Fintech in investment management

Fintech combines innovative technologies such as AI, machine learning, big data, and blockchain to bolster the services that investment management companies already provide — and enhance their accuracy and security. Automation is key, with both retail investors and companies better controlling their finances and balance sheets through smart, autonomous algorithms.

Many of the aforementioned tools that are core across the fintech industry play an even bigger role in investment management, where the handling of data — from clients and the world at large — is essential to build a successful platform.

Big data’s analytic tools improve by the day, with large amounts of data sources available that can be analyzed and then fed into smart algorithms for investment optimization. With the correct configuration, non-traditional data sources such as web traffic and patent filings can be correlated to advise investors about brewing market sentiment. The more data sources to study — indexes, ledgers, sensors, social media, and even satellite images tracking car frequency on Walmart’s parking lots — the better.

Together with big data, AI analyzes huge batches of data and recognizes patterns within it, all but eliminating risky gut reactions in favor of decisions rooted in actionable data. By automating certain actions, the decision-making process is simplified and man-hours can be better allocated elsewhere.

Beyond the well-known high-frequency trading algorithms employed by Wall Street firms, AI can improve investment management platforms in different ways. For example, AI-based NLP technology can recognize and catalog voice-based interactions, generating troves of valuable data for big data to convert into insights that can be used to improve the solutions offered by your platform.

While AI analyzes data, machine learning algorithms read between the lines of code to understand human feelings, behavior, and how those intangible characteristics affect decisions. This allows machine learning to uncover and anticipate patterns where there’s seemingly none — such as correlations between a company’s stock fluctuation and the tone of voice and lingo used by its CEO on quarterly earnings calls. These lessons, in turn, underpin smart algorithms that optimize trade via automation.

Even when not considering the revolutionary concepts of value brought mainstream via cryptocurrencies, the same distributed ledger technology (DLT) that enables blockchain also lends a thick layer of protection to investment platforms. Smart contracts, for instance, can be designed to demand multiple signatures for validation, shielding the parties from market volatility — and scams. Blockchain’s consent-required underlayings lend transparency and reliability to fintech platforms, which then increase client acquisition and company valuation.

Distant cousins to chatbots, robo-advisors are automated text-based assistants that can execute trades, optimize portfolio strategies, and organize your taxes without requiring human intervention. Because they can efficiently reach customers at scale, robo-advisors excel at reducing costs and enabling growth.

Speaking of scale, analysts project that robo-advisors — linchpins of “wealthtech” — are going to become the new normal advisors: By 2026, they’ll be managing $16 trillion in assets — a leap of 4x over 2020 figures.

Drawing from AI disciplines, fintech-specific smart algorithms are now ubiquitous in investment management apps. Trading is now done at hyperspeed: Markets that some years ago would update their trading values once per day at the opening bell now do so in real time, so traders must rely on algorithmic trading for better insights, to automate and speed up trades, and to react better and faster to unexpected market movements.

Fintech as a whole provides innumerable benefits to its adopters even in the most casual tapping of financial services, like checking your balance in an app.

A great fintech investment management product, however, delivers on a single objective: increasing ROI.

Not so long ago, an asset management team would consist of anywhere from one manager to up to a dozen, limiting its accessibility to only those who could afford it; “wealth management” was only for the wealthy. Fintech has turned that reality upside down.

“Today, the tools that used to be solely available to Wall Street are now up for grabs to anyone with a smartphone,” says Ravi Srikantan, senior fintech advisor at Vention. “With plenty of quality investment management products to choose from, many of which are free of charge, the playing field has been expanded and the industry as a whole is fortified.”

VCs have accordingly injected multi-billion dollar investments into products like retail investor-oriented exchange apps that meet the demand of technologically astute, financially literate customers.

If investment apps enabled more retail investors to access the market, tokenization tech such as blockchain-anchored collectibles, digital or otherwise, has fueled unconventional investment markets that are now worth billions. Borrowing a page from targeted advertising, smart algorithms can tailor insights to an investor’s situation and circumstances, down to the individual level — like the highly personal rules-based investment management model, where stock is picked based on pre-arranged rules — and retire the one-size-fits-all approach to investing that has long been standard.

Great investment management platforms don’t just optimize a customer’s investments, but their income and expenditures as a whole. Since every penny saved is one that could be invested, many of those solutions can also be optimized to increase a customer’s savings by, for example, figuring out the best strategy to reduce their tax burden.

While both individuals and companies benefit from investment management platforms, the tools they rely on and the scale at which transactions are done can be wildly different. Retail investors rarely have to deal with risks such as the need for high liquidity, or portfolios involving hundreds of assets in multiple countries. Companies do, however, and they need to manage risk in very particular ways.

Executives who plan to build an investment management solution need to remember that:

AI, machine learning, and big data all must be properly configured — and in tune with your company’s objectives — to be reliable. A subpar setup of the big data infrastructure, for example, could feed machine learning algorithms with irrelevant information, botching the quality of risk management and decision-making processes.

If, say, your company specializes in B2B, your investment management platform will be quite different than if it was B2C. In some instances, there’s an easy way out to adapt the existing infrastructure to different needs — new functions here, slight UI/UX adjustments there — but in many cases, that may require plenty of extra coding hours and hefty sums. Knowing your end-users beforehand saves you a lot of unnecessary rework.

Compliance is a matter of life or death for fintech apps. This is especially true for companies operating in multiple countries. Regulations, especially those governing new technologies like crypto, can vary dramatically across regions, and without a comprehensive understanding of how your company operates in disparate markets, a keen awareness of what the regulations are in each one, plus a plan to build a solution that automates compliance as much as possible, your investment platform will suffer.

Not only are integrations a great source of data for insights, but they do double duty by sharing information that can be relevant for safety or risk management, like credit scores from financial institutions such as Experian. Too many out-of-the-box integrations can clog a system, however, so customization is often the best strategy for a stable platform.

• Foundersuite - Foundersuite’s goal is to let startup investors — banks, incubators, and individual investors — manage the entire fundraising process within a single solution. Borrowing from CRMs, it features performance metrics, asset management, and status tracking.
• U-Rite - This cloud-based investment management product focused on real estate integrates with Excel to simplify calculations and facilitate access; it also uses ML to predict variables such as vacancy and adapt accordingly.
• Personal Capital - In the personal investment field, Personal Capital supports the linking of multiple accounts to its platform. The data is then processed and returned to the customer as highly detailed investment tracking. Users can reliably segment and organize physical and virtual cards, taxes, and retirement accounts, as well as establish metrics to improve them.

With so many up-and-coming investment possibilities in recent years, it’s easy to get carried away and miss the forest for the trees. The fintech world has barely scratched the surface of what recent technologies have to offer, but we already have some egregious examples of emerging markets shaken by their investors’ inability to work out their supposed potential value.

As any investment guru would tell us, one should never put all their precious egg assets in the same portfolio basket. Likewise, rushing to build an investment platform solely based on current hype might not be the wisest decision a couple of years down the road — especially in saturated markets.

While pivoting has its place (as Play-Doh will tell you), you don’t want to design with the attitude that you can repurpose if plans go awry. Building an investment management platform is laborious: Time, budget, man-hours, and sunken opportunity costs add up, so the more centered around rock-solid concepts a founder’s vision is, the higher chances are its fully-fledged platform will outshine competitors. Plus, the better your brand reputation kicks off from the get-go.

Hype wears off. Great products, and the head-turning disruption they cause, stick around for the long haul.