How is the latest technology helping wealth and asset management firms to improve their data?
Data is a core aspect of wealth management and the latest advancements in technology are helping firms to improve their usage of data. Not only is this enabling them to become more efficient, but it is also improving the output of their advisors.
FinTech Global spoke to several players in the WealthTech space to get an understanding of how new technology is revolutionising wealth and asset management through improved data capabilities.
Technology is not only improving the usage of data but is actually making data more powerful. Tamara Kostova, CEO of Velexa explained, “Data has evolved from a simple reporting tool to the lifeblood of today’s wealth management businesses. It drives automation, enhances client experiences, and boosts advisor efficiency, making it a critical strategic asset.”
For instance, AI-driven analytics is one area data can hold tremendous power, and these analytics allow wealth managers to process vast amounts of structured and unstructured data. Through this they can uncover investment patterns, automate risk assessments and improve portfolio management.
Kostova added, “Furthermore, thanks to data-driven insights, hyper-personalised investment strategies are now possible. Wealth managers can use technology to tailor portfolios that reflect each client’s unique preferences, goals, and risk tolerance. By leveraging AI and cloud-based solutions, wealth management firms can offer a more customised, proactive service, fostering stronger client relationships and enhancing overall satisfaction.”
However, firms cannot simply assume they can implement a nice piece of technology, like an AI-driven analytics tool, and expect it to work perfectly. Firms have a lot of legacy technology that has created siloed systems, keeping data segmented and not usable. If a firm wants to make the most out of its data, it needs to ensure it has technology that can access all its data.
Fredrik Davéus, CEO and co-founder of Kidbrooke, explained, “For Wealth Managers you have investment and market data, and you have customer data and also data on how customers use and interact with your services. Here it is paramount for improved data use to have your data in good order and accessible in a structured and scalable way. In our experience, most of the time the challenges lie in getting the data you need to the algorithms and analytics you want to run/use. Here, modern solutions within data aggregation can be helpful to pave the way for improved data use.”
Yohan Lobo, Industry Solutions Manager for Financial Services at M-Files, also commented on the impact technology can have through data. By establishing a modern data architecture and integrating advanced technologies, such as AI, machine learning and workflow automation, wealth managers can analyse more data, spot patterns and offer personalised financial advice.
He added, “This can improve client satisfaction and loyalty, thereby increasing assets under management. Enhanced data usage may also make better advice accessible to more potential clients who have not traditionally had access to wealth management firms. Firms will still be able to offer personal service to more clients as advisors become more effective based on new technology.”
Echoing this Ralf Heim, Founder & Co-CEO of fincite, also pointed to the dramatic impact stronger data access can have, describing it as ‘game changing.’ He said, “Through modern advisory s Modern advisory software empowers advisors to gather 3x more high-quality data for deeper customer insights. Cutting-edge technology seamlessly integrates financial planning, aggregated wealth across multiple custodians, market and fund data, and the bank’s investment logic—automatically. The result? Advisors get instant alerts when a customer’s risk profile shifts, financial goals come closer or drift away, or wealth levels change—ensuring they stay ahead and deliver smarter advice in real time.”
Use cases
While this provides an overview of how technology can help, the respondents offered some practical use cases of how technology can empower firms to make better use of their data.
Kidbrooke’s Davéus believes one of the greatest use cases for how to improve data management comes from connecting systems. As mentioned, many wealth management firms are held back by siloed data or data that is scattered across different business systems. While accessing customer data might be challenging, and pose potential privacy issues, market and investment data offers an easier path to success.
“Here we see some great use cases with our own tech aggregating market and investment data across a number of sources, normalising it and providing it to the organisation via easy to use and intuitive APIs. This leads to consistent data across the org and its customer channels, it leads to reduced time to market for new features and capabilities, and it can really deliver business value in the hands of advisors and relationship managers who can provide unparalleled insights and customer value.”
everyoneINVESTED managing director and expert general manager Jurgen Vandenbroucke, offered a couple of examples where technology can help wealth management firms improve their data. The first of these is with big data and investment performance.
He explained, “Past performance is a key part of any (robo)advisor’s pitch, despite the disclaimer that past performance is no guarantee of future returns. Anything that helps improve performance is therefore welcome. Technology can help in this regard, for example by enhancing the ability of humans to extract predictive value from large data sets.
“Predicting returns is at the heart of portfolio construction and asset management. And while financial markets prove difficult to capture in repetitive patterns, there are plenty of proponents of technical analysis, fundamental analysis, and more, that motivate why prices will go up or down. Advances in big data and machine learning (ML) can strengthen our ability to support such motivation. In fact, we are seeing a growing number of investment portfolios managed primarily or exclusively on the basis of ML models, for example Optimum Fund Enhanced Intelligence Global Allocation – KBC Private Banking. Certainly, there will be a learning curve, but the (past) performance of these products gives them a lot of credit.”
