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Robo-Advisor with Python

By Aki Ranin
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  1. Free Chapter
    Chapter 1: Introduction to Robo-Advisors
About this book
Robo-advisors are becoming table stakes for the wealth management industry across all segments, from retail to high-net-worth investors. Robo-advisors enable you to manage your own portfolios and financial institutions to create automated platforms for effective digital wealth management. This book is your hands-on guide to understanding how Robo-advisors work, and how to build one efficiently. The chapters are designed in a way to help you get a comprehensive grasp of what Robo-advisors do and how they are structured with an end-to-end workflow. You’ll begin by learning about the key decisions that influence the building of a Robo-advisor, along with considerations on building and licensing a platform. As you advance, you’ll find out how to build all the core capabilities of a Robo-advisor using Python, including goals, risk questionnaires, portfolios, and projections. The book also shows you how to create orders, as well as open accounts and perform KYC verification for transacting. Finally, you’ll be able to implement capabilities such as performance reporting and rebalancing for operating a Robo-advisor with ease. By the end of this book, you’ll have gained a solid understanding of how Robo-advisors work and be well on your way to building one for yourself or your business.
Publication date:
February 2023
Publisher
Packt
Pages
250
ISBN
9781801819695

 

Introduction to Robo-Advisors

Welcome to the world of Robo-advisors. My name is Aki Ranin, and I’ll be your guide on this journey into digital investing. I started a Robo-advisor company called Bambu in 2016, and have been working on Robo-advisor solutions ever since. I hope my experiences will be of use to you on your digital wealth journey.

In this very first chapter, I’ll provide an overview of Robo-advisors. We will then understand why they were created, and why people use them. By the end of this chapter, you’ll have a good understanding of why Robo-advisors exist.

Throughout this book, we’ll proceed to tackle the main questions you might have while embarking on your own Robo-advisor project, from the overall strategy to the key capabilities demonstrated in Python.

In this chapter, we’re going to cover the following topics:

  • What is a Robo-advisor?
  • How do Robo-advisors work?
  • What is the history of Robo-advisors?
  • Why are Robo-advisors an essential part of the wealth management industry?
 

What is a Robo-advisor?

Today, Robo-advisors take many shapes and forms, but fundamentally, we are talking about a digital investment platform. An individual investor, such as yourself, uses a Robo-advisor to manage investments on your behalf. While there is no formal or legal definition for a Robo-advisor, a typical Robo-advisor will help you make investment decisions using a digital app or website. To make investments, you will be required to transfer real money into an account managed by the Robo-advisor. Consequently, that money will be placed into some form of investment product, most often into an investment portfolio of Exchange Traded Funds (ETFs). While in certain scenarios it may be possible to use other products, such as stocks or mutual funds, ETFs are the main products powering Robo-advisors due to their low cost, diversification, high liquidity, and daily price transparency.

Such a seemingly simple tool is helpful to investors for several reasons:

  • Access: Traditionally, to make investments, you would have to have a physical interaction of some sort with a financial institution. Initially, this would be done by walking into a branch office, but later by getting in touch with such an institution over the phone or via email. Either way, the inconvenience of these interactions is greatly improved by digital tools such as apps or websites. Further, this access was traditionally limited to the wealthy. To justify a human financial advisor spending time on a customer to manage their investments, significant fees had to be incurred by the customer. This is equally true today, and due to inflation, the time of a professional investment manager has never been more expensive. Further, this cost, which was a percentage of assets, meant that to open an account, you had to start with large sums of investible cash – up to 7 figures for premiere advisors from private banks. Most Robo-advisors have minimum account sizes of just a few hundred dollars, making them accessible to regular people without huge existing savings. In between, some banks and wealth managers may offer so-called hybrid advice, which combines digital platforms with limited human management.
  • Convenience: While anyone could learn to invest on their own, most people choose not to. If you’re a busy professional, or simply have better ways to spend your time than reading annual reports like Warren Buffett, then you don’t have the time to not only research the market but learn the tools of the trade used by professional investors. Apps such as Robinhood have made it easy to make investments, but at the end of the day, are you comfortable making those decisions on your own? If you stick with index funds, then which ones do you buy, and in which ratios? Even simple investing involves a huge amount of decision-making. Robo-advisors simplify the process of investing by abstracting away things such as portfolio and order management and instead ask you about how you feel about risk. The rest is taken care of on your behalf.
  • Cost: Robo-advisors typically charge a small percentage of your total assets on the platform as an annual fee. Compared to traditional investment advisors, who might charge as high as a few percent per year at the high end, or typically around 1%, a Robo-advisor might charge you a fraction of a percent. This is, again, largely driven by automation – there is simply less human cost required to manage your account. On paper, if you already know what you’re doing, you could save even more by building a portfolio of ETFs on a low-cost online broker. It just means you will have to also invest the time to track performance and perform rebalancing, and that time is money too. To further justify their fees, many Robo-advisors offer additional conveniences such as tax reporting and optimization.
  • Psychology: If you’ve never invested before, you may not yet be familiar with this problem. This has been an area of research for decades, and there are many known traps that investors fall into when they manage their investments. These include the sunk cost fallacy and the loss aversion bias. Humans aren’t all the same, but all of us have our own set of biases and quirks that make it very challenging to remain objective when it comes to making decisions about money. The benefit of a Robo-advisor in this regard is that it simply removes a lot of this decision-making from you, instead relying on compound interest, some simple math, and time to produce a return on your investment.

