Friend or Foe: What Does Artificial Intelligence Mean for the Private Client?

Friend or Foe: What Does Artificial Intelligence Mean for the Private Client?

These days there’s no shortage of articles and white papers on how artificial intelligence (“AI”) is dynamically altering both our personal and work environments. From IBM’s Watson to Apple’s Siri and Amazon’s Alexa, AI development and adoption is rapidly accelerating. In fact, worldwide spending on AI systems is expected to grow to $52.2 billion by 2021.[1]

But what does AI mean for the private client? Not much is written from a client’s perspective. Will your future portfolio strategy be determined by an intelligent machine? Will human holographs and android replicants represent the next generation of Investment Advisors and Portfolio Managers? If they look like the cast in Blade Runner 2049, will you even care?


AI in a Nutshell

In broad terms, AI is the ability of a machine to copy intelligent human behavior. It is not a single technology, but rather a family of technologies, including natural language processing, computer vision, automated speech recognition, advanced machine learning, image recognition and robotics. Progress in AI has been driven by significant improvements in computing power, the explosion of big data and advances in algorithmic science.

Today’s AI is more accurately defined as artificial “narrow” intelligence because it performs specific tasks and operates within limited, predefined ranges. For example, Siri uses natural language processing to enter your specific information request into a search engine and provide you with the results. Siri cannot perform other tasks, such as order Uber Eats, or respond to general queries that require more comprehensive knowledge. In contrast, most fictional AI represents artificial “general” intelligence, because it has the cognitive ability to perform a broad variety of intelligent tasks with some level of human consciousness.

The main advantage of narrow AI applications in use today is their ability to quickly scan extremely large quantities of data, discover patterns and make reasonable predictions. For example, a human loan officer generally looks at a few criteria to evaluate your credit application (e.g., assets, credit score, income, age). However, an AI application determines your creditworthiness from thousands of variables, including your internet browsing, social media activity, shopping habits, geolocation data and more. Taken alone, the predictive power of each variable is not meaningful. But when combined, these variables can lead to accurate assessments about your status as a borrower. This capability has countless uses, such as automated customer support, self-driving cars and rapid medical diagnosis.


AI in Wealth Management

The most well-known example of AI in wealth management today is the robo-advisor platform. Robo-advisors (or “robos”) emerged in 2008 as a low-cost, digital alternative to a personal financial advisor for retail investors. Today, robo-advisors allocate approximately US$398 billion of worldwide investment assets using automated, rules-based models.[2] You fill out an online survey about your age, investment goals and risk tolerance, and the robo application selects an assortment of exchange-traded funds (ETFs) for your portfolio.

For new investors who are still accumulating assets and do not meet private client portfolio minimums, robo-advisors have helped broaden access to formal investment advice, as the systems can scale to take on extremely large numbers of clients with any size of portfolio. For private client investors, who are accustomed to working with human professionals, the advance of robo-advisors has helped fuel more widespread investment in robust, automated service delivery tools by their wealth management providers.    

While financial journalists and big name consultants have gotten great mileage out of the potential disruptive impact of robos within the investment industry, the reality is that this narrow form of AI cannot replace human advice. Even with recent advances, robo software still relies on the individual investor to provide the data necessary to determine their risk profile and asset mix. This model works well in rising markets, when it’s easy to love risk, but what happens when there’s a significant market pullback and your portfolio of ETFs drops by 15%? Will you rush to log into your digital advisor and modify your profile to “LOW RISK” at the worst possible time? Who will prevent you from making this irrational investment decision that could materially impact your net worth? Who will give you the big picture?



Along with robo-systems, financial institutions have been investing in AI to extract value from big data and better understand what products and services their clients want. For example, Australia and New Zealand Banking Group Limited (ANZ) was an early adopter of AI technology with the use of IBM’s Watson to understand client behaviour.[3] BlackRock acquired a digital advice platform in 2015 to enhance and inform their investment decisions.[4] UBS uses a technology called Sqreem (Sequential Quantum Reduction and Extraction Model) to identify typical client patterns in large amounts of unstructured data.[5] More and more, fintech startups are unveiling applications that use AI to synthesize news, market data and product information for wealth managers to share with their clients.

So what does all this mean for you, the private client? At the very least, you should expect to receive, in real time, more tailored, personalized insights that reflect the knowledge and expertise of the entire firm, delivered through your preferred channel. Your wealth manager will become better at predicting your financial needs and life-changing events based on your digital footprint. Armed with dashboards that push through relevant data, portfolio metrics, alerts and automated decision-making, advisors and portfolio managers will spend less time preparing for meetings and more time providing proactive advice and recommendations.

You’re not alone if the thought of this radically improved service experience triggers some privacy alarms. However, today’s private client is a digital immigrant at best, who still likes voicemail, turns off auto location settings and remembers the original Blade Runner cast. Social experts say that the next generation of private clients is far less likely to have digital-spying qualms, provided they see value, such as better service, from their data being used.[6] At the same time, financial institutions have no choice but to continue investing in data privacy and governance programs to maintain client trust.


An existential threat? 

Tech leaders like Elon Musk, Stephen Hawking and Bill Gates have issued vocal warnings about AI advancing beyond human control (for some of you, this may evoke fond Terminator memories). Unfortunately, we don’t have room to explore their hypothesis in this blog. However, it does bring us back to our opening question: Will the next generation of investment advisors and portfolio managers be represented by some form of intelligent machine?

We believe the advisor and portfolio manager role will evolve, not disappear. While AI is superhuman at dynamically processing information and doing digital detective work, it is unable to choose its own goals or think creatively – not to mention the fact that AI outcomes are devoid of empathy and entirely based on the data and assumptions with which they are shaped. The complex, interpersonal nature of investor risk profiling requires a flexible and robust understanding of human needs and emotions. For this reason, wealth management will remain both an art and a science, balancing technological progress with the human touch.

In conclusion, private clients need not worry that AI will completely take over their investing process and experience.  More realistically, robos and intelligent systems will eventually work alongside investment professionals, allowing them to focus more on high-value tasks such complex decision making and relationship building. The concept of a flawless, intelligent, replicant advisor with human-like consciousness will have to remain as sci-fi movie material – at least until we have artificial general intelligence. If that day ever comes, let’s just hope we’re prepared. 


[1] The International Data Corporation (IDC) Worldwide Semiannual Cognitive Artificial Intelligence Systems Spending Guide. 


[3] “The evolution of Robo-advisors and Advisor 2.0 model” ©2018 Ernst & Young LLP.

[4] & [5] “Transformative Nature Of Artificial Intelligence (AI) In Wealth Management” ©2017 The Capital Markets Company NV (Capco)

[6] “Applying Artificial Intelligence in Wealth Management: Compelling Use Cases Across the Client Life Cycle”, WealthBriefing, December 2017