One of the books tech founders consistently quote is “Crossing the Chasm” by Geoffrey Moore. It has become something of a bible for tech sales and marketing.
Although Moore wrote the book in 2006, some of his thinking could have been written about the current state of artificial intelligence.
“To get an early market started requires an entrepreneurial company with a breakthrough technology product that enables a new and compelling application…,” one quote reads. “[It needs] a technology enthusiast who can evaluate and appreciate the superiority of the product over current alternatives, and a well-heeled visionary who can foresee an order-of-magnitude improvement from implementing the new application.”
One of Moore’s self-avowed fans is taking his advice to heart. ARQA CEO Haik Sahakyan is billing his company as being at “the forefront of the financial AI revolution.” ARQA is focused on applying AI-driven technology to the 21.7 million people on the planet who have more than $1 million in assets, better known as high-net-worth individuals (HNWIs).
The revolution will be marked by AI-driven automation of routine tasks that can reduce operational costs and improve efficiency, Sahakyan said. This includes everything from customer service chatbots to monitoring financial transactions. It also includes enhanced decision-making and analysis, with AI processing vast amounts of financial data to identify trends, risks and opportunities, which can aid in investment decision-making and risk management.
AI Chat is a data-agnostic generative AI application for wealth management, where advisors and their clients can avoid signing into multiple systems to access their portfolios. Users and advisors can ask it to monitor data based on specific criteria, and then get notified when triggered so they never miss changes in the data that are important to them and their clients.
KorScript is a simpler AI-enabled application aimed at reducing manual data entry and research. Currently, advisors manually enter capital calls, distributions and valuations from PDFs for alternative investments. With AI, ARQA said it can simplify this process and cut down on the number of documents needed before it accurately processes data from PDFs as well as other transactional data that comprise a wealth portfolio.
Both products are built to solve for the pain points that banks, fund managers and HNWIs encounter when using multiple platforms.
“We’ve completed many surveys, and prospects usually have more than two systems and datasets that they’re working with to manage their operations,” Sahakyan told PYMNTS. “Many potential clients want to use ‘best-in-breed’ platforms. Therefore, they end up using disparate systems and datasets that don’t always ‘talk to each other’ as well as they should, which leads to inherent operational inefficiencies. The outcome of the AI revolution will be pretty broad, but if I were talking to a roomful of bankers, I would tell them that the highlights will be operational efficiencies.”
One of the things that makes ARQA unique is its target audience. Instead of aiming solely at advisors and bankers, it has included individual users. Here Sahakyan leans on Moore’s “chasm” points about tech innovations, starting with a small set of innovators and early adopters. Even though ARQA is currently waitlisting potential clients, Sahakyan said he expects these early adopters to be innovative and ready to make independent buying decisions.
For example, an individual can convince an institution to be an early technology adopter, but an institution rarely takes the lead on a technology purchase. Sahakyan said some of his clients are managing more than three technology adoption lifecycles.
“HNWIs present a challenge because each one can be unique in the way they want to interact with our platform,” he said. “Instead of having one advisor who uses the same workflow for a majority of their clients, you can have each HNWI doing something different with their portfolios and their financial data. Therefore, I believe this creates a unique, albeit interesting, problem for their segment where their sheer volume of users can drive numerous feature requests and solutions.”
Sahakyan’s background is in data. After leaving Addepar in 2017, he built a data feed aggregation business that he exited a few years later. However, he stayed in touch with many clients and realized that although many were unhappy about their tech stack, the answer was not to build one more system with a few more features.
His mission came from the understanding that something radically new was needed to drive current systems to their full operational capacity. He said he likes to use the analogy that his clients’ infrastructure is the soil, their data is the water, and the seed is ARQA’s AI.
“It’s up to them if they want to grow a cherry tree or a sequoia,” he said. “AI in wealth management means so much more than just generative text about market data. Personalizing the data truly allows the AI to go above and beyond to drive insights and analytics in an efficient manner versus having to jumble through multiple systems and reports repeatedly.”
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