The second area Vandenbroucke pointed to was intent data and investor onboarding. The everyoneINVESTED team believes in the power of technology to expand the reach of a bank’s investment offering. A bank’s mobile app can reach more people than a brick-and-mortar branch, for example. However, they would need to ensure they can build a digital relationship based on personalised and engaging messages to ensure it is successful. This is where data becomes vital.
“Data is not an end in itself. Data is a means to an end. The real value, in our view, lies in the marriage of data science and decision science.
“On the one hand, we use data science to generate and process data. This can range from customer profiling based on payment data to our science-based customer intent measurement tool, see Behavioral risk profiling: Measuring loss aversion of individual investors – ScienceDirect. Just as important as the data itself is the best way to use them. This is where decision science comes in.
“Over the years, our understanding of how people make decisions has improved dramatically. In the context of investor onboarding, this means we can use data to tailor and personalize digital services. Digitization need not be limited to cold automation. The business impact is huge, without an explosion in operational expense. The scale that can be achieved is far beyond the capabilities of standard business models.”
Velexa’s Kostova pointed to a solution used by JPMorgan Chase on how AI-driven analytics can improve the operations of a firm.
She explained, “JPMorgan Chase demonstrates the power of AI across its operations, significantly enhancing both efficiency and client outcomes. Its COiN platform streamlines compliance by automating the review of legal documents, while LOXM optimises trading efficiency in global equity markets.
“A standout innovation is JPMorgan’s IndexGPT, a generative AI tool that combines advanced data analytics and machine learning to design personalised investment strategies. By analysing market trends, economic indicators, and client preferences, IndexGPT enables wealth managers to create customised portfolios that are adaptable to dynamic market conditions and aligned with clients’ evolving financial goals. Similarly, Goldman Sachs employs machine learning to predict market trends and optimise portfolio strategies, enhancing decision-making for wealth clients.”
Finally, Fincite’s Heim outlined a few areas where improvements can be felt. One of these is suitability monitoring, with aggregated data allowing advisors to ensure investment strategies are always aligned with the customer.
Elsewhere, compliance can also greatly benefit. For instance, integrated data allows compliance teams to ensure they have all the up-to-date information on products and ensuring requirements are always being met.
A third use case Heim outlined related to intelligent sales. He stated that wealth aggregation and financial planning provides deep insights into the perfect timing and reason to engage with a client. “Turning cold calls into meaningful conversations,” he explained.
Finally, he pointed to hyper personalisation, which has become a major trend across the wealth management sector. He said, “Advanced data-driven proposals tailor strategies to each client’s unique situation. Financial planning reveals lifetime goals, wealth aggregation uncovers private market or real estate exposures, and estate planning considers family structure—all shaping investment horizons, risk appetite, and protective measures.”
Ultimately, all these use cases result in stronger client relationships, smarter decisions and future-proof wealth management experiences, he added.
Why improving data access should be a priority in 2025
On a final note, the respondents outlined why improving data quality and accessibility should be a priority for wealth firms in 2025.
One thing they all agreed with is that it should be a priority for wealth management firms in 2025 and beyond.
M-Files’ Lobo explained, “Garbage in, garbage out” is another way of saying that the quality of the output is directly dependent on the quality of the input data.
“If “data is the new oil,” then just like oil, it needs to be refined to power processes or new technology like generative AI. Raw data, much like crude oil, is not immediately useful. It needs to be cleaned, organized, and structured to unlock its full potential and drive valuable insights.”
As such, he encouraged firms to ensure their data is structured properly and connected with robust data management practices. These include data governance frameworks, data quality assessments and the use of advanced tools to connect information across various systems and processes. “By operating and maintaining a connected, well-structured and high-quality data repository, firms can harness the power of automated workflows and generative AI. This will augment advisor and firm effectiveness and improve client experience & loyalty which will ultimately grow assets under management and revenue.”
Velexa’s Kostova noted that the wealth management industry is becoming increasingly data driven. Firms will need to have strong data quality to make informed, accurate decisions and enhance portfolio management and risk assessments.
“Accessibility is equally crucial as it allows wealth managers to quickly access real-time insights and respond promptly to changing market conditions or client needs. In 2025, the ability to integrate and analyse data from multiple sources—such as market performance, economic trends, and individual client portfolios—will be more important than ever.”
Echoing a similar tone, Kidbrooke’s Davéus added, “Data quality and accessibility is key to use the new capabilities in analytics, including AI, that is now rapidly being developed and made available at increasingly lower cost to the market.”
The benefits of technology can have when coupled with data have been listed throughout, but on a concluding note, Heim said, “At the end of the day, wealth management is a trust business. The best relationship managers have always been great listeners. A strong data foundation is the digital equivalent of truly understanding your clients—helping advisors deliver more relevant, timely, and impactful advice.”
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