Speaking Their Language: Integrating Insurance Data Into Wealth Management Systems

“The world is one big data problem.”

– Andrew McAfee, co-director of the MIT Initiative

According to a survey by research firm Gartner, “poor data quality is responsible for an average of $15 million per year in business losses.” They also found that nearly 60% of those surveyed didn’t know how much bad data costs their businesses because they don’t measure it in the first place.
We categorize these issues under “data maturity” when analyzing the technology infrastructure and supports processes of an enterprise wealth management firm.  Does the firm gather the right metrics about how data flows through their organization so they can manage things? Or do the just stumble from crisis to crisis and wonder why nothing works right?

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 Rich Romano, CEO, FIDx.

In this article, we summarized Rich’s insights on building data pipes between insurance carriers and wealth management firms, tips for understanding how different companies need to receive critical data and why every firm should agree on an internal data hierarchy to prepare for data outages and future issues.

In case you missed this webinar, you can click here to unlock your access to the full recording.

A Single Source of Truth

Craig: We’re talking about data moving smoothly for your organization. One of the things we’ve seen in our industry is a slow shift from 100% batch processing overnight files, to shipping critical data via FTP and flat files, moving more to API connections and streaming data. has this change made life easier or harder for vendors?wealth management data model

Lack of data standards is one of the many challenges confronted by wealthtech firms, Romano noted.   When trying to combine data received from multiple sources, there’s no consistency which results in a lot of extra work to normalize dozens of data elements.

Simple things like what is an account number or account value become complicated without standardization, Romano continued.  These data elements don’t have industry-wide standards like equities and other securities which can be identified by CUSIPs.

When you need to support different investment vehicles, especially complex ones such as annuities and alternatives that are illiquid, the amount of work required to transmit this data between firms increases dramatically, Romano said.

FidX has spent the past few years building data pipes to all the major annuity providers, so they have experienced a wide range of unusual data issues and requests, Romano explained.  Consistency is important since you can’t build a custom feed for every firm. There needs to be one internal standard. If one company asks for a particular value to be added to their feed and the developers do it because they had an unused field, it then gets sent to every other company that subscribes to that feed.

Why doesn’t FidX just build out a set of application programming interfaces (APIs) and deliver data that way?

APIs are limited when compared to a data feed because when making an API call, you’re constrained to whatever the max return value(s). If you need other pieces of data, you’re stuck, Romano stated.  Even though many “data feeds” are delivered via flat files, they still can offer more flexibility that an API, although they lack the ability to make programmatic data requests.

This becomes even more confusing when different types of client requests are handled by different systems that require different communication methods. For example, an insurance company might offer APIs for employee enrollments that can be completed in real time, but terminations require a file feed via an overnight batch.

It’s also important to note that while a web service-based API integration is almost always better than a flat file feed, none of them are 100% perfect—especially in the insurance space. However, we recommend selecting a vendor who offers API integrations with as many of their partners as possible.

Data synchronization also causes issues when multiple sources can update the same field(s), Romano said.  Ezra Group offers a Data Assessment Service that helps firms develop a Gold-Silver-Bronze methodology for automating these decisions across their key data sources.  Defining these backup processes save time when a crisis hits and avoids finger-pointing that often occurs in large enterprises when multiple groups have overlapping responsibilities for data.

These types of synchronization problems can be alleviated when the system of record is able to accurately trace all fields back to their data sources, observed Jeff Marsden, Head of Product for Xtiva Financial.  Part of that narrative requires high trustability in the data being onboarding for key systems like compensation performance management.

Speaking Their Language

PwC’s Annual Global CEO Survey revealed 49% of respondents put data inadequacy down to the fact their company data is siloed. Not only does this affect integrity, but it also reduces management’s ability to monitor performance across the company without extensive manual efforts to extract and import data.wealth management data model

To break data out of their silos, vendors like FiDx have been building connectivity between different parts of the industry and acting as a conduit to send the data to those that need it, Romano said.  The complexities of insurance data make it harder to consolidate it inside of wealth management platforms. To do so you need to speak their language, he insisted.

Developing what are essentially communication pipes between the insurance carriers and wealth management platforms is a hurdle that FiDx has successfully overcome, Romano noted.  This has enabled FiDx to get their data directly from the originating systems so they can service their clients more efficiently, he said.

Bringing their data directing into the wealth management platforms avoids advisors having to switch between the various carrier websites when buying different insurance products. We have seen insurance broker-dealers whose advisors have to go to different portals for life insurance, disability, long-term care, etc. Marketplaces like Envestnet’s Insurance Exchange, which is powered by FiDx might be able to consolidate multiple products in a central location.

The FiDx landscape of insurance products has been limited annuities up until now, Romano noted. The challenge with annuities and similar insurance-like products is that they can only be incorporated into wealth management as held away assets.  Since annuities do not share any of the characteristics of exchange traded products the challenge was to bring them into an account without them appearing like underperforming mutual fund accounts, he stated.

Romano explained that FiDx built out technology to consolidate all account data and reference it back to things like Morningstar IDs and capital market assumptions in order to generate holistic risk scores so that advisors can view across holdings at the household level.

Data Dictionaries

At Ezra Group, we work with enterprise wealth management firms to optimize their data infrastructures, which includes building data dictionaries that can be shared across systems and departments.  This greatly improves efficiency at larger broker dealers that merged and acquired other firms over the years that results in multiple data dictionaries and data taxonomies.

In the IBM Dictionary of computing, a data dictionary is defined as “a repository which is centralized and contains information of the data in the database such that the meaning, relationship, source of data, where it will be used and the format is clearly mentioned or specified”.

  • A data dictionary provides well-structured and clear information about all database objects making it easier to understand the overall design as well as identify any redundancies (duplicate columns, tables, etc.).

When it comes to the books and records for insurance contracts, the carriers should be considered the golden source, Romano insisted.  This is because they’re the ones that are on the hook for the legal and compliance work. They accepted the insurance contract and are responsible for reporting on it and managing it, he said.

We expect to see more insurance data being integrated into wealth management platforms, especially in holistic reporting but also for portfolio rebalancing with insurance products that have embedded securities like Variable Universal Life policies.  The ability to access allocations across many different accounts and custodians will enable advisors to provide better advice to clients and reduce their risk.

Portfolio risk can also swing based on security classifications, Romano noted.  One firm may have a security master that classifies a mutual fund as large cap growth while another classifies it as balanced. Investors with accounts at both firms would see different risk scores and different projected returns, he said.

Getting the data right from the originating source also eliminates issues around multiple handoffs that can see data slightly changed as it passes from system to system and firm to firm.  Reconciling this data is more labor intensive, Romano said.

Updating beneficiary information can cause conflicts when consumers make changes at the carrier site but not at the custodian or vice versa, Romano warned.  There’s no one platform that acts as the master controller in these scenarios which requires a lot of manual communications, he said.

There are some systems that can provide centralized data control such as Xtiva’s Sales Performance Management Platform that supports a broad universe of data, Marsden explained.  Each enterprise client is allowed to configure their instance to increase local efficiency while still allowing Xtiva to perform analysis and benchmarking across multiple firms.  There needs to be a limit to the amount of configuration clients can do since too much would add unnecessary friction to the experience, he said.



The Wealth Tech Today blog is published by Craig Iskowitz, founder and CEO of Ezra Group, a boutique consulting firm that caters to banks, broker-dealers, RIA’s, asset managers and the leading vendors in the surrounding #fintech space. He can be reached at craig@ezragroupllc.com