Financial services (FS) firms are operating in one of the most dynamic and regulated environments in the global economy. From volatile interest rates and foreign exchange swings to heightened regulatory scrutiny and the rapid pace of digital transformation, finance leaders in FS face unique challenges when it comes to budgeting and forecasting.
Traditional annual budgets, locked away in spreadsheets, are no longer sufficient. Smart financial institutions are adopting new practices that prioritise agility, accuracy, and collaboration – enabling them to respond quickly to market shifts and regulatory changes. This blog explores the best practices for budgeting in financial services today, and why firms that modernise their processes gain a competitive edge.
1. The Unique Challenges of FS Budgeting
Financial services firms face budgeting pressures that differ from most industries:
- Interest rate volatility: Shifts in central bank policy directly impact loan portfolios, deposits, and margins.
- Regulatory compliance: Basel III/IV, IFRS 9, and stress testing requirements mean finance teams must plan under multiple scenarios.
- Risk exposure: Credit risk, market risk, and liquidity risk all interact with financial forecasts.
- Complex revenue models: Banks, insurers, and asset managers each balance fee income, trading income, and interest-based income streams.
- High stakeholder expectations: Boards and regulators demand accuracy, transparency, and agility.
This makes budgeting a complex exercise – especially when relying on manual spreadsheets.
2. Moving Away from Spreadsheets
Spreadsheets remain common in FS budgeting, but they come with significant drawbacks:
- Consolidating hundreds of files across departments takes weeks.
- Formula errors can lead to regulatory compliance issues.
- Static models cannot keep pace with real-time market changes.
Smart FS firms are migrating to cloud-based planning platforms like Workday Adaptive Planning and IBM Planning Analytics. Benefits include:
- Centralised data: A single source of truth across risk, finance, and operations.
- Auditability: Built-in governance to satisfy compliance requirements.
- Scenario agility: Ability to model dozens of regulatory or market-driven scenarios quickly.
3. Rolling Forecasts Tied to Market Data
Instead of static annual budgets, leading FS firms use rolling forecasts, refreshed quarterly or monthly. These forecasts link directly to market drivers such as:
- Central bank rates
- Currency exchange movements
- Loan growth or default assumptions
- Assets under management (AUM) flows
This allows CFOs to quickly answer questions like:
- What if interest rates rise by 50 basis points?
- How would a 10% decline in AUM affect profitability?
By tying forecasts to market data, finance leaders can deliver forward-looking insights that guide strategic decisions.
4. Driver-Based Planning for FS
Driver-based planning is essential in financial services. Instead of relying on broad assumptions, smart firms model the key levers of their business:
- Banks: Net interest margin, loan growth, cost-to-income ratio
- Insurance: Premium growth, claims ratios, reinsurance costs
- Asset management: AUM, fee structures, redemption rates
With these drivers in place, FS firms can run what-if analyses and stress tests with precision. For example, an asset manager can quickly assess how a 5% decline in AUM impacts both management fees and operational headcount requirements.
5. Stress Testing and Scenario Planning
Stress testing is not optional in FS – regulators require it. But beyond compliance, stress testing also provides strategic value.
Modern platforms allow firms to run dozens of stress scenarios simultaneously:
- Recession impact on loan defaults
- Liquidity squeezes and their effect on funding requirements
- Market volatility impact on trading desks
The ability to produce rapid, data-backed stress tests helps satisfy regulators while also improving internal resilience.
6. Cross-Department Collaboration
Budgeting in FS is inherently cross-functional. It involves:
- Finance: Ensuring profitability and capital adequacy
- Risk teams: Monitoring credit, liquidity, and operational risks
- Compliance: Aligning with regulatory reporting requirements
- Business units: Revenue forecasting from retail, corporate, or investment divisions
Cloud planning tools enable these groups to work together on a shared platform, reducing silos and improving accuracy.
7. Leveraging AI and Predictive Analytics
Artificial intelligence is increasingly reshaping FS budgeting. AI tools can:
- Analyse historical transaction and market data to predict future pattern
- Identify anomalies, such as sudden increases in credit defaults
- Suggest forecast adjustments based on external indicators (e.g., interest rate expectations)
Workday Adaptive Planning, for example, includes AI-powered predictive forecasting that enhances forecast accuracy and reduces reliance on guesswork. This enables FS CFOs to make more informed, forward-looking decisions.
8. Case Example: Asset Management Firm
Consider a mid-sized asset management firm. Previously, its finance team relied on spreadsheets to project revenues based on AUM and fee structures. Forecasting a 10% market downturn required weeks of manual recalculations.
After implementing a cloud-based planning solution:
- Forecasting cycles were cut by 60%
- Scenarios could be run instantly (e.g., inflows, outflows, fee pressure)
- Predictive analytics helped flag risk in specific funds
The finance team gained credibility with the board by producing faster, more accurate, and actionable forecasts.
9. Steps to Get Started
For FS firms considering a budgeting transformation, here’s a roadmap:
- Identify key drivers: Focus on net interest margin, AUM, claims ratios, or other sector-specific levers.
- Assess current pain points: Where do errors, delays, or compliance gaps occur most often?
- Engage stakeholders: Bring finance, risk, and compliance teams together early.
- Select the right platform: Choose a solution with strong security, governance, and integration capabilities.
- Pilot with a single driver: Test rolling forecasts or stress tests before scaling firm-wide.
Conclusion
Budgeting in financial services is no longer a once-a-year exercise. It’s a continuous, dynamic process that must reflect market volatility, regulatory demands, and risk considerations.
By adopting rolling forecasts, driver-based planning, stress testing, and AI-powered analytics, FS firms can improve accuracy, satisfy regulators, and guide their organisations more effectively.
The firms that succeed will be those that embrace budgeting as a strategic capability, not just a compliance requirement.
If your FS organisation is still relying on static spreadsheets, you’re exposed to both compliance risks and strategic blind spots. At ICit, we help banks, insurers, and asset managers modernise their budgeting and forecasting with Workday Adaptive Planning and IBM Planning Analytics. To learn more about our FP&A Solutions in Financial Services
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If you would like to discuss how we can help you cut your budgeting cycle time in half, improve accuracy, and stay ahead of market and regulatory changes, please contact us today.
