Client and sales assets under management (AUM) and flows can throw up dozens of false positives and negatives as indicators of business performance. So, why are so many sales managers still relying on these metrics?
Effecting a shift to calculating and publishing client revenue metrics on a production basis is complex and difficult to achieve. Below, we have explored five reasons why managers find it such an arduous task.
1. Raw AUM and Flow data is often of poor quality
Building client revenue requires clean, high-fidelity AUM and Flow data. If a large asset manager is trying to create a firmwide view of AUM across all clients, products and jurisdictions, it needs to run a data service that can ingest between 80–100 diverse transaction data sources from TA, FA and distributor files and process it with metronomic reliability.
Doing so requires maintaining a library of over 120 data connectors and a rule set of over 100 data quality rules and calculations, including netting out double counts inherent in cross-holdings and cross flows between funds, as well as the DevOps capability to deliver secure and agile ‘run-and-change’ capabilities — all in the face of increasing the data volumes and volatility, plus new sources of data including ESG and private assets data.
2. The enterprise client, financial terms and product data is not up to scratch
For client revenue to be meaningful, the high-fidelity AUM and Flow data needs to be matched to the enterprise client, fee and product masters. This is the subject of several Aiviq articles in this series.
3. Client fee and billing data and distributor payments information is required
Client revenue is confidential and price-sensitive for a period of time up to and beyond quarter and year-end reporting cycles. The finance function usually controls this data with valid concerns about democratising data and allowing wider access. Calculating a tangle of flat, banded, tiered or performance-based fee schedules is complex and must be controlled carefully.
Unfortunately, the quality issues inherent in poorly processed AUM and Flow data and the state of most managers’ enterprise client and product masters mean that a worrying proportion of client revenue calculations (and, by extension, client fee invoices) are inaccurate.
4. Non-functional capabilities are immature
If a business has mastered the functional features required for a state-of-the-art enterprise client revenue data processing and calculation engine, does it have the design to scale as data volumes grow? Can it meet performance and data as a service SLAs? Does it meet enterprise information security standards and integrate to deliver data to consumers at the point of use with audit trails and proactive fine-grained access controls?
Many in-house solutions that were sufficient 10 years ago would now keel over when new requirements are retrofitted into a legacy design.
5. It is business change, not just a data project
Data flows and gates create power structures, and people who do not want to give up the latter are unlikely to surrender the former. Democratising data in this way requires high levels of cultural change. In addition, changing data patterns and formats in an organisation is incredibly risky and complex. Managers who bear the risk are often reluctant to move away from the safety of the status quo of AUM and Flow, which, despite its flaws, is well understood.
In light of these challenges, is the payoff worth it?
For the managers who have successfully crossed from blunt measures to smart numbers, the answer is still a resounding ‘yes’. Discover the three compelling reasons that managers should and must make the transition.
To speak to someone about how to discuss how your business can move from blunt measures to smart numbers like client revenue metrics, please get in touch with Aiviq today.