These are just the fundamental principles behind the design of the first generation of Robo-advisors. Many of these platforms now also offer other services and products, such as debit cards, loans, and the ability to trade single stocks and crypto. Over time, your financial life may increasingly revolve around your Robo-advisor.

Now that we have an idea of why Robo-advisors were created, we should look into how they work, and the various components that are required to build one.

 

How does a Robo-advisor work?

Our ultimate goal is to build a Robo-advisor, so we must begin to unpack the concept into its constituent parts. We will dedicate lots more time to this question in Chapter 2, What Makes Up a Robo-Advisor?, and beyond, but to set the stage, let’s establish some basics. The core features of any Robo-advisor include:

  • An app or website user interface
  • Questionnaires for profile information, risk appetite, and Know Your Customer (KYC)
  • Portfolio modeling, construction, and recommendation
  • Automated account opening, management, and transfers
  • Automated order management, execution, and rebalancing
  • Performance modeling and monitoring
  • Reporting and statements

Fundamentally, what makes a Robo-advisor a Robo-advisor is the element of automation. It’s not simply making investing digital, as that has been done before and is being done today. If there are just humans on both sides of the screen making all the decisions, then it’s not considered a Robo-advisor. Mind you, you can have something called a hybrid Robo-advisor, which is just to indicate that there are different degrees to which this automation can be done. Initially, the plan was for Robo-advisors to be fully automated. Effectively, the customer using the Robo-advisor would be interacting with nothing but technology and algorithms making investment decisions. The later addition of hybrid implies a higher degree of human involvement in the form of a financial advisor. Both flavors of Robo-advisors continue to exist and thrive today.

The core investment decision being made is what to invest in. Such questions are traditionally highly regulated by government entities whose exact roles and guidance vary by country. This guidance has been clarified over the past decade as it relates to how Robo-advisors are allowed to operate in their decision-making. For example, you might imagine that some fancy artificial intelligence is making the investment decisions inside of a Robo-advisor. I used to get that question a lot, myself. The regulations tend to forbid that explicitly in favor of clear rules on how investment decisions must be made based on risk scoring. The most common form of risk scoring is a simple questionnaire. Depending on how a customer answers this questionnaire, they will be placed into conservative, moderate, or aggressive investments. These terms simply indicate the amount of risk a customer is willing to accept when making investments and is then the basis for the Robo-advisor allocating customers to specific investments matching that risk score.

We’ll get into all of that in much more detail later when we get hands-on, but before that, let’s go back to the beginning to understand how this all started.

 

Origins of the Robo-advisor

The term Robo-advisor has become quite ubiquitous in the past decade since digital investing has become mainstream. During the COVID-19 pandemic in particular, amid market turmoil, the popularity of investing reached new highs. While most of this newfound attention was directed toward trading tech stocks on platforms such as Robinhood in America, it was also a record period of growth for many Robo-advisors. During the peak frenzy, Robinhood reached a record one million downloads in a single day (Haverstock and Konrad). Robo-advisors may have not yet reached such levels of excitement among retail investors, yet after more than a decade of steady growth globally, Robo-advisors are here to stay.

The term Robo-advisor is both helpful and misleading. There are no robots involved, even if automation of the financial advisor is implied. The exact origin is not known, but the earliest reference comes from a financial journal article in 2001 (Kane). The first platforms we would call by the term only emerged in 2010, in the wake of the financial crisis and riding a new wave of excitement for financial technology (Stein). In many ways, the Robo–advisor was inevitable. Like any other industry, the wealth management industry was due for digital transformation. Any process mainly driven by humans and paper is bound to be disrupted by digital platforms looking to optimize time and cost.

