Are You Ready To Trust A Robo Advisor With Your Money?

taliTali Soroker is a Financial Analyst at I Know First.

Are You Ready To Trust A Robo Advisor With Your Money?


  • Do robo advisors help or hurt investors?
  • Basic benefits and drawbacks of using a robo advisor
  • Obstacles that robo advisors need to overcome
  • How I Know First’s robo advisor will best serve clients

Robo Advisors

Robo advisors are becoming a popular investment tool especially among emerging middle class investors and millennials. This new form of portfolio management relies on an advanced algorithm to do market analysis, allocate assets, and rebalance a client’s portfolio. These robo advisors tend to have more basic wealth management services and have lower fees than those charged by traditional advisors.

Robo advisor

(Source: Google)

As the first robo advisors were just introduced to the general investing population in 2008, some investors and analysts are weary that an algorithmic system can successfully optimize an investor’s portfolio while managing risk. For many investors, the online user interface is easier to engage with than traditional analysts or advisors, while other investors need more than a computer to uncover the most suitable portfolio for their specific goals. There are some clear upsides and downsides to using a robo advisor rather than a traditional advisor, but are robo advisors ultimately beneficial or investors or not?

Key Benefits and Drawbacks

Lisa Woodley, Vice President of Digital Experience NTT DATA, Inc., explains what she sees as the key benefits and drawbacks of robo advisors:

“Robo advisors are inexpensive, rely on state-of-the-art digital technology and algorithms, and are ready to work with investors at all levels of investment. For digital and asset-light millennials it’s a no brainer. Why talk to a salesperson motivated by commission when I can invest myself? Answer questions, move sliders, come up with different asset models. It’s like playing a game. As long as you’re tracking to your retirement goal you’re good.

But what happens when investment strategy becomes less abstract — when you move from “retiring someday” to saving for your newborn baby’s college. That’s where emotion enters the equation. “What will college cost in 17 years? What if we need to buy a house or move to a bigger apartment? Can we even afford this!?!”

When you think of investing in these terms an algorithm isn’t enough. You need to talk to someone who understands you; someone who can calm your fears and talk you through all your options.

So, it depends. Advisors who aren’t interested in building relationships and just want to collect commission on quick sales are definitely in trouble. The type of investor who is ok with just being told where to put their money is already starting to do that themselves via self- serve and robo advisors.

But for the relationship builders, the advisors who know you, understand your goals, and more importantly your fears, the rise of the robo advisor leaves them right there where you need them, on the other end of the phone armed with all the info they need ready to reassure you and walk you through your options, options that are at the ready thanks to their own handy robo advisor.”

Beyond the Concept and Interface

In a cursory glance it may seem as though robo advisors have uncharted potential and just one problem to face, namely, that investors get nervous in unsure situations just like every other person. The rules-based investing tool has lower fees and an easy-to-use interface that is attractive to younger investors. Beyond the concept, though, and beyond the interface and the monthly billing is the algorithm that the system is built around. Chris Georgandellis, a Senior Portfolio Manager for Exchange Capital Management, Inc., finds fault with the robo advisor right at the center of the system:

“A robo-advisor strategy is nothing more than a rules-based approach to investing.  The obvious benefit to such an approach is consistency:  That is, you will (on average) get a consistent application of the rules.  The downside to this approach should be obvious:  The rules that are being applied are only as good as the people who created them.

The drawback to any rules-based system is that nearly every rule is drawn from direct historical observation – for example, “When A happens, B happens afterwards, so we do C.”  So long as that historical relationship works, then the rules upon which they are based will work.  However, if those relationships should change or shift – a regular occurrence in the investing universe – then the rule-based approach will suffer accordingly.  Not only that, but the designers of the systerobo advisorm will be forced to decide whether or not losses incurred by “stale rules” are simply temporary or represent a real shift in investment thinking.”

He’s right, of course, a rules-based system is only as good as the people that write the rules. It’s important, though, to differentiate between an algorithm that is designed with built-in rules written by its creators and those that employ machine learning and deep learning processes. Systems that are created with deep learning abilities are not designed to follow written rules, the machine can find the relationships within large data sets and derive and change rules on its own with no human involvement.


In the Works

I Know First’s R&D team is currently working with co-founder and CTO, Dr. Lipa Roitman, to develop a robo-advising system with the integration of I Know First’s propriety algorithms. The algorithmic system that has been developed by Dr. Roitman incorporates artificial intelligence and machine learning with elements of artificial neural networks and genetic algorithms. This state of the art system is able to analyze, model, and predict the stock market.

Dr. Roitman elaborates, “Our (I Know First’s) system is adaptable, and the self-learning, deep-learning algorithm detects when the rules change and creates new rules accordingly. Daily we see rotation in the important inputs. Gradually one input becomes less important, and is overtaken by another one with growing importance. Volatility, currency rates, interest rates, oil price and other macro indicators take turns as leading inputs. Rules change and the forecasting system adapts. Just like the market is a complex living and competing eco-system, similarly, our algorithms are the eco-system of multiple independent predictors, each competing with another for room in prediction space.”

The employment of I Know First’s algorithmic system will advance the concept of robo advising. In this system, the algorithms will not be following set rules to analyze stock fundamentals or market conditions but will be optimizing investors’ portfolios with the predictive capabilities of the algorithms.


There are many benefits to using a robo advisor both as an individual and as a wealth management firm. The system capitalizes on advanced technology to offer clients a less expensive and, often, more accessible investing option. The concept is not without flaws, though. These systems rely on algorithms that function using rules that are written by human beings, so the system is only as good as the people that created it. However, were a robo advising system constructed with deep-learning algorithms rather than rules-based algorithms, then the system would be performing analysis on market data and writing the rules itself instead. I Know First’s team is working on incorporating the algorithms that were developed by Dr. Roitman into a new robo advising system that will not face this same problem.