The retail brokerage industry has historically been boring and traditional. Many behemoths of today were founded in the late 70s and early 80s to offer do-it-yourself (DIY) investors direct access to financial products. Since then, such financial product platforms have innovated at a glacial pace.
Just as Amazon, through skillful application of Artificial Intelligence (AI), created an intelligent consumer product platform and disrupted the multi-trillion-dollar e-commerce industry, so will the adept application of AI disrupt financial product platforms and the manner in which DIY investors interact with them.
Role of AI in the Retail Brokerage Industry
Over the past 40 years, the industry has seen an explosion in financial product platforms. Consider this: In 1970, there were 1,328 mutual funds but today, there are over 18,000 (including all fund share classes). That’s over a 1,200% increase!
While these financial product platforms provide the ability to browse and invest in a wide range of financial products: stocks, bonds, mutual funds, exchange-traded funds, options, and annuities, they lack the “Amazon-like” built-in intelligence to narrow down on the appropriate products and offer rich personalized solutions to customers.
Instead of browsing thousands of products to develop their own solutions — a task most DIY investors are ill-prepared for due to lack of financial literacy — Artificial Intelligence offers a unique opportunity for financial product platforms to offer an “Amazon-like user experience” to the DIY investor.
Imagine, you want to invest in your financial future and instead of paying a brokerage service or meekly seeking avenues such as Google, family, and friends or (in case of a millennial) forums such as Reddit for best products or ad hoc guidance, you have an all-in-one AI enabled financial platform watching the trends and offering custom, real-time advice, and suggestions!
So, how will this next generation of AI-enabled financial product platform be achievable?
There are two key aspects to it:
- First, develop a multi-dimensional Customer Map through thoughtful collection and analysis of customer data;
- Second, apply AI to predict key events in a customer’s life and show context-rich user-centric products and guidance.
Data Gathering and Analytics for a Comprehensive User Map
Instead of relying on siloed legacy systems, an intelligent financial product platform will be built on the premise that “customer data is the new currency.” This approach is akin to the gold standard followed by most human financial advisors: “know-thy-customer.”
A “know-thy-customer” approach will require next-gen brokerages to harness customer data, develop a rich multi-dimensional Customer Map and that enable deeper financial interactions. This process begins with a brokerage making it incredibly intuitive for customers to securely aggregate information about their assets and debts in one place.
Doing so helps construct an overall financial picture of the customer about types of external investment accounts and product choices, credit card balances, and any student or mortgage debts the customer may have.
The brokerages can further enhance their understanding of customers by offering logical “next-step services.” For example, if a customer connects a retirement account like a 401(k) — 75 million families have one — the brokerage could nudge the customer to perform a retirement analysis and fill additional gaps in the Customer Map.
This wealth of data can then be leveraged by an intelligent brokerage to better “connect the dots” for an already overwhelmed and financially less literate customer. Insights such as a customer’s product preferences (e.g. whether a customer prefers mutual funds or exchange-traded funds (ETFs), level of financial literacy and ability and willingness to take a risk can all be accurately assessed from this data to assist the customer.
A potential example of how such an intelligent brokerage can instantly “connect the dots” for a customer may involve a customer performing a retirement analysis that shows a shortfall (81% don’t know how much they need for retirement and the average Fidelity 401(k) in 2018 was 104K).
Now imagine, if the shortfall triggers the intelligent brokerage to instantly and automatically perform a detailed analysis, looking for “wastage” the customer may be unaware of.
What if the brokerage discovers that rolling over existing credit card debt to a lower alternative could result in interest cost savings that if invested could reduce retirement shortfall by say 10%. The brokerage could then show the cheaper credit card alternative, do the math, calculate the interest savings, the amount such savings could grow to if invested till time to retirement and how much better off the customer would be in achieving the retirement goal.
From the DIY investor perspective, the intelligent brokerage has done the math, and presented the analysis simply, intuitively and clearly for the investor to decide. All the investor has to do to trigger this change is to merely click a button. Imagine the savings in terms of time, effort and money everyday investors could achieve if technology could make such connections for the DIY investor as opposed to the investor setting aside time and expending considerable effort trying to reach a similar conclusion.
AI to Predict Future Events and Offer Contextual Advice
The next level of guidance could go a step further and be predictive in nature. In order to achieve that, the user map becomes the foundation on which application of AI and predictive analytics can even more radically transform the user experience.
One area where an application of AI could be incredibly helpful for average Americans is that of 401(k) roll-over. An average person changes jobs 10 to 15 times in his or her career.
Assuming that the person works for an employer that offers a 401(k), such a person does the following: 1) sets aside time to initiate the 401(k) rollover 2) sets reminders to check if the cash transfer is complete 3) allocates time and expends considerable effort on how to invest this cash… 10 to 15 times in his or her life.
Now consider this: What if the intelligent brokerage predicts that an investor has changed jobs, confirms with the investor via his/her preferred method of communication be it voice or text or chat (based on User Map), initiates a roll-over of 401(k) when customer clicks a button, informs the investor of cash transfer, suggests a tailored asset allocation solution (based on retirement information in the User Map) pre-filled with low fee products (based on product preferences in the User Map) which the investor can either accept “as is” or alter before investing…all with just 1 click.
And technology can do that as many times as the investor changes jobs…without emotions and without any distractions. The individual investor, who may be grappling with the stress that comes with job change, not to mention the myriad other stresses of life, now finds in the intelligent brokerage a partner that doesn’t take control away yet empowers him or her to make intelligent investing decisions just as Amazon’s intelligent product platform helps customers reach smarter decisions faster and cheaper.
Beyond this kind of assistance, AI-driven retail brokerage can continually update its understanding of the investor by revising the importance it attaches to the various user actions and attributes defined in the User Map. This approach, once again, mimics what human advisors do when they, through on-going interactions and dialogue, evaluate the ever-changing mindset of the client towards risk, wealth and desires.
An intelligent brokerage could be there…intelligently analyzing the digital footprint of the customer…ready to serve with contextually relevant and highly user-centric solutions… as customers transition through life’s crucial events like marriage, kids, job change, home buying etc.
AI will transform the retail brokerages as we know them. The next generation of brokerages will empower DIY investors to instantly make smart investing decisions, and channel millions of hours saved and the billions of dollars not lost to high fee products on people and priorities that matter.