Now, let’s review the path Robo-advisors have taken from the early days, and where they seem to be heading today.

 

Evolution of the Robo-advisor

The first two Robo-advisors were Betterment and Wealthfront. They both started in 2010, and for at least 5 years, they were the main two actors responsible for starting a new industry. Their marketing was consistently aimed at the next generation of would-be investors: the millennials. Among the incumbents, this was seen as the wrong strategy. Millennials simply did not have the assets, which were largely held by their parents and grandparents. Nevertheless, the users and assets of both platforms kept climbing year after year.

Eventually, many of the incumbents, such as Schwab and Blackrock, entered the market with Robo-advisors and have since overtaken these pioneers in sheer Assets Under Management (AUM). Yet the role of these two start-ups cannot be overstated. Many Robo-advisors operating today have copied their approach, marketing, portfolios, and user experience directly from these two platforms. At the beginning of 2022, UBS announced it had acquired Wealthfront for $1.4 billion to focus on millennials and the Gen Z that came after them (UBS). However, this acquisition was later terminated in September 2022 due to pressure from regulators and shareholders (Reuters).

Let’s briefly wind back the clock and examine how we’ve arrived in a situation where Robo-advisors are being adopted worldwide and becoming integrated into the suite of basic financial products available to most consumers alongside credit and savings.

From consumer platforms to B2B

My journey with Robo-advisors started in 2015 in Singapore, where I was working as a software consultant at the time. Many of my clients were financial institutions, and there was a tangible hype building around this idea of Robo-advisors. The question on everyone’s mind was, would Silicon Valley startups come across the oceans to challenge the traditional distribution networks operated by the major banks across Asia, or would local competition emerge? The term used for this type of phenomenon is disruption, and the people in charge don’t like it. This forced the existing players to evaluate whether they should be building platforms and pre-empt any new entrants from stealing market share.

From this hype, it gradually became clear that Robo-advisors were not a separate category of financial service. They represented the digital transformation of the industry, which was still largely operating in the world before the internet. Major banks only offered wealth management services through advisors to affluent or high-net-worth clients. At best, retail clients were offered high-priced online brokerage services with terrible user experiences. This combination of factors created the need for Robo-advisor platforms, such as my company Bambu. Some of the world’s largest banks might have the appetite and budget to dedicate a team for 5 to 10 years and build their own Robo-advisor from scratch, but what about the rest? Since 2016, companies such as Bambu, InvestCloud, and WeInvest have been offering technologies and services to financial institutions looking to launch Robo-advisors around the world.

From America to the rest of the world

If the first Robo-advisors were launched as early as 2010 in America, why did it take so many years for them to spread to the rest of the world? If anything, the choices for retail investors outside of America are far more limited. Even if you know what you’re doing, many countries do not have low-cost online brokers that offer access to low-cost ETFs to build a portfolio. When I lived in Singapore, in 2016, my bank would charge me $15 for every trade, which isn’t uncommon in many places even today. This goes a long way to explain the popularity of apps such as Robinhood that offer free trading.

So, why doesn’t every country have a Robo-advisor or several? Why haven’t Betterment and Wealthfront conquered the world as Uber and PayPal have? The simple answer is regulation. Compared to taxis and payments, which are also regulated industries, wealth management is highly regulated. Not only that, but the regulations vary greatly between countries. What is allowed in America is not automatically allowed anywhere else. A Robo-advisor wishing to enter a new market must start by applying for local licensing, and ensuring their platform and business comply with local regulations. This process not only takes a huge amount of time and money but takes away focus from your immediate growth plans. Thus, for most platforms, until the growth opportunity is fully sapped locally, going international just isn’t worth the trouble.

This introduces a massive hurdle for market entry, which plays into the hands of the incumbents and local startups. The pace of innovation for Robo-advisors thus far has been dictated by local start-up disruption. As soon as local Robo-advisors start emerging and gaining traction, the traditional providers must move to offer similar platforms and services. In Singapore, this process was driven largely by StashAway, which also started in 2016 as a start-up Robo-advisor. Initially, they were met with skepticism, but after a few years of solid growth, they have forced the hand of the industry and created a thriving ecosystem of Robo-advisors offered by a host of banks and start-ups playing catchup with StashAway.

