Faulty data models and poor data hygiene can undermine your investments in systems
If your trust company or family office is frustrated with your current systems, the fault may lie in the data you are using rather than the software. Even the best software platforms, offering the most intuitive dashboards and processes with insightful layouts and logical flows, are at the mercy of the data model being used and the quality of that data.
If you’re loading data into your ERP, CRM, accounting platform, GL, etc. and subsequently suffering from any of an array of common data issues, you will see, at best, a lot of time being wasted on data reconciliation and review. Worse, if your employees or management don’t trust the data, they will abandon use of the systems involved. Worse still is if those data issues extend to the reports and data your clients see—if your clients can’t trust the data you are reporting to them, they won’t be clients for long.
As a result, the importance of data hygiene and a focus on identifying appropriate data cannot be overstated. Indeed, garbage data going into a system will result in garbage decisions coming out. Your company cannot afford this issue.
Here are some of the more common data issues that we see with trust companies and family offices. If you recognize any of these, maybe it’s time for a closer look and a plan to find and fix these critical issues.
As new legal entities, related parties, contacts and other information are added to trust accounting or portfolio management systems, CRMs, or email contact lists—and then edited over time—errors in data entry are bound to occur. We see this all the time as we onboard new WealthHub clients: cities entered in the legal entity field, first and last names entered in a first name field, fields that should be required left blank, and many other mistakes of that nature. This is not that surprising given that input mistakes will happen and there is little reason to export your data and systemically review it. But it does mean that you end up with a lot of inaccurate or incomplete data over time which can lead to misinformed decisions or embarrassing miscommunications.
Data conflicts from disparate systems
It is common for key information on legal entities, beneficiaries, and financial accounts to be stored and used in multiple places. These could include trust accounting systems, Outlook or other email clients, portfolio management systems, GL systems, and excel spreadsheets or word documents. What happens when a new address or email is entered in one of these places, but not in another? Or if financial info is edited and corrected in an Excel spreadsheet or report, but not in the underlying system of record? Or vice versa?
The solution to this issue is to maintain one single system of record for each type of data, then properly integrate other systems such that updated and accurate information is propagated across all systems where that data is consumed as soon as it is entered or updated in the system of record.
Relationship data being personal, not institutional
Many of the details that guide effective servicing of UHNW relationships are kept in the personal records of the trust officer or relationship manager. Histories of interactions, requests for special or personalized treatment of assets or tasks, and lists of tasks that don’t make it into tickler systems are all examples of the types of details that are critical to delivering the service levels your clients expect and deserve. These details, however, are often hidden in lists in personal word documents, Excel files, or Outlook reminders. What happens when that trust officer goes on vacation or retires or leaves for a competitor?
Activity histories, upcoming tasks, notes on asset servicing, and other relationship data need to be an institutional asset available to others in the organization, not a personal data asset that walks out the door with a departing or absent employee.
Too much or too little data
One of the most dangerous situations involving data is when it is incomplete—missing critical fields or transactions, for instance. When this happens, it does not necessarily show on a high-level bar graph or pie chart or report. If you’re looking at a dashboard or report that is reliant on information that is missing and are making critical decisions on investments, or servicing, or management, you could be making crucial mistakes.
A close cousin of the incomplete data issue is the “complete, but useless” data issue. Many organizations are collecting data that is not relevant and not being used. If that data is collected automatically, then there is little cost other than making it more difficult to find the information that is of actual use. It is a more significant problem when this unnecessary data has to be manually entered; besides being inefficient, this will make it less likely that the information you do need is entered on a timely and complete basis.
To address incomplete data, systems should have clearly defined fields identifying required data and either not allow users to save records or have reports and reminders concerning data that should be required. Seems simple, right? But we see data sets all the time that are missing information that is required to accurately service an account or asset. As for data hoarding, we suggest working backwards from your reports. Identify which data is actually being used in internal or external reports or processes, and be disciplined in deleting data elements that add work to input—but don’t add value.
Financial data aggregation and reconciliation
This is probably the largest issue (or set of issues!) surrounding data for trust companies and family offices. Most trust accounting systems were originally structured to handle omnibus accounts at single financial institutions. But most trust companies now have to deal with held-away accounts, while directed/delegated trust models—by definition—have accounts scattered across various custodians. The adaptation to this has been to partner with financial data aggregation providers to get bank and brokerage balances for liquid securities. For special assets like hedge funds or property, values and transactions often have to be entered by hand into accounting or portfolio management systems. Many family offices enter all of this data manually into GL systems.
The result is a data reconciliation nightmare. Some organizations throw large amounts of resources at this problem. Others throw up their hands and outsource their reconciliation work. The bad news in the short term is that data aggregation has been getting progressively worse; many data aggregation provider rely on scripted logins into online banking or brokerage websites to download transactions and balance data. The advent of multi-factor authentication and challenge/response security questions has chewed into the reliability of these services to consistently deliver financial data without login information being rekeyed frequently. The good news here is that “Open Banking,” or access to bank/brokerage information through common APIs, appears to be on its way (no matter how slowly) in the US. And some financial institutions have gotten out ahead of the curve on this, creating and publishing APIs that make direct and reliable data connections easier and more secure.
This is a subject complicated and critical enough that we will come back to this later with an expanded piece, but the key takeaway for consideration by trust company management and family offices is as follows: the availability of an up-to-date and user-friendly API from your banks and custodians should become a prime determinant in selecting a financial institution. If your bank is hostile to data aggregation (as some are) or is on a technology platform that cannot accommodate direct data integration, you should be considering moving your accounts. Your reconciliation burden and ability (for you or your systems vendors) to reliably control and download your information will be critical to improving operational efficiency, financial data quality, and ease of account onboarding.
There are also a growing number of vendors specializing in both aggregation and reconciliation as a specialized service, rather than as a broad range of outsourcing services.
How many of these issues are you seeing (or rather, not seeing) in your company? It is critical to have an internal discussion to first understand the health of your organizational data and then to evaluate how that health can be maintained at the highest level. This is needed to make informed decisions, to provide the highest levels of customer service to UHNW clients, and to report and communicate effectively both internally and with your clients or family members.
Here at WealthHub, we have placed data health among the highest priorities for our trust company and family office clients. Examining and addressing data health is the first step in any new project implementation we undertake. We recognize the importance of good data and have seen every type of causal issue that can bring errors or incomplete results to company reports, dashboards, and decision making. We know how these issues get started and we know how to correct them.
If your organization is experiencing similar issues, talk to us. Let’s discuss your financial data issues, explore ways to address them, and get to the point where your team trusts your trust data!