“We’re entering a new world in which data may be more important than software.”
– Tim O’Reilly, founder, O’Reilly Media
“Data is the new oil,” is a phrase that I’ve seen written a lot recently. While they’re both immense, untapped and valuable assets, data’s value can be repeatedly extracted over and over to gain new insights.
Many companies still consider their data infrastructure to be a cost center when it should be a profit center. If managed correctly and treated as an enterprise-wide corporate asset, enables sharing of information about products and customers. This will deliver opportunities to up sell, cross sell, improve customer service and retention rates. By using internal data in combination with external data, there is a huge opportunity to create new products and services across all lines of business.
As part of our work to help our enterprise wealth management clients get the most benefit from their data assets, Ezra Group has partnered with Xtiva Financial Systems to produce a series of webinars. Our goal is to bring leading industry experts in data strategy, data architecture and systems implementation to share their experiences and best practices.
We recently produced the fourth webinar in the series called, “The Tower of Babel: Tips on Consolidating Wealth Management Data From Multiple Sources” which included panelist Mike Stern, Head of Product, Riskalyze.
In this article, we summarized Mike’s insights on leveraging data to facilitate client engagement, about his firm’s experience transitioning to APIs the benefits of building a dedicated data integrations team.
In case you missed this webinar, you can click here to unlock your access to the full recording.
Using Data to Facilitate Client Engagement
The wealth management industry feels very far behind what the average consumer experiences with most retail websites, Stern noted. The vision for the advisor experience that Riskalyze has been working on incudes being able to update a data field in one location and have it automatically flow through to every other system that needs it. They would also like to deliver a consolidated Dropbox-style or Evernote-style data service where advisors would have access to aggregated information at their fingertips, he said.
“Data sharing is the way to optimize higher-relevant data, generating more robust data and analytics to solve business challenges and meet enterprise goals,” according to a recent Gartner report. “Data and Analytics leaders who promote data sharing have more stakeholder engagement and influence than those who do not.”
Gartner predicts that by 2023, organizations that promote data sharing will outperform their peers on most business value metrics. Yet, at the same time, Gartner predicts that through 2022, less than 5% of data-sharing programs will correctly identify trusted data and locate trusted data sources.
Everything starts with data, Stern continued, so Riskalyze places an emphasis on pulling all related data together so it can be surfaced and presented to the client in ways that are useful and efficient. The company vision is to deliver an elegant experience around aggregated data to facilitate client engagement, he said.
Vendors talk a lot about integrations, but they’re not useful without accurate and timely data, Stern warned. His vision is how do we take these customer insights for advisors, and even home offices, and business insights for advisors and home offices, and surfacing that up?
We talk about business intelligence tools and a lot of tools that people might use to do this, but you still have to get the data in there. And that’s really been the biggest challenge across our industry.
The Transition from Integrations to APIs
The entire industry is being pushed to migrate away from application-specific integrations and towards APIs as a service, Stern explained. What this means is that the old way of manually setting up integrations directly between two applications, such as eMoney and Redtail, for example, will be eliminated. They will be replaced by application programming interfaces (APIs) that can provide real time data transfers in a much more robust manner.
Many of Riskalyze’s clients and partners are even mandating the use of APIs as part of system upgrades and internal platform development efforts, Stern reported. As more wealth management firms take on the responsibility of building parts of their advisor and/or client experiences, they realize that they own the ongoing support costs, which should be lower using APIs.
A lot of the data that Riskalyze processes is gathered from their clients, enriched by the vendor’s internal systems and staff and then redistributed back to the same clients. “It’s like this revolving door,” Stern observed.
Based on the recent survey conducted by API integration platform Cloud Elements, 83% of global firms consider API integration a critical part of their business strategy to drive digital transformation initiatives. Respondents reported improvements across many crucial elements of their businesses including Increased productivity (59%), Increased innovation (51%), and Direct increase in revenue (43%).
