Big Data is New Data: How It could impact Retail Investing
The views and opinions expressed in this article are that of my own and do not represent the same views and opinions of any entities I am associated with. Full disclaimer at the end of the article.
Big data, frankly defined, is new data. This is could be new data that is collected or old data that was previously overlooked but is now being analysed and considered when a user makes a decision. In the latter, it is new data to that user because that user did not use that data before, although that data could have been generated or collected a while back.
The financial sector, particularly banks, are known for lagging behind when it comes to upgrading their systems/business models to new inventions. One just need to assess the number of Fin-tech start-ups to support this argument. Investing, like many other sectors, is also not immune to this problem of lagging behind when it’s time to upgrade to new ways(inventions) when a need to do so arises.
In this article, I attempt to illustrate how new data, otherwise, big data (I use “new data” with clear intent of avoiding the commonly used jargon and keep those in finance until the end) could possibly impact retail investing. I use three simplified scenarios to demonstrate how this new data is currently being used and how it should be used by different stakeholders in the retail investment space. I also show a bit of unwise courage by making some unjustified inferences on the broader trend of a new generation of investors and the resulting impact on key stakeholders, particularly Financial Advisors and Investment managers.
The following scenarios are completely hypothetical but are as close to reality as possible and embrace the broad adaption of technology as a new standard of living.
Scenario 1
Miriam just posted a picture on Instagram of a meal she is having, a Vegetarian Fajita. She used two hashtags and the caption reads “I have decided to be Vegan for a year, and taking my official first bite of that journey today with this colourful fajita”.
Scenario 2
Katlego just received an insurance pay out after his car was damaged in a storm that hit his town recently. His Tesla Model X was damaged beyond repair. He was the first batch of customers to buy a Tesla. He plans to buy the latest Model 3 next month and has been searching online on the different extra configurations he can add.
Scenario 3
Ruben is a loyal Chelsea fan (Like many people, Ruben is not perfect), which just announced Three as the main official shirt partner (Sponsor). Ruben’s sports enthusiasm span to Basket Ball as well and he has never missed a single game of the Lakers in the last season.
Data Generation
All three scenarios have one thing in common, at some point, they generated online digital footprint and these data will be used by different role players. In the first scenario, Miriam will be seeing a lot of online adverts that relates to being a Vegan. This will occur for a while, and almost everywhere, whether on her Twitter account, or in her emails, she will be followed by “Vegan” advertisers.
Cookies have made it a lot easier to do what Miriam will experience. What has happened is that she has generated some data, and that data is immediately being used by role players who have the right resources to use such data as soon as its generated. The “role players” in this instance might exclude her Financial advisor, who does not concern herself of whether the people she gives financial advice to are Vegan or not. In a perfect world, the Financial Advisor should know that her client is Vegan or plans to be Vegan in order to give a more informed advice. This advice will be aligned to the investment philosophy that will be explained later.
Making informed decisions
It makes logical sense to argue that the more information we have about a specific subject matter, the more we are able to make much more better informed decisions on that subject matter. A simple example is this, imagine you are living in the 70s and you are visiting a friend in a different city. During those days, you will have no idea what the weather will be like in a different city. Assuming the main form of communication is writing letters, you will most probably have no slight clue of what the weather will be like on the days you are supposed to visit. And so, you will just have to wear what fits the weather in your area but be sure to take extra clothes for different seasons along your visit in case the weather is different in the other city. Assuming you will pay extra charge for the extra luggage of extra clothes, this example illustrate the cost of making a decision without enough data or information on a subject matter.
We are living in the fourth industrial revolution and data is now a critical resource for any decision maker, which includes me and you. The vast amount of data we generate allows us to make far better decisions than we used to. Not using such data becomes a sort of negligent as you deliberately don’t take into account information that is at your discretion.
Investment Philosophy
Investing is really a simple thing to do, as Warrant Buffet, most probably the best investor of our lifetime, attest. Invest/Buy into companies that you think you will never sell. So, essentially, if you are Vegan, you might want to be invested in a business/company that produce/sells vegan meals.
In the second scenario, Katlego should then be invested in Tesla stocks. Assuming Katlego was the first batch of customers of a Tesla produced car, and at the same time invested (bought) Tesla stocks, his investment would have produced some great returns for him.
This way of investing makes a lot of sense, if you are the customer of a specific business that is making a solution/product for you, you should clearly be invested in that same specific business. This is because you and the people this business is catering to, will be enough to sustain that business. If you are Vegan, you should clearly be invested in a business that sells/produce those same Vegan meals to you.
