An inclination towards investment recommendations
Background
Financially literate individuals always used to acquire assets with liquid cash so that they can reap the benefits later on. But the set of ‘financially literate’ people is a very tiny proportion within the large population. This is true even in the developed economies like US and the situation is worse in developing economies like India. Bottom line is that the investment inefficiency is a problem to address regardless of the economical bracket of the geography. As we speak, there are vivid horizons of plausible technology driven solutions that are being discovered within Banking & Financial industry and when you have such a vast consumer base unsure about the intricacies about the money management, the possibility is literally infinite.
The thought provocation
One of the trending topics these days among millennial or Gen Z population is to increase their net-worth by smart investments. As the general textbook says, we all should invest in some way or the other else our money will be decayed over time by something which we as call as ‘inflation’. A whole lot videos are being uploaded on YouTube on daily basis and millions are watching as well. Even if the selling proposition is inflation and increasing money overtime etc. the product offering has been generic to the mass population, lets not talk about the riches here because firms deal with them with extra care no matter what. Or let me rephrase, even though the overall investor population is diverse in their priority, goals, dependency, challenges and look for solutions catering to their needs but Financial Institutions used to sell them the same products. Understandably, we have a conflict in expectation vs the offerings or rather a genuine opportunity to explore the potential for growth.
Setting the ground
Although FIs somehow understood the problem but how to solve the problem? Dedicated advisors are mapped for rich individuals but it is absolutely impractical and in a way impossible as well to assign FAs at the mass level. Technology is in the rescue. Alright but still, how?
The problem statement is broad — provide personalized investment solutions. But it can be segregated into several small problems and accordingly find solutions. Sounds good but which tech, what steps? Is there any prerequisites? any preconditions? Well, let me come to those one by one. When we talk about understanding human and recommending something then with closed eyes we know that this can only be achieved by intelligent implementation of AI/ML algorithm. Talking about important conditions to build the solutions, there are few:-
Across the globe, regardless of the business every company is moving fast towards digitization. Some are already ahead of the curve and very rightly so they are reaping the benefits as well. Here is the catch, just because millennial are tech-savvy and that’s why everyone is building digital gateways — that is probably not entirely true and there has to be a bigger hidden opportunity.
The Eureka
There are already several tools available where individuals do their own wealth planning or subscribe to account services or declare their goals etc. and accordingly customers get some calls asking them to invest here and there and by so and so date they will be exercising this much profit which is fine but not what new age customers are expecting. They want a genuine recommendation which falls as per their need. Say, Mr. X is risk averse so obviously crypto is not for him. On the other hand, he has been heavily investing in stocks and that too in Oil & Energy sector. So now, is his debt allocation is less? Citing the rising crude oil prices where is his investment going? is there any projection for next 6 months? Is he interested in sustainable investment or is he dedicated to only Equity investment? Is it good to be short on tech stocks now? How dollar is performing with Euro? I understand these are pretty complex topics and an expert financial advisor should be able to answer these. But here is the beauty of technology, you still can achieve something without the expert around. Machine Learning algorithms are smart enough to understand client data, then the current market conditions, asset data thereafter evaluating probabilistic scores with the customer behaviors and accordingly recommend investment changes or solutions. Firms are going towards this way. Let me give you couple simple yet appropriate examples — Mr. X has a son who is going to take admission in a renowned engineering college in next 4 years.Mr. Y is looking for a ‘Euro Trip’ with his friends in the year end. Mr. Y has to take some aggressive call to make more profit whereas Mr.X can afford to be moderate while deciding. That’s the recommendation. Our ML algorithm which is running behind the scene should understand and provide recommendations catering to their individual needs.
Have we reached there? Well, the journey has started but have to cover a long way. The technological implementation is certainly not easy because firms need to gather data from innumerable sources and then performing data cleaning, doing due analysis of such huge dataset is a cumbersome task to say the least. Moreover, the volatile market conditions and socio-political atmosphere throws more challenges to firms and their developers. Hence, the eventual journey towards future will be a roaler-coaster ride for sure. Lastly, the exact approach towards implementation i.e., the tech — well lets discuss that on some other day and do a deep dive into the ML recommendation system design — hopefully soon.
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