During our 3rd Digital Thought Leadership event focused on the digitalization of wealth management, our panel of industry experts addressed five key questions about customer data and emerging industry trends. The panel included Roopalee Dave, Director in Wealth and Asset Management at EY, Sebastian Dovey, Non-Executive Director at Entrepreneur’s Investment Office, co-founder of Scorpio Partnership, and WealthBriefing’s 2018 Wealth Management Thought Leader of the Year, and Oliver Brupbacher, our innovation-driven CTO.
Their answers will help you better understand how to tackle the typical data-related challenges facing the wealth management industry.
How do you ensure you have as much data as possible but also are compliant with GDPR and other regulations?
According to Roopalee, the main challenge is how to manage and navigate data. Your end clients want to know that their data is safe, which is why cyber and operational resilience are becoming focus areas for wealth management companies.
GDPR has given companies the opportunity to ensure that they have data structures and data lakes that are not only in place but that are being properly used.
How do you know what to do with all the data collected?
Oliver Brupbacher says that wealth management firms should make smart use of the data by complying with regulations, driving better decisions, providing better guidance to clients, and automatically generating user interfaces that adapt to their individual situations.
He explains what to do with the data when it’s not needed anymore: “When you build a workflow system, process, or segregated piece of onboarding, what’s built in there by design is destroyable data. This means that when someone enters data into that system, it makes sure to only ask for the information that is absolutely needed within that context.” Some of the things, like user interfaces, can be constructed automatically based on available data. We’re exposed to so much data and when you build a process, you have to make sure that data can be destroyed or anonymized if a customer decides to have their data removed.
How do we get the right data and aggregate it to be relevant to clients and advisors?
Roopalee says that the best market approach for a company is not to “unplug” what it already has in its technology stack but rather to look at which FinTech companies to “plug into” in order to empower the organization.
Oliver Brupbacher builds on that sentiment: “Data is part of a company’s maturity but it’s not enough to focus solely on that data or on technology. It’s the knowledge that companies should focus on; the data has to become executable.” Ultimately, he says, what you want is knowledge that's executable. Based on that knowledge, a financial advisor needs to guide the customer as well as collect more data in order to perform their tasks, make better decisions, and drive processes. Complex knowledge (such as knowledge about different regulations) is streamlined into an understandable and usable process.
How can you utilize data without crossing the “creepy” line?
Trust plays an important role in not crossing that line. Most end clients would like to have the option to make changes to how much data their financial provider has access to. This is especially true with the younger banking generation.
In order to retain these customers, you need to build trust and loyalty. The key question is how to actually do this. Sebastian advises to start by helping customers manage their financial data. Once a baseline is established, people start trusting the source of the data as well as the curation provider.
Roopalee acknowledges a trend in shifting from marketplaces to the development of ecosystems, stating, “Companies shouldn’t be competing over customers but instead be collaborating so they can better serve them. Ecosystems, for instance, are one of the entry points to accessing more holistic data.”
How is the wealth management community benefiting from AI?
Brupbacher made it clear that AI isn’t as mature as most companies would expect it to be, and it’s important to remember that it has an assistive role in decision making but shouldn’t be a decision maker in and of itself. Organizations can use AI as part of an automation process, where it can support in data-driven decision making. However, the current status of AI is that it’s very fragile and hard to reproduce. At the same time, we need to be able to reproduce these decisions that have a regulated impact.
Key takeaways that wealth management firms can apply to the use of data:
The first step towards data governance is identifying business objectives. Data is the medium through which you can ultimately reach that goal, and it plays an integral role in the business strategy
Evaluate how you’re capturing and managing existing and potential customers’ data; you want to make sure you’re not crossing the “creepy line” when you collect data and that it informs your digital processes
Remember that any data-driven wealth management practice should be a benefit-led process and not just a risk assessment exercise