You will not be surprised to hear that financial advisors then, don’t bother themselves with what you eat, wear, and in a worst case scenario, what you drive, where you live and work. This is completely justified because this kind of data is hard to gather, store and analyse. I cannot imagine an Advisor knowing every kind of meal every single one of her/his more than 1000 clients had in the past month. Even if advisors started gathering and using this form of data to make far better-informed decisions for their clients, they still will face a problem of a mismatch of where to invest those clients. This is because Investment Managers also don’t take into account such subtle information such as whether an investor is Vegan or not.
New Generation and a broader trend of Investors
The increasing success of new and different investment platforms such as EasyEquities and Robinhood can be used as clear indicators of how retail investing is changing and shaping to be in future. It might not be clear of how this will eventually come to, and any prophet can be a prophet of doom, unless they have analysed enough data to infer their prophecies. A simple yet informative analysis of these new investment platforms can be that the people that use them are significantly younger compared to investors on different platforms (Older investment platforms)
One can further argue the younger generation of investors are much more conscious of their investments. They want their personal, ethical, religious and personal preferences to be reflected in everything they do, including their own investments. It will therefore be unattractive for this new generation of investors to invest in “bundled funds” that most large retail investors offer them as they don’t usually take into account these investors’ preferences.
Let’s assume Katlego is an environmental activist who would, in a perfect world, only invest in companies that have clear ESG goals and targets. Another assumption we can make about Katlego is that he is a government employee and so his pension/retirement investment are managed by a state administrator. Despite the fact that Katlego was the first batch of customers to drive a Tesla, he might never be invested in Tesla stocks as the Portfolio manager of his pension fund will never include it in their portfolio until the stock is included in the S&P 500 Index. Even if Katlego turned to invest some of his savings with a private investment manager, the Portfolio manager there might not take into account what his client drives and might be of the opinion that Tesla stocks are unattractive, too expensive, the company is burning too much cash, plus give another dozen reasons not to own the stock, but still not taking into account the client preferences.
Miriam and Ruben might face the same situation as Katlego with their respective investments. Miriam might never be invested in a Vegan business/Stock although she might be Vegan for the rest of her life. The last scenario of Ruben is more complex (I included this example as this will need far more data to analyse in order to end up with a more informed decision). Will Ruben also be loyal to the new sponsors/brands/companies associated with the sport teams he is loyal to, should he then be invested in these same businesses and if so, at what point should he be invested.
New Data for Retails Investor
As I demonstrated earlier in the example, having more data on particular subject matter allows the decision maker to make far better-informed decision on that subject. Should then Portfolio managers take into account this new available data of what their clients eat, wear, drive, etc when deciding their next investment and is that even possible. The answer is yes, given the right skills and resources, it is possible to “tailor make” investments to match the clients’ preferences, instead of bundling funds and leaving potential investors to pick whichever funds that might closely reflect their life or preferred investments.
Investment managers are highly rational decision makers when it comes to investment decisions (To all behavioural scientists/economist/investors, let us make this assumption here and leave the debate for more fair analyses) and most of them make their investment decisions guided by a specific mandate. The mandate might be to earn returns higher than the inflation rate at any given time, to be Regulation 28 complaint, to only invest in businesses that have prioritised ESG targets, etc. This has worked well for most of them, but such more broader decision making without considering what investors prefer might need to be changed.
A Portfolio manager’s role then might change to consider what Katlego (The investor) is driving and invested in, and decide how to diversify Katlego’s total portfolio. Should he maybe be invested in Volkswagen Group, he might not be happy with the past Dieselgate against the business and take a hard line on ESG. Or his portfolio might be better diversified if he adds Toyota instead. Perhaps this role of identifying and ensuring diversity should be played by the Financial Advisor instead of the Portfolio manager. In any case, it will be essential for each key role player to take into account more and more of such data when making financial and investment decisions.
The collection and analyses of such data might be costly and where the measurement of the benefits of using such data can be subjective, to simply neglect such data that helps in making better decisions is to some extent negligent. There is of course the issue of data privacy and what can be used and what is off the limit. I choose to avoid the debate on this as it should be up to individuals of how much of their data that is at their discretion they want to use and share with different role players. But as far as we know it, me and you generate data each and every single day, and whether or not we choose to use these data to help us make more informed decisions, particularly our own financial decisions, is up to us, but in either case, that data we generate will lend in someone’s hands, they will analyse it and one way or the other, help, or implicitly put, “influence” our decisions later on.
Disclaimer
The views and opinions expressed in this article are that of my own and do not represent the same views and opinions of any entities I am associated with.
The individuals mentioned in the article are hypothetical.
This article is not an endorsement of the different investment platforms and stocks aforementioned.
This article should not be viewed as financial advice. Anyone seeking such advice should do so with a Financial Advisor or Planner that is registered with the FSCA (If in South Africa) or with the relevant regulatory authority in their respective country.
