Family offices strive to provide a wide array of financial and investment services, so it's imperative that they have a complete picture of their clients' financial assets. But implementing a cohesive account aggregation strategy is far from simple. This article will explore some of the key advantages-and challenges-involved in aggregating client financial data.
Let's first define "asset aggregation": Asset aggregation is the process of collecting and storing financial information from multiple sources so the organization's key accounting and reporting systems can use it. An asset aggregation platform should provide adequate controls to guarantee accuracy and consistency across source systems.
A "complete" asset aggregation platform should not take any shortcuts. Data must reside in a central repository and data from all sources should be treated equally. Using Excel to combine data from a primary system with information from secondary sources, while perhaps satisfactory for certain portfolio reporting, would not constitute complete asset aggregation unless Excel replicated significant functionality in the primary system and included reconciliation.
In deciding on whether a specific aggregation solution is satisfactory in your environment, you should consider how far the implementation strays from the ideal. While you may not require every capability that a complete aggregation strategy entails, you should not accept a solution without careful consideration of how that system incorporates all of what you may need now and in the future.
Why Is Aggregation Important?
To understand why aggregation is important we just need to look at how having complete information impacts client service. Some key examples, relevant to family offices, include the following:
Consolidated Reporting: This is the most basic advantage of aggregating data. It provides clients with a coordinated picture of their financial assets that they would be unable to get on their own. Compare looking at multiple investment statements, each with its own schedule and asset classification scheme, with a combined statement where data is presented in a consistent fashion and summarized over all data sets.
Tax Planning: Consolidating information from multiple sources provides a much clearer picture for tax planning. Analyzing potential year-end tax strategies (e.g. tax-loss selling) when all data is combined goes from a paper-and-pencil exercise to a streamlined analysis of tax planning opportunities.
Risk Analysis: Only by consolidating all financial data can one get a true picture of asset diversification and the inherent risk of an individual's investment portfolio. In addition, having all information in one place makes possible the development of applications to compare managers and rebalance portfolios to meet investment objectives.
Why Is Aggregation Difficult To Implement?
While aggregating data from multiple sources may seem like a straightforward process (aren't computers good at transferring files from one system to another?) there are various issues that must be addressed to guarantee that an aggregation platform meets your expectations. Here are some questions to consider when setting up an aggregation system.
Do you have a core system that can store and process aggregated data? The typical ultra-high-net-worth portfolio includes a wide variety of assets, each with its own characteristics. Partnerships require custom functionality for allocation of interest. Private equity investments must process capital commitments and call provisions. Real estate may require processing of depreciation. If your system does not have asset-specific functionality, there will be limitations on your ability to fully aggregate and analyze your investments.
How will the data be imported? Manually entering data, while always possible, is not a viable solution for most family offices. Family office clients typically have many investments and manually inputting the information is a time-consuming and error-prone process, particularly if accounts need to be updated daily. For a portfolio with a large number of marketable securities, the only practical solution is to automatically import high-volume transactional and position data while manually entering low-volume data such as periodic hedge fund positions or personal assets.