An asset management activity within a banking group needed to structure its planning capabilities to manage its performance in a volatile market environment.
Existing budgeting processes were fragmented across teams (management, sales, middle office), with heterogeneous methodologies for projecting management revenues (management fees, performance fees). Manual consolidation did not allow for rapid iterations or reliable simulations.
Before implementing any tools, a clarification of the target projection model and harmonization of methodologies were necessary.
The central challenge was performance management in a volatile market environment: how to project management fees and performance fees, which depend on assets under management and market performance, in a context where assumptions can be invalidated within weeks?
Heterogeneous methodologies among teams and the lack of rapid simulation capabilities made projections unreliable and budget cycles too long to adapt to market changes.
The objective was to build a system that would:
• model management fees according to the specific characteristics of each asset class,
• quickly simulate the impact of different market scenarios on projections,
• shorten cycles to maintain relevant projections despite volatility.
The management and finance teams had differing views on how to project revenues. We organized joint workshops to build a projection model that was acceptable to everyone, incorporating the specific characteristics of each asset class (equities, bonds, alternatives).
The work focused on:
• modeling management revenues (management fees based on assets under management, conditional performance fees) with explicit assumptions about market developments and inflows,
• building market scenarios to test the sensitivity of projections to changes in benchmark indices,
• implementing a rapid reforecasting process to update projections within a few days during significant market movements.
The business now has the responsiveness to maintain relevant projections despite market volatility.
Outcomes
• Significant reduction in budget and forecast cycles.
• Improved projection quality through harmonized methodologies.
• Enhanced performance management with regular variance monitoring.
• Ability to simulate market scenarios to inform decision-making.
• Improved responsiveness to market changes.
• Strengthened financial governance and increased visibility into the financial trajectory.
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