A resilient finance operating model for banks

A challenging environment

The increasingly volatile interest rate environment is impacting banks. Both the treasury function and planning, budgeting and forecasting (PBF) are being hit particularly hard in this environment. Achieving a sound responsiveness towards sudden market changes in the daily business is a major challenge for many finance teams. Does this sound familiar?

Deloitte’s Swiss Finance & Performance Practice regularly helps clients to define their target operating model (TOM). In this article, we would like to shed some light on how the planning teams of banks can generate more accurate foresight in a difficult planning environment to improve decision-making, and how treasury can provide a better basis for interest rate hedging transactions.

We find that banks struggle to reflect their ambitions in their operating model (OM). In this regard, we see the following shortcomings most frequently: The OM does not enable the agility to respond quickly to change in the marketplace, there is a mismatch of available skills with value-adding activities, and organisations do not make use of IT as efficiently and effectively as possible.
Many of these deficiencies are due to the ongoing use of legacy systems that compromise both data quality and process automation.

The two processes we are highlighting here – treasury and PBF – are particularly affected by these circumstances and therefore lend themselves to a discussion of possible improvements in the TOM. These challenges can be overcome with modern finance IT – but we first need to understand the challenges faced by the finance teams of banks.

Key challenges

The volatile macroeconomic conditions exacerbated by the current political uncertainties pose a major challenge to risk management and planning activities.

On the one hand, the reaction time to adapt to different scenarios with a material impact on the business is currently very short, which makes it more difficult to define and monitor actions for achieving objectives. Furthermore, it is increasingly difficult for banks to plan product margins across all segments, especially in the interest-related business of retail banking.

A key planning challenge that needs to be addressed is how to quickly obtain up-to-date and meaningful business data, including detailed sales figures, financial reports and departmental budgets.

Improvement potential

Potential for optimisation can be found in all categories of the operating model. Given the challenges in banks’ finance functions described above, we have identified the greatest potential for improvement in treasury and PBF and the associated digital landscape.

The digital maturity of the treasury function and the use of advanced digital technologies and use cases can be effectively improved as part of a comprehensive digital strategy.

We have identified the following enablers for proper treasury optimisation:

• Data architecture should be integrated with relevant treasury and financial inputs and outputs, including consistent data sourcing and traceability

• The technology platform should include a single, centralised system for collateral data capture, including the attributes required to link the data to the underlying transactions

• Report generation should be consolidated into a single team within the treasury or finance department

To quickly identify potential challenges and mitigate uncertainty, it is necessary to create a unified corporate approach which ensures that the finance team is closely aligned with the business. Another lever to improve planning reliability and enable agile actions is to leverage real-time data from across the business and continuously identify emerging patterns. Operational forecasting is supported by technology, and we are seeing a steady trend towards AI-driven systems.

• From a process perspective, one possible solution to the problem of volatility is to introduce an agile planning approach, such as rolling forecasts or continuous budgeting.
• From a technology perspective, data analytics and automation can help streamline the budgeting process and increase its efficiency. Applying analytics with financial and operational data can also provide CFOs with insights to influence operational planning decisions that define budget items.
  

Our proposed approach

We propose the following approach to optimising the finance function, with a particular focus on the change-leading role of the CFO and the importance of combining digital technologies and operational capabilities.

Conclusion

In this article, we have described some of the challenges that banks face in today’s increasingly volatile environment and how the finance function can react by setting up a future-proof TOM, thereby adding value to the entire organisation. In fact, a finance function built for the future must be dynamic, risk-sensing and able to react to any disruption that comes its way.

Although the finance department faces these challenges, it is also in the privileged position of acting as a data architect, taking ownership of the bank’s data to design new planning models that enable the bank to better manage uncertainty.

Are you ready to take the next step towards your future finance capability?

>> Read the full report (pdf)