How is data being used in the wealth management sector today and what benefits are you seeing? Also, what improvements do you expect to see in the future in wealth management if data is more efficiently and effectively utilized?

Traditionally, data was tightly controlled and infrequently refreshed in wealth management shops. Internally, not everyone had access to all the data – some could view holdings, some performance, some account data, for example, but the teams worked constricted by data silos and without real-time access. Externally, clients or third-party contacts received limited slices of the data in a periodic fashion, such as in quarterly client, advisor or custody reports, without real-time access.

Today, investment advisory firms can differentiate themselves through data by providing more detail and real-time availability to clients. They can also manage their business better when work stream silos are removed, leaving behind an integrated front, middle and back office concerning data, and obtain comprehensive data views into activities that are important to the business.

Today’s uses and benefits of data in wealth management are many and varied and include the following:

• In operations, data can be used to check counterparty effectiveness, for example, how good is your custodian, what’s costing you money, what are reconciliation match rates. In terms of billing and account management, integrated platforms can tell you about your operations and help manage cash flow better. Data is also key to building and managing investment portfolios and measuring performance.
• In operations, data can be used to check counterparty effectiveness, for example, how good is your custodian, what’s costing you money, what are reconciliation match rates. In terms of billing and account management, integrated platforms can tell you about your operations and help manage cash flow better. Data is also key to building and managing investment portfolios and measuring performance.
• Data can enhance the customer experience. Investors, advisors and their clients expect to be able to access a wealth of data in real time and holistic/aggregated views of their investments. Firms that can meet investors’ data expectations and ever-increasing reporting standards have an advantage over those who can’t. A particularly significant aspect of current best-practice data analysis platforms is being able to segment clients and personalize investment proposals.
• Data can also enable a more personalized experience by providing insights and ideas to the advisor.
• Data’s capacity to offer improved disclosure on risk exposures, fee structures and expense allocations help managers ensure compliance with portfolio mandates and regulations, along with the ability to survey operations, accounts and portfolios to identify and manage risk.

In the future in wealth management, if data is more efficiently and effectively utilized, I believe we'll see a host of improvements that transform the industry. Gone are the days when a client had to call their advisor to check in on the latest market news and how it has affected their investments. Wealth managers will apply data for more trend and statistical analysis and to give the best service to their clients. They will use big data sets and analytical tools to develop, implement and adjust new strategies based on quantitative content, improving success.

Managers can view data in real time, see the trends affecting the market, and take action. For example, if a manager is tying his expectations of future bond market yields to stocks and inflation, getting more insight more frequently on these markets will serve to adjust and optimize strategies. With an ability to see all relevant market alerts in a dashboard in real time – and, at the same time, recognize which specific portfolios, assets or client segments for which these messages are relevant, advisors can use disaggregated data to make consolidated decisions.

Similarly, data will provide real-time, active and actionable insight and direction to meet investor preferences and objectives, such as for sustainable investing. As sustainable investing, ESG, and other strategies grow in popularity, so too will the need to increase efficiency in data capture, maintenance, and reporting. Data analysis will help prove the value of strategies, their effectiveness and their fit (or not) for a particular investor.

Compare that to the past, where a benchmark file would be accessed, compared to a portfolio, and compel adjustments, all in a passive, manual, time-consuming and risky fashion.

I see a firm’s data capabilities and the strides made in this area ultimately leaving two types of investment managers in the future: small niche/boutique firms and large broker-dealers (wire houses); the middle may disintegrate.

Niche players can use available data to deliver bespoke service and solutions, customized products for investment options and strategies based on market trends and current data. With a much more timely approach to effectively deploying data to develop investing strategies, products will have a custom feel for clients and be more active, more responsive based on trend analysis using real-time data.

Broker-dealers (including large mass-management firms like Schwab, Fidelity and Vanguard) are managing a very large number of accounts. Data and related tools can service their clients efficiently and effectively by making macro changes en masse in a bespoke way. Clients see the changes they want while the broker/manager is able to implement it at scale by applying data triggers and portfolio rules.

In a more effective, efficient data-driven world, the middle space will be swallowed up and aggregated by the large players, or become highly specialized and join the ranks of the boutique providers.

What solution(s) does your business offer to the wealth management sector that focus on data? How do they work and how do they help wealth managers?

