Big Funds, Bigger Data: 5 Companies That Utilize AI In Wealth Management

This article has been written by the I Know First Research Team.

Wealth management, the trade and art of, in absolute terms, increasing the client’s affluence through a variety of investment-related services, is reshaping itself as the new era comes knocking at the door – and with it, come the high-net-worth individuals (HNWIs) of the millennial generation, with their taste for all things high-tech and an individualist attitude. But while this new clientele, along with other features of this day and age, be it the abundance of buzz to navigate around when developing tailored investment solutions or the rise of the robo-advisors, does pose a challenge for the industry, the opportunities may be more than ample as well.


Enter AI and Machine Learning (ML), the very technology that has enabled the arrival of automated investment advisors in the first place. With CPUs and GPUs getting more and more powerful, machines are now able to use this newfound computational capability to pick up patterns and signals in the gargantuan flow of data we generate every second and derive actionable insights from them, relying on advanced statistical programming and complex mathematical models. This sphere holds a massive promise for businesses and whole industries looking to keep up with the world, and thus, it is no surprise that it is widely projected to grow.

The wealth management sector is hardly an exception in this respect, especially since, as a recent report notes, people are still hesitant to entrust a piece of code, no matter how advanced it might be, with full, unsupervised control over their fortune. Thus, it may be all too early to dismiss the human wealth management experts as doomed to lose their jobs to robots; in fact, the field is well-positioned to embrace the new tech and reap the benefits of the smart machines on multiple fronts while maintain its signature personalized, rapport-based style. This idea seems to resonate with the BlackRock Group, the world’s largest investment groups, which has recently established a dedicated center for AI research. Morgan Stanley, despite being known for its human-centric business culture, has also seemingly placed its bet on the shiny new tech, developing an ML-based model to help out its financial analysts with suggested investment choices for customers.

If you are looking to follow suit and pick up an AI-based solution that could boost your wealth management service’s performance in many of its aspects while also giving it a sought-after high-tech appeal, here are 5 companies to consider.

Automate Your Outreach: &, AI-based Customer Relationship Management Services

Building up the client base may be a challenge for private welfare managers, as endless cold calls and emails consume the time that could have been spent studying the client’s portfolio or building up the rapport with the customers., a startup founded in 2015 by entrepreneurs JD Chang, John Mao and Michael Roberts, seeks to address this issue by utilizing AI technology and social networks. It helps welfare managers to develop their connections on LinkedIn by scraping the social network for profiles similar to those they are already working with and ranking them by their likelihood to respond. It also allows to automate the outreach, with the algorithm picking one of several introduction message templates to send it to the potential customer in line with their profile.


Based in Austin, TX, the company claims that its service allows to greatly expand the client’s outreach at a price that in most cases amounts to a mere 10% of what recruiting an actual salesperson would cost. While its $1.2 mln. of funding coming from Corsa Ventures over a single round may look meek against the attention that other companies on the list received from investors, but the service itself is quite indicative of a role that AI-based solutions could play in forging and developing the relations between the wealth managers and their customers.

Social media, whether geared towards professionals, like LinkedIn, or more informal, offer troves of data that can be mined to get a better understanding of the client’s goals and a more subtle customer classification than the traditional split along the aggressive-growth-balanced-conservative lines. Here, a more nuanced data-driven approach drawing upon psychometrics and behavioral psychology could in its turn lead to a portfolio and a set of services that is more optimized to the client’s exact needs, which is likely to be appreciated by the customers. And on top of that, it is quite astonishing to see the machines being used in rapport-building, the aspect of wealth management that is so fundamentally human in nature. 

“Siri, Manage My Money”: Cinch Financial, AI-Based Personal Finance Assistant

AI-driven personal assistants, like Apple’s Siri, Amazon’s Alexa or Microsoft’s Cortana, have made their way into the mainstream high tech, giving the users the comfort of being able to handle such mundane tasks as buying a movie ticket or switching on the music just by telling their smart gadgets to take care of that. However, while it is hard to imagine recruiting Siri as your personal Chief Finance Officer, there is an AI helper which would actually be pretty happy to work for you in that capacity.


Founded by Sean Collins, a seasoned finance expert, in 2014, the Boston-based Cinch Financial taps into the city’s history. Back in 1924, it was Boston, MA, that saw the first open-ended mutual fund established. Before that, in 1830, the duties of a fiduciary were codified there via a major court ruling.

The sophisticated AI-based personal helper that the company has created seeks to be your personal fiduciary, trusted asset manager (meaning that the company takes it upon itself to make sure the app only works in your best interest), as it studies your income, spending, student loans, insurance, credit cards and financial goals and then delivers financial advice tailored to your needs. This effectively works as a more readily-available form of wealth management delivered in a user-friendly package that seems quite appropriate for the current day and age.

The company is reported to have drawn almost $9 mln. worth of investment over three rounds. It pledges that the customer data is not transferred to any third parties, and its product has collected some favorable reviews from critics.    

