A Pragmatist’s Approach to Data Strategy in Wealth Management

There are plenty of opinions eulogising the perfect data strategy and mandating its ownership to avoid imminent collapse. Yet many wealth managers in the UK today operate without this level of structure. In a recent roundtable,  half the participants – representing some major firms – admitted to not having that single golden document articulating a firm’s approach, ownership, prioritisation, protocol, health, etc of a firm’s data set up. Is it a good idea to have one? Probably, yes. Is it mandatory? Certainly not always. However, are there some key constituents to unambiguously lay out? Yes.

The state of data management across the Wealth and Private Client industries is a mixed bag. The full suite of data strategies are the domain of the largest firms, or those who otherwise have – often accidentally – found it a necessity when trying to undertake significant change in the business. The number of re-platforming exercises and M&A integrations have forced many firms to formalise their data approach.

There is also the regulatory drive from Consumer Duty and Operational Resilience that require ever more exhaustive internal reporting, awareness and timely escalation. In some cases, these have tipped the balance in favour of a formal structure. A systematic approach to data is worth the investment versus a manual collection and reporting exercise.

There are accretive reasons to manage one’s data in a more rigorous way. The implications are laid bare when considering AI use cases which Alpha and the industry are starting to investigate with some seriousness. Our articulation of AI has to account for the sophistication of data quality and tooling.  While there are plenty of single case, beneficial AI opportunities, the real value lies in “effortlessly” synthesising (post implementation) the data sourced from across the business. This speeds up processing, deepens client engagement, and appraises product success and profitability, amongst many other benefits.

While data is an asset, we still see firms viewing it as a cost centre. Yet, it requires relatively marginal additional resource and commitment to materially extend the value of a good data policy to a Private Client business.  The reality is that implementing a data strategy can be challenging; it can involve hard truths and uncovering of dormant concerns that have existed under a rock for some time without peril. Data competes with multiple other priorities – so where would the pragmatist begin?

We strongly recommended that Wealth businesses:

• Map out and prioritise your key data domains that are business critical or offer value to the business
• Assign owners and track completeness – the higher the priority, the more rigorous the approach should be
• Speak to your key vendors, many of whom have been investing in data management, reporting and insight tools over the last 5-10 years
  • they’ll likely have a view of how you can use their systems to maintain data more effectively and less arduously. If you utilise an outsourced service provider, so much the better: they already manage across much of your business-critical data.
• Don’t be shy in instigating tactical fixes when this deviates from the ideal data strategy, so long as this is consciously agreed and the pay-off documented
  • We’d recommend this particularly where the data is “seen” i.e. reports, error fixes, client-facing documentation, etc. A longer-term remediation plan attached to this will help to bring the data purists onboard

To extend your capability:

• Investigate new data management technology entrants and how they can allow you to seize new capabilities (e.g. AI), and ameliorate the future barriers to change, upfront
• Reflect your strategy and value proposition in how you manage and prioritise your data
• Consider a more formalised data management capability and resource model, across centralised, federated or hybrid models

Effecting change to your data landscape may sometimes feel peripheral, versus some of the competing priorities of the business. Yet there is so much untapped value in getting the basics right: ensuring you can see how a client engages with you; rationalising your market data costs; laying the foundations for transformational AI initiatives that have enormous potential to transform the Wealth industry.

Demand for data is only growing – internal and external stakeholders alike want more data, faster, and of sufficient quality to inform decision making. Ultimately, deciding how far down the road to go with one’s data strategy is context dependent. It is seated in the strategy of an individual firm, the value proposition and operational set-up. In Alpha’s experience, there is always an opportunity for a Wealth Manager’s data to work better for them; the key is to make a deliberate decision for a firm’s specific circumstance.