Wealth Management's Client Data Dance

Mark Trousdale 8 December 2020

Wealth Management's Client Data Dance

How does a wealth manager approach data management that doesn't silo client information but delivers real insight? This technology view examines that journey.

In a year where weath managers have moved mountains to digitise their services and technology has largely availed, Mark Trousdale (pictured), chief growth officer at wealth management platform InvestCloud, examines the main hurdles for managers in getting all those assets orchestrated. Understanding the data science and organising principles behind client data is the redemptive path to seeing their "entire wealth view" he proffers. The platform supports around $2 trillion of assets so is well-versed in where managers are leading and lagging in these efforts. The editors welcome guest contributions and invite readers to jump in. Email and

The days of regular face-to-face meetings are disappearing; all of a client’s information must be available at the touch of a button. At the same time, wealth managers must optimise their time to an even greater degree to be more efficient as well as more accessible and approachable to today’s tech-savvy client.

Data is the key to unlocking this more digital-centric and multi-channel era of wealth management. It allows for new account openings and full onboarding with minimal human effort. It also means that wealth managers can understand their clients on an even deeper level – helping them anticipate financial needs and wants more efficiently.

The ability to harness these opportunities is dependent on how data is collected, stored and used at every stage of the client journey. A task which comes with challenges.

Data collection and storage
One of the biggest pitfalls facing many wealth managers – indeed, facing businesses of all shapes and sizes – is how data is collected and stored.

Too many firms are still dependent on data lakes to store their information. These are essentially unstructured, massive repositories for collecting lots of data – collecting it, however, without the rigour of a data model. This means that at a fundamental level, the pieces of information painstakingly curated over time cannot work collectively across a business – and firms lose those opportunities for valuable insights, making it nearly impossible to build upon and scale.

For example, deploying a client portal requires an application to measure internal performance analytics. These require roughly the same information: holdings, transactions, accounts, security master details and so on. A data lake doesn’t give you the information to power all this in an easy way.

As an alternative to data lakes, some firms wishing to achieve operational efficiencies have looked to implement data marts as a solution. These place information in separate containers – meaning better reporting capabilities. But as everything is siloed, navigation, interpretation and flexibility remain difficult.

More forward-thinking wealth managers have adopted data warehousing. This improves navigation and business intelligence by putting data sets into smaller atomic sets. But data warehouses tend to be organised by developers rather than users, resulting in data filed in ways that were not intuitive – or necessarily useful – to the end user.

A digital warehouse – a cloud-based data warehouse that combines external sources and non-traditional data points such as media, documents and even held-away assets – creates a single version of the integrated truth (what InvestCloud calls SVOTIT™). A Digital Warehouse therefore provides the best outcomes for data storage and handling, as all information is centrally located and can communicate with different applications and functions. It offers the complete picture.
Integrating data science
An important element of being a successful wealth manager is the ability to see the bigger picture. This means having in-depth knowledge of your clients’ financial goals.

Over the years, this has been done by face-to-face conversations, where advisors bond with their clients and spend valuable time learning how they tick. The increasing digitisation of the wealth industry means that data management and processing must now play a key part here.

As the industry ramps up its digital capabilities, there are more and more apps and functions being used. Too often, these are siloed as different hard-coded and white-label applications from different vendors which are unable to “talk” to each other. This means that a wealth manager or client will struggle to see a truly holistic view of their entire wealth, and that information provided in one place may not carry across to other functions.

Advisors need to join the dots between the various services to ensure that they can track and push clients through the entire digital journey. Data science is the key here – the ability to interpret how users have been engaged through the digital journey to lead them to a desired outcome.

Every click and interaction should be recorded automatically. This creates a wealth of information to an advisor – allowing them to better serve and predict client behaviour. Wealth clients are already used to seeing this every day of their lives – through social media platforms or in ecommerce. Wealth managers need to follow suit and implement such initiatives, otherwise even with the best designed experiences, they will fall short on client expectations.

Bringing data full circle
Another major consideration for wealth managers is how they use the data at their disposal. We have discussed the pitfalls and opportunities around collecting information using data science and why storage is such an important consideration. But the true worth of data is in how it is used.

The end goal of using good data is to optimise digital workflows and journeys, finding where and how users are engaged. Looking at people, products and processes, wealth managers can clearly see holes in their portfolios as well as quickly identify the needs of their clients. This information is the key to successful wealth management. The final piece to the puzzle is communicating this to your client in a clear, concise manner.

A common pitfall is not relaying advice or providing experiences that are best suited for the individual client. In a digital world, one size fits all will not cut it with clients, as they are used to hyper-personalisation. Wealth managers can use the data they have gathered from the client via data science techniques and combine this with the data they own in their Digital Warehouse to provide these unique experiences – without having to create a tailored platform per client.

This is done by understanding personas. For example, financially literate and experienced high net worth individuals may be more interested in seeing the hard numbers and portfolio data, while younger mass affluent clients may need to see more content in order to push them towards a certain decision or understanding advice. The data clients provide will inform the experience they get – and the data from the wealth manager can automatically generate this.

The fuel for modern wealth management
The increasing digitisation of wealth management has meant that many firms have adopted online capabilities, but often in a disjointed way. Data has the power to connect these – so long as it is collected, stored and used in the right way.

Achieving this is not an easy task – and there are many pitfalls that wealth managers can fall into on their journey. But by ensuring that data is centralised and at the heart of everything the business does, the industry can achieve greater operational efficiencies, stronger client relationships – and crucially, better profitability.

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