as a tool to the end user and, based on her/his specific investor profile, give him either investment recommendations or letting the robo-advisor do the asset allocation independently. Alternatively, it can be a tool for the financial advisor himself to support him both in terms of speed and quality, the preparation for meetings with clients, optimally leverage the information exchanged during the appointment or increase the number of portfolios she or he can effectively manage. The robo-advisory platform can also be used as a way to ease interactions between the advisors, the portfolio managers and the customers. The best robo-advisors offer an easy client onboarding process, customized and suitable portfolio management services to reach her/his financial goals, low fees, attentive customer service, comprehensive client education and high security standards.

Main advantages for financial advisory businesses

From streamlining operations to enhancing the user experience, here are some of the main advantages financial advisory businesses profit from when using robo-advisors:

• Low costs and low account minimums: the costs of a robo-advisor are around a 1/3 to 1/2 compared to the costs of a traditional advisor and allow high economies of scale. It enables to serve clients who have been historically difficult to serve at all or to offer them more sophisticated investment practices. This includes for example households with relatively lower income or younger individuals with lower investable funds.
• Automated processes: automating processes reduces operational risks and saves time. Robo-advisors offer clients tailored services while enabling individuals to widen their scope, freeing them from certain basic tasks for them to focus on more complex issues.
• Self-service digital distribution: the virtual aspect of the services increases the accessibility and availability to 24/7 from anywhere with an internet connection and without the need of a physical presence.
• Higher user experience and data analysis: client demands for cutting-edge technology are ever growing. Millennials which constitute the largest group in the labor market are tech savvy while the next generation, Gen Z which is entering the labour market, is considered tech native. Further, a significant growth in tech adoption is observed among older generations. Robo-advisors allow investors to invest in a range of different asset classes conveniently via mobile phones or web applications. Furthermore, they provide full access to portfolio management tools and performance results which are completely transparent and easy to understand. The ever growing amount of data (big data) exceeds the analytical capabilities of humans while robo-advisors, if enhanced by new technological developments (e.g. AI), can provide better and more tailored offerings.
• Reducing behavioral biases in the investment process: behavioral biases lead to suboptimal decision of investors. These biases may be categorized as either cognitive errors (resulting from faulty reasoning) or emotional biases (resulting from reasoning influenced by feelings). Robo-advisors are not subject to these biases and could even profit from them happening in the financial markets, if developed correctly.

The Sankey’s approach to robo-advisory

At Sankey Solutions, we work on projects for several financial advisors and provide them with tailor-made solutions based on their clients’ needs. With our very agile approach in designing, building and testing, we help building successful and flexible robo-advisor platforms to achieve highest customer satisfaction and profitability. Our engagement can vary based on individual requirements and set-ups: it spans developing the full range or only components, from building a robo-advisor from scratch to designing and developing a front-end using APIs to connect to existing third-party providers, for B2B and B2C use and accessible as multi-channel service through SOA services (service-oriented architecture, web, mobile and cloud). Here are few examples of some of the main components of a robo-advisory our team is able to provide:

• • User interface: with client expectations rising the focus has long shifted from product-centricity to user-centricity. The user interface needs to be intuitive, accessible across all channels and devices, easy to interact with, visually appealing and responsive. The overall experience needs to show your clients that you know them and what they value, that you will ensure their individual needs are matched and you will ultimately reward them. Further, the user interface is customized with brand design, cultural behaviors and language for users to experience the brand

             Components include:

• • Client onboarding: it needs to move away from the onerous task of making clients fill out forms to transfer and set up accounts. An omnichannel onboarding process needs to be offered and should be based on a storytelling approach tailored to the user to create a strong first impression.
  • Client profile building: the regulatory compliant investor profile can be created using digital tools based on gamification aspects, investment education scorecards or predictive and dynamic questionnaires. Combining big data with artificial intelligence methods offers new ways of gathering information and creating the investor profile. It could include virtual, digital or voice assistants interacting with users with their natural language.
  • Investor dashboard: market data as well as research information can be presented. It enables the client to monitor the development and risk parameters of her/his portfolio as well as individual financial instruments (in real-time and historically) with user-friendly analytical tools. Visualization tools tell users the story of their finances by representing the data in an interactive, attention- grabbing and easily digestible form. It can be built as a separate application or integrated in an existing website or app.

• Asset allocation, rebalancing, monitoring and reporting: a cutting-edge platform which is highly scalable and API-ready guaranteeing easy connectivity to third-party services (e.g. data providers, banks, custodians, trading venues) is at the centre of any robo-advisor. An analysis of the existing IT architecture to evaluate the degree of potential integration should be the starting point. Regarding the investment aspects various solutions are possible.
  • Portfolio construction: the range of possible algorithms making the investment decision across different asset classes is very wide – from simple and more passive (e.g. based on modern portfolio theory) to complex and more active based on state-of-the-art machine learning techniques and alternative data. The algorithms require a very disciplined approach in development and rigorous testing. They can be used in different ways:
    • The robo-advisor makes recommendations and serves as a decision support system to identify opportunities and matching them with the investor profile.
    • The robo-advisor performs asset allocation and rebalancing on its own, but requires some human intervention to take action, from a portfolio manager or a committee validation.
    • The robo-advisor is in full-blown automatic mode. It can allocate a fixed amount of capital or use a fixed monthly payment to implement a pre-defined strategy. It can provide the investor with the possibility to choose between several themes to customize her/his portfolio with special investments.
  • Rebalancing: It ensures that any deviations from the target portfolio, break of restrictions or change in client preferences are identified and determines necessary transactions or submits appropriate recommendations. The process can be both rule-based with a fixed regular frequency and event-based with alerts triggering the system when necessary. This event-driven feature is of prime importance in order to do the necessary reassessment of investor profiles and soliciting human intervention when market data or performance demands it. It can also include liquidity modules controlling the correct implementation of capital withdrawals and capital injections while managing risk as well as tax-loss harvesting.
  • Execution: depending on the business model, trade orders can be generated by the user or automatically by the robo-advisor. After built-in checks these can be automatically shifted to back office for further processing or directly routed to the selected trading venue for execution. Buying and selling of financial products generates costs for the clients which need to be minimized. To reduce commissions, slippage (price change between signal and order execution) and market impact (change in price of an asset caused by buying/selling of that asset) an execution module can be built to.
  • Reporting: automated report generation allows maximal flexibility with masses of reports generated within a short period of time or customer-specific ones ad hoc to keep clients informed in a timely and compliant way (e.g. Global Investment Performance Standards).

• Data protection and cybersecurity: the sensitive and personal nature of client’s information that robo-advisors are entrusted and work with on a daily basis requires the implementation of the highest security and encryption standards. Processes and strategies to prevent, detect and respond to cybersecurity threats and vulnerabilities are an absolute must to protect client data, wherever it is stored or accessed from, any communication and to be compliant with all legal as well as regulatory requirements.

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