Growing pains: DFMs must maintain data oversight – especially at scale

In this piece, Tom Whittle, CEO of Tikker, explores the growing operational strain within model portfolio services (MPS) as assets under management scale and consolidation accelerate across the discretionary fund management (DFM) market.

The growth story of model portfolio services is well-documented, and earlier this month, Tatton CEO Paul Hogarth predicted £500bn of assets within MPS by 2030; but as consolidation continues apace, high-growth DFMs further expand, and new ranges enter the market, the data practices at the heart of MPS are arguably showing strain. 

Data challenged by scale is not a situation unique to MPS. Across adjacent areas of the financial world, examples of outdated data practices are highlighted: from Mark Polson of the lang cat calling out the continued reliance within financial advice on “letters with wet signatures” – i.e. inconveniently paper-based letters of authority – to Criterion’s heralding of API standards for DFM-platform interactions. DFMs should take note and rethink their own data practices. 

The data gaps inside MPS operations 

Within MPS, three data-gathering challenges stand out – each manageable at a small scale, but increasingly problematic as AUM and platform count grow. These challenges are felt alike by IFA networks, consolidators, and high-growth DFMs. 

1. Flow data. Understanding monetary inflows and outflows is essential for C-suites, operations, and finance teams, but downloading flow data once at the start of every month means not being in the detail of daily flows. Data is like seafood – only good when it’s fresh. Software applications and operational processes that aid the monitoring of data, not just monthly but daily, would help to put DFMs’ oversight picture into sharper focus. 

2. Asset availability during rebalances. When a DFM initiates a rebalance, they need to know, in real time, which instruments are available on which platforms. Today, discovering that a fund is gated, temporarily blocked, or simply unavailable on a given platform often happens mid-process – requiring manual intervention, exception handling, and delays.

At scale, these exceptions multiply. Without a structured way to surface and manage them, rebalancing execution windows stretch and the risk of inconsistent outcomes across platforms increases. This erodes the intended strategy of the investment committee while the market moves on regardless. The value of the strategy is – similarly to out-of-date seafood! – no longer “prime.” This is directly linked to challenge #3. 

3. Factsheet production. With the FCA eyeing up the unifying of disclosure formats for MPS and funds-of-funds, new factsheet formats may well be on the horizon, which would create operational overheads as compliance teams strive to adhere to new rules and graphic designers produce new templates.

But the very accuracy of factsheets could also be brought under greater regulatory scrutiny. Whether a platform doesn’t host a fund at all; offers it only at a subpar share class; or hasn’t yet implemented a price discount agreed between a DFM and a fund manager, variation factors will cause the exact makeup of a model to be different from platform to platform.

Therefore, a factsheet’s “facts,” from asset class split to percentage allocation among top holdings, are really averages drawn from as many subtly varying portfolios as there are platforms hosting them. This is a Consumer Duty risk and only compounds as MPS holdings get bigger.  

Each of these pain points has a common root cause: data that exists somewhere in the ecosystem, but is not surfaced in a timely, structured, or centralised way. Consider an IFA with a married couple invested in the same model across two different platforms. Fees will differ, but that is expected and explainable. Performance divergence is not. Even marginal differences in returns are a conversation the IFA has to have and one that is far harder to answer. 

What consolidators and high-growth DFMs should strive for 

The ultimate goal would surely be: flow data, real-time fund availability, and information on cross-platform portfolio variance all unified in a single oversight dashboard. Not assembled manually each month, but continuously updated. Not platform by platform, but aggregated centrally and acted on concurrently.

Not reactive, but structured to surface exceptions before they become problems and to provide accurate, granular reporting. And when a rebalance is underway, the team would know in advance which funds are unavailable on which platforms – enabling exception management all in one go, not piecemeal and model by model.   

This is not a vision for a distant future. Intelligent automation can already connect legacy platform infrastructure with modern workflows, without requiring platforms to rebuild. The firms growing fastest – including the consolidators and high-growth DFMs reshaping the market – are precisely those that most need this kind of centralised oversight.

For them, the question is not whether to invest in better data infrastructure, but how soon to act before the operational strain jeopardises client and regulatory obligations. Some are already on that journey. Many are not. Current practices cannot scale, and the gaps grow faster than headcount can fill them. The people absorbing the pressure know it better than anyone – and they did not study for their finance degrees to end up doing data entry! 

The MPS market has grown up. Isn’t it time the delivery network caught up – and helped providers serve their recipes at their prime?