Data analysts often use the term ‘star schema’ to define a data model, whereby a single data point in the centre of the star acts to link everything together. 

Wealth firms will almost always have the client account in the centre, making it a fairly simple process to link AUM to centrally held client static and create a highly segmented asset book. Take the same approach with fees and commissions and firms will lay the foundations for powerful segmental or client level yield analysis.

Much of the challenge however comes from incomplete or poor client data. Few firms have a truly integrated data model across their front or middle office applications, and hence the reporting function must make a decision on the best source of data and then take a lead role in addressing data quality.

The traditional view on client account static is to take the data held by the core wealth platform. That is, after all, generally considered the firm’s books and records. But is it the right decision if the front office is managing clients using the data available from the CRM tool? 

The answer for many firms is perhaps to take the most reliable and frequently updated data source. That doesn’t necessarily need to be from a single source as long as the current or future reporting tool is sophisticated enough to merge data sources and provide a full audit trail of where the data has come from.

Even once the source is defined, data quality is likely to be an issue in the short to mid-term. Our advice is to apply the 80-20 rule. Find the 80% of the data that is readily available and of a decent quality and quickly structure it into a reporting framework. As a simple example, it is likely that a client account is accurately tagged to the correct Investment Manager, hence it should be a reasonably simple exercise to roll that Investment Manager code into a team, an office, a region and possibly an entity. 

Firms may find there are some outliers that can not be easily classified, but at least those outliers can now be identified, quantified and tracked until resolved. Tackling one segment at a time, including identifying ways to clean data at source, will allow firms to build up multiple ways to slice and dice the data. True analytics will start to take over from the old-fashioned approach of solely reporting the numbers.

Take a harder example of rate card. It is not unusual to see many hundreds of rate cards with a structure further complicated by bespoke discounting. The 80-20 rule equally applies here, it’s unlikely that firms will be able to quickly structure 80% of their rate cards, but they might be able to classify 80% of the asset book by value.

Tackling rate cards will perfectly demonstrate how hard it will be going forward to maintain control with new data elements being added all the time. This is where selecting the right reporting tool will become critical. Get it right and new or amended elements will be instantaneously identified, understood and challenged before being added to the structures. 

The benefits of structured data are immeasurable to a wealth firm. Firstly, it will bring about control and efficiency gains, but ultimately open up a world of true analytics and deeper understanding of the client and asset book. Informed decision making will naturally take over, driven by data insights rather than previous beliefs.

See original blog: https://www.linkedin.com/pulse/part-2-master-your-data-paul-brann/