From risk to goal-based investing

Traditionally, financial advisors would make a large part of their fees from commissions by selling specific fund products from asset managers. Hence, the engagement with new clients would center around which funds would be appropriate given the client’s needs. In the early 2000s, academics started developing an investment methodology that catered more to the client’s life situation than the advisor’s incentives. One such methodology is goal-based investing. According to author Paolo Sironi, goal-based investing had never caught on due to two main reasons: the practice of selling investment products was still immensely successful, and the technology to create a compelling user experience wasn’t there (Sironi). Robo-advisors presented a solution to the latter challenge.

Over the last decade, some form of goal-based investing has become the default approach for Robo-advisors around the world. Back in 2016, when Bambu was starting out, this was not an obvious choice. Many financial institutions were still operating in the traditional fund sales regime, so moving to goal-based investing was an additional unknown. Adding goals to a digital wealth platform is a double-edged sword. The obvious benefit is that it allows the platform to engage with the user around an aspirational topic of what they wish to achieve in their life, whereas the traditional engagement around risk is perceived as somewhat negative. The downside of adding goals to a user journey is that it is an additional complication. You still need risk questions, so the overall number of steps to open an account is now longer, which can impact conversion negatively.

The implementations of goal-based investing vary greatly among Robo-advisors. It can be as simple as assigning a name to your portfolio, or as complicated as assigning separate accounts and risk profiles to each goal. At Bambu, we made this the central defining feature of our platform, creating a whole library of calculator APIs to help people understand how much they might need for common life goals such as weddings, college, buying a home, or retiring based on different levels of lifestyle.

The future of Robo-advisors

Looking at where we are in 2022, a few key trends have emerged among the innovators in Robo-advisory. As market conditions and interest rates continue their turbulence, Robo-advisors are looking to expand their product offerings. A few years ago, this started with high-yield savings when Goldman Sachs entered the game with their Marcus app, offering 2% interest on cash. The success of this model forced many existing Robo-advisors to offer similar savings plans, and it was one of the reasons for record growth in users and AUM between 2019 and 2020. The savings rates offered by Wealthfront and others are highly dependent on interest rates and subject to regular updates (Wealthfront).

The fiscal pressures to deliver higher revenues and margins continue to push Robo-advisors to innovate and expand beyond their initial remit of investing. Several platforms have introduced bundles that include debit cards, margin loans, and even trading in stocks and crypto. These additional features serve to keep clients engaged, boost margins, and increase overall wallet share. This product expansion is beginning to gray the traditional borders between financial institutions such as advisors, brokers, custodians, lenders, and banks. Increasingly, these players are entering each other’s segments with overlapping product offerings.

Longer term, we may also see a bigger transformation of the Robo-advisor through blockchain technology. While regulations do not yet allow allocations of cryptocurrencies as part of Robo-advisor portfolios, that may be around the corner soon. Betterment’s acquisition of the crypto platform Makara indicates such a future (Sharma). However, the bigger opportunity may lie in a fundamental rethinking of how investment products are structured. The fundamental challenges in giving the world easy and free access to investing are still unsolved, due to the many complexities in how the industry operates, and the archaic technologies it was built on. Ideas such as tokenization promise a new approach to using distributed ledgers as a mechanism for defining the next generation of investment products. Already, many emerging markets have attracted stablecoin-based wallets as a solution to rampant inflation. Instead of the famous S&P 500 index fund, your future Robo-advisor might offer you portfolios consisting of tokens of fractional ownership in NFTs.

 

Summary

In this first chapter, we established the proper context for understanding what Robo-advisors are, where they came from, how they are useful, and how they have evolved since their beginnings in 2010. This should give you a basic understanding to follow the rest of the chapters in this book.

From here, we will delve deeper into the inner workings of the Robo-advisor before going hands-on and building one.

 

Further reading

You might be interested in reading some extra information related to the topics discussed in this chapter. Here are a few links to some of the external resources:

About the Author
  • Aki Ranin

    Aki Ranin is the founder of two A.I. startups in Singapore: Bambu in Fintech, and Healthzilla in Healthtech. He serves as Adjunct Lecturer at Singapore Management University on the topic of Machine Learning. His company Bambu has been a pioneer of Robo-advisor platforms since 2016, having built the first Robo-advisor in Singapore and worked with 20+ Enterprise clients across the world to design, build, and launch Robo-advisors Aki lives in Singapore and holds a Masters Degree in Computer Science from Aalto University in Finland and writes occasionally about startups, philosophy, and technology

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