Even as Riskalyze is moving towards higher use of APIs, they still must process hundreds of thousands of files every day from external partners that have not upgraded to real time data transfer technologies, Stern stated. The data that is extracted from these files is often missing key parameters and fields that must be added by Riskalyze before they can be sent to downstream systems.
An example Stern shared is that Riskalyze supports multiple custodians across multiple platforms. Sometimes this data may be missing household information or risk objectives. Also, tax lot data sometimes doesn’t come through the API’s and can only be delivered as a file.
The Benefits of a Dedicated Data Integrations Team
The financial services industry is particularly data-intensive. According to IDG research, 49% of financial services companies have more than ten internal or external sources of data that are critical to their business processes. The problem is that all of these systems create data silos that act as a drag on innovation. In an industry that continues to evolve rapidly, that can become a competitive disadvantage over time if it is not addressed.
Riskalyze has dozens of data sources that must be combined, cleaned and normalized to feed downstream systems and clients with the data they require to operate. Until recently, this work was performed by many people and groups spread out across the company.
Stern explained that they are standing up a team dedicated specifically to managing the flow of data into and out of the firm. The goal is to ensure that their data helps to provide the best experience in the industry and deliver a seamless integration between different third party platforms and technologies.
Nearly two-thirds (63%) of data scientists in financial services firms say their organization is not currently able to combine data and analytics in a single environment.
Besides managing data that comes in from external partners, Riskalyze has to be aware of how data flows between apps on the advisor’s desktop, Stern noted. It can be difficult and cumbersome for advisors to understand how data entered into one application gets transferred to another application via integrations.
The average advisor has 8 or 12 different applications they must deal with just get their daily work done, Stern reported. Many advisors have to memorize the direction that data flows across their financial planning, CRM, custodial, and other tools to avoid overwriting or duplicating data.
Data Consolidation Horror Stories
Everyone on the panel agreed that performance reporting and billing are usually the source biggest horror stories across the industry. Stern shared one story on a client that had sent out a batch of hundreds of performance reports that were used to generate their billing invoices. The only problem was that the reports were wrong! The reporting timeframe was off by a single day, which made the performance calculations incorrect.
The operations team realized the issue shortly after the reports were sent, but it was too late to stop some of them being used as the source for the quarterly billing and hundreds of client accounts were debit using this incorrect data. This required that the operations team to manually net the difference and adjust all of the account, which was quite a nightmare, Stern related.
Stern also told a story of a client that either forgot to pass through number of model updates or the system was ignoring the changes. They only noticed it three months later. And at that point, it didn’t make sense to apply all of the updates, so they tried to calculate the transactional differences between the two points in time. Needless to say, if was a big mess for a long time, Stern, said.
House Holding Requires Data from Multiple Sources
House holding is loosely defined as the process of grouping related customer records for services like model management, rebalancing, reporting and/or billing. What the house holding process allows is the ability to manage many separate accounts as a whole across the aggregated relationship of a family. This can become very complicated, very quickly due to differences in how accounts are managed and identified, Stern noted.
The exact definition of an account can vary from vendor to vendor. How do they identify an account number? How do they identify a household across multiple custodians and multiple types of firms? These factors strongly influence how easy or difficult it is for vendors to manage household data in their system and for advisor firms to be able to access it.
For Riskalyze, and probably many other vendors, house holding is driven by account registrations. Most platforms handles them in slightly different ways, but it’s important to enable each advisor to choose how they want to group accounts and how they want them to be displayed, Stern insisted.
We have another product feature coming out which is portfolio groupings, right? A lot of firms group accounts in different ways. Maybe their performance reporting only neither a different part of a risk assessment and so, grouping accounts and what we’re calling account collections on our side, be able to household being able to group accounts. Thinking about the hierarchy is really what we’re spending a lot of time in our platform team right now putting that data together.
So you have the central repository, a data lake, a data warehouse, or whatever the case may be, you have the central place for their data.
And as we pull in all this data and maybe somewhat duplicated data from different places, aggregators versus custodians, and things like that, where you have different naming conventions, and different parameters and, and metadata for those attributes.