Data is critical to the operations of any business and we’ve focused on how our platforms can bring data to consumers that is easily ingested and integrated, both derived from SS&C solutions as well as from external sources for the full, clear picture. We focus on data management and quality, given how critically important it is, and have structures and tools in place for data quality management that goes hand in hand with the operational tools developed to work with that data. Key SS&C platforms for the wealth management sector include SS&C Global Wealth Platform and SS&C Aloha, our new investment operations platform that provides extensive asset class and functional support across the front, middle and back office.

Our most recent platform, Aloha, has a real focus on removing data barriers and silos through a single non-traditional data model. I see that as a huge step forward bringing robust enterprise technology to wealth management while at the same time reducing risk by erasing data integration points within the wealth operations stack.

From the perspective of your business, data monitoring and data governance are as important as the data itself. We can look at the broad spectrum of data across front, middle and back office; monitor processes through health checks; and bring to light what data elements aren’t where they need to be – pricing, custody, pending trades, compliance, etc. It is difficult to integrate multiple data sources, which provide different data sets with different data formats, without the native data management capabilities of a platform like SS&C Aloha, which reduces laborious processes for the collection, compilation, and cleansing of large amounts of information. As a result, it’s much easier to evaluate data and act on it. We offer the ability to evaluate and analyze your data dominion to ensure everything is correct and contiguous.

Our platforms monitor and indicate your operational health and tell you why your health is at a given level. For example, the system may highlight a security name mismatch so you can correct it, adjust your score and improve your data health. If there are less robust checks on completeness and accuracy of data, it gets difficult to identify any bad data that exists.

Beyond health checks, we build alerting and workflows based off data health and deploy the data to support the range of activities any wealth manager carries out. Data analytics provide an opportunity to automate manual tasks, optimize processes, increase efficiency and save a large amount of memory by removing duplicate information. Data analytics help users act effectively at the enterprise, group or office, and/or individual investor or sub-account level. Some ways our platforms facilitate wealth management operations include:

• KPI and KRI management in real time to keep your firm on track
• Workflow and alerting to optimize resources to focus on critical exceptions and priorities
• Real-time compliance and internal audit checks and balances
• Risk management ex-ante and ex-post through data analysis
• Real-time matching to ensure consistency and alignment between your portfolios and the market
• Real-time investment strategy management and drift management by regularly assessing the suitability of approaches to keep each client optimally positioned

Our data is also used for varied client-facing activities. Managers can use data to create comprehensive prospect profiles, map relationships, identify new markets, and generate better leads. Data can be tracked to create client profiles, ascertain a client’s potential lifetime value, and measure risk tolerance for various types of funds and advice by correlating transaction and channel data with market events. Data analytics can help in anticipating the needs and behaviors of the customers, and then segment customers to tailor interactions and offers, thereby increasing revenues for firms.

Personalizing client’s investments by leveraging analytics in data management leads to product development and customization that can be managed at scale. At SS&C, we offer data-driven ways to handle large volume accounts and allocate portfolio changes en mass via tools such as SS&C Global Wealth Platform’s rules-based engines TIA (Tailored Investment Automation) and TAA (Tailored Asset Allocation) to automate the management of SMA and UMA portfolios.

At SS&C, we understand how important it is to have as much clean, reliable, and relevant data as possible to assist wealth managers in their work.

The more data inputs you can ingest and manage, then the better armed you are. To that end, we’re instituting the concept of permissive storage in our data management. Permissive storage delivers the ability to take, load, process and analyze partially complete information. In the past, you couldn’t load an incomplete record– but we came up with a way to take partial information, like unstructured, raw data, ingest it into the system and offer it as part of the full data picture, until you get the full record together. With SS&C Aloha’s machine learning (ML) and natural language processing (NLP) capabilities, we can process and learn from vast amounts of data to complement the human process, allowing asset managers to spend more of their time on high-value decisions for their client, and gaining new ways to uncover insights and improve productivity.

Big data and advanced analytics are transforming the wealth management industry, with new ways to optimize operations, develop and implement investment strategies, engage and retain clients, and manage risks. The industry is moving from insight to foresight – starting with gaining a better understanding of what's happening to forecasting what could happen with greater precision. Real-time and predictive analytics can elevate firms to a higher standard of excellence. We are incredibly excited to help our customers build a better path to success through smarter, data-driven decision-making.

This article is part of The Wealth Mosaic's recent WealthTech Views Data Management Report. Access that full report here.