Robots Are Coming: Bambu, AI-Driven Robo-Advisor Services Platform

The robots are coming to replace the humans, goes the narrative across the many industries predicted to shrink or even disappear as automation becomes the word of the day. While whether that is true or not is beyond the scope of this article, it may be worth noting here that at least some of the robots are not as much about taking jobs from the humans, but rather about helping the humans in their jobs centered around decisions requiring a thorough data analysis.  


This vision is at the foundation of Bambu and the projects it offers. Founded in 2016 by Ned Phillips, former Advisor for the Singapore FinTech Consortium, entrepreneur Luke Janssen, and Aki Ranin, a self-described reformed corporate executive, the Singapore-based company offers three products tailored towards specific clients. The first one, the Intelligent Advisor, is aimed at private banks and wealth managers working with HNWIs and provides investment recommendations tailored to match the investor’s profile; as such, it is designed to enhance the decision-making of welfare managers rather than replace them. The second product, White-Label Robo, is geared towards banks, asset managers and insurance companies and provides investment recommendations. This product is designed in a more mass-market way, with a broader audience in mind. Finally, the company also runs its own API for developers of automated solutions.

The company has landed a total of $3.4 mln. in investment over 2 rounds, with Franklin Templeton Investments, an American holding, as the leading investor. It can boast partnerships with DriveWealth, another fintech company that runs a brokerage platform for investing in US stocks and has raised almost $30 mln. in funding, and with Thomson Reuters, which works as the source of the market data for its algorithms. This works as a solid foundation for a strong end-to-end product that can enable wealth managers to optimize their decision-making.

Level The Playing Field: ForwardLane, AI-Based Data Aggregation & Insights Platform

It probably wouldn’t be too much a stretch of imagination to assume that most wealth management companies (and many other companies as well) would want to be Morgan Stanley, or at least have the same powerful AI to guide their decisions. It also goes without saying that most companies don’t have the amount of funds or manpower required to build a huge tidy dataset that is necessary to train an accurate ML model. ForwardLane, an ambitious fintech startup targeting wealth managers and investment advisors, looks to close this gap and make the playing field more even.


Founded in 2015 by Nathan Stevenson, a former quantitative analyst and investment banker, and Shay Krauss, a seasoned software engineer, ForwardLane has developed proprietary APIs aiming to give the mid-level wealth management companies unable to build up their own AI-driven tools for market research and analysis a way to boost their business with insights based on ML algorithms. Its Insights Engine works as a Google on steroids, utilizing natural language processing techniques to identify content and figures that would be most relevant to the wealth manager and their client. Its Client Prioritization API allows for a more tailored analysis that includes the “best next action” recommendation, seeking to identify the best course of action for every customer of the wealth management service.

The company has attracted $6.7 mln. in investment over 4 rounds; among its investors are such renowned names as Thomson Reuters and Techstars, a US-based seed accelerator, which helped it make its way into the world of high-tier asset management and tailor its product to its needs. Its partners also include Morningstar, Salesforce, Pershing and IBM Cloud. According to the company, its services allow wealth managers to save up to 20% of their working time, effectively giving them a whole extra workday in productivity.

Act On The Signals: I Know First, AI-Based Daily Market Service Forecast

While a human would probably struggle with keeping an eye on the prices of thousands of assets and calculating and re-calculating their interplay to build predictive models, for an AI, this task is basically not a problem as long as the computational power is there. I Know First, a stock market forecasting company based in Israel, makes use of this fact to help out wealth managers, hedge funds and other institutional and private investors eager to embrace algo-trading with their strategic decisions.


Founded by seasoned algo-trader Yaron Golgher and Dr. Lipa Roitman, a machine learning expert with years of experience, the company has trained a complex self-learning AI that relies on historical data for a period stretching around 15 years back to pick out the signals from the most recent market data and model whatever happens next. To a degree, it utilizes chaos theory to account for the volatile nature of the stock markets, where one small event can set the whole system off balance. The algorithm is familiar with over 10,000 various assets, including stocks, ETFs, currencies and other financial instruments from all around the globe; its output is delivered as a heatmap that shows the performance of every asset on the forecast compared against each other and includes a predictability score demonstrating the AI’s confidence in its own forecast. The algorithm includes a genetic component; in other words, the model minds its own accuracy and improves it with every new iteration.


The company’s output includes forecasts for different time periods, ranging from three days to one year, as well as financial analysis and analytical content on fintech and ML. It provides an overview of a whole variety of sectors, including high tech, pharma, biotech and chemicals, and does bespoke portfolio reviews. The algorithm demonstrates a solid perfomance, outdoing the S&P 500 index in terms of the generated returns.

As a matter of pride for the founders, the company has been able to develop and succeed on bootstrapping, needing no financial help from the outside. Its client network stretching across 70 countries, the company has developed an impressive global footprint, backed by its ability to model the price dynamics for assets from markets across the globe.