How much has the efficiency of support functions improved?

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December 2018 Following the latest set of quarterly earnings results from major banks, it s clear that there is a renewed focus on cost management. Prior to the results, analysts closely studied how banks are performing on costs, with some banks announcing or reiterating forward guidance on efficiency ratios. As we near the end of the economic cycle and macro risks continue to emerge, we anticipate that this renewed focus on cost will only intensify. Across our own client base, we are seeing heightened activity around assessing support costs. This article focuses on support functions, which, on average, cost an organization 30% of total group revenue. However, within these support functions, there are still substantial savings opportunities that can certainly move the dial on a bank s efficiency ratio. Our analysis estimates that improving efficiency by one quartile against the industry standard can yield an efficiency ratio improvement of up to 6.3% equivalent to a $1.6 billion savings for the average top 50 bank. How much has the efficiency of support functions improved? Post financial crisis, almost all banks have implemented some form of a large-scale efficiency program. Expense reduction levers that span support functions include optimizing procurement and sourcing, reducing non-core assets along with associated cost to serve, deployment strategy, organizational design, systems rationalization, and automation. Figure 1 illustrates the change in average absolute support costs from 2013 2017. Figure 1: Support Costs 2013 2017 ($billion) Other Control Functions Technology & Operations 12.8 13.3 12.9 13.0 1.5 1.6 12.1 1.6 1.7 1.5 2.9 3.0 3.1 3.2 3.0 8.4 8.7 8.2 8.2 7.7 2013 2014 2015 2016 2017 Control Functions includes Finance, Risk, Compliance, Legal, and Internal Audit Other includes Marketing & Communications, Human Resources, Corporate Services & Central Overheads

While it s notable that costs dropped off in 2017, our data in figure 2 shows that the average cost per front office head has steadily increased by 14% over the same period. Figure 2: Support Costs per Front Office Head 2013 2017 ($thousands) Other Control Functions Technology & Operations 229 243 213 210 211 26 31 31 27 28 49 48 51 57 61 138 134 132 141 150 2013 2014 2015 2016 2017 Although we would expect a trade-off between technology costs and front office headcount due to digitization initiatives, the overall increase in per head costs has been across all support functions. There are several reasons for this, such as increased regulatory and compliance demands. However, this also highlights the fact that future savings opportunities will likely target a firm s support functions. Heading into 2019, we expect to see a ramp up in efforts to improve cost efficiency ratios, with new programs commencing and existing ones continuing. The evolving landscape will impact how banks approach cost Compared to post-crisis restructuring programs, there are several key differences that impact the approach management must take when addressing cost in the current environment: 1. Business mix: Fundamentally, business models and business mix have evolved, which can structurally impact the cost base. For example, within global markets there has been 29% growth since 2013 in technology and operations-intensive prime services, while advisory fees have been relatively flat. Some banks have shifted capital away from banking and markets to wealth management and others have focused on growing their technology-intensive transaction banking business. This changes the profile of support spend for many banks, blurring comparability to prior years. 2. Treatment of restructuring costs: There is less forgiveness from investors and analysts on the treatment of restructuring costs as one-offs. Investors expect to see increasing returns on equity, operating leverage, and dividends. Restructuring costs have become the norm over an extended period, meaning they re no longer one-offs. 3. Digital investment: The scale of digital investment for banks is significant. On one hand, this is a powerful lever to reduce cost and enable revenue growth. On the other hand, the investment required to keep pace with disruption in the industry will weigh on cost efficiency ratios, at least in the short to medium term. 4. Spend mix: Regulatory-driven change, compliance challenges and fines, automation, and business mix changes have all re-baselined certain functional spend. Cost Analytics: How to Uncover the Opportunities that Drive a $1 Billion Cost Optimization Program 2

5. Execution complexity: Within the industry, the term low hanging fruit is often used in reference to cost savings achieved over the immediate post-crises era. Improving efficiency is exponentially more difficult today. Banks will need to adopt a different approach to tackling cost reduction, which will require smarter investment, as well as the need to evaluate the quality of the cost savings that they re targeting and delivering in terms of sustainability. 6. Shift to Agile: Firms are increasingly considering how they can transition into an agile organization. This is broader than just applying agile practices to project management. It means looking at revenue and costs from an entirely different lens. Firms will have to assess profitability on a transactional basis and consider the cross functional lifecycle costs attributable to a transaction. This leads to increased transparency and challenge on all expenses. However, the shift will not happen overnight. It takes time for bank reporting systems to evolve to a state that supports an agile way of analyzing financials. How can a data-driven approach support cost optimization? Preserving precious investment and maximizing returns on investment means making the right decisions on where to invest. Top-down targets are essential, but should always be informed by data-driven analysis. Accountability and ownership of targets are the most important factors in the success or failure of a cost optimization program. Yet, when this is not complemented with a bottom-up understanding of the cost base, program cost overruns, scope reduction, and benefits erosion are likely. A data-driven, analytical approach to cost management can pay dividends as savings become increasingly difficult to realize. In practice, this means understanding relative performance for several cost drivers and KPIs, including: Compensation expenses Non-compensation expenses at the account level Spend categorization in order of criticality External workforce analytics Grade pyramids and spans & layers Deployment analysis Sub-functional comparisons Efficiency ratios (e.g., operating expense per revenue) Coverage ratios (e.g., number of support heads per front office head) Embedded roles (e.g., number of support staff in the front office) Line of business split Peer comparability Understanding the gap to median, upper quartile, and best-in-class, both from an internal and external perspective, can help size opportunities. This method is particularly relevant for firms that are already best-in-class, given that the dissection of the cost base will always uncover room for improvement. In summary, adopting a data-driven approach can help management improve transparency over expenses. Cost Analytics: How to Uncover the Opportunities that Drive a $1 Billion Cost Optimization Program 3

Sizing the opportunity Our analysis illustrates the average cost savings banks could make from improving by the equivalent of one quartile in each support function, expressed both as a percent reduction in the cost base and as a percentage of revenue (see figure 3). On average, improving by one quartile in each function can yield an increase in the group efficiency ratio of up to 6.3% in total. The greatest areas of opportunity lie within technology, operations, and finance. Crucially, this would provide the capacity to fund digitization, increasing compliance demands, cyber security, etc. However, banks must undertake their own tailored cost analytics contextualized with business mix, strategy, current performance, and market relevance to truly pinpoint where exactly savings opportunities reside. Carrying out this in-depth, yet rapid assessment is guaranteed to protect future investment and maximize return on investment. Figure 3: Potential Cost Savings per Function by Moving One Quartile vs. the Industry Average Function Cost Base Reduction % Improvement in Group Efficiency Ratio Technology 19% 2.7% Operations 17% 1.0% Finance 23% 0.7% Risk & Compliance 17% 0.6% Communications & Marketing 20% 0.2% Other 23% 1.1% Total 6.3% Other includes Legal, Internal Audit, Corporate Services, and Central Overheads. Cost Analytics: How to Uncover the Opportunities that Drive a $1 Billion Cost Optimization Program 4

Critical success factors What are the critical success factors in optimizing cost, maximizing return on investment, and ensuring successful execution? Accountability: We ve covered the importance of accountability earlier in this article. Top down mandates and ongoing cost forums are important in providing clear direction and ensuring accountability within business units. Using data to drive insights: Cost optimization opportunities should always be underpinned and validated by hard data up front. Not basing insights on facts, i.e. the actual cost per general ledger and industry comparisons with market intelligence, will lead to an erosion in savings over time, as the facts become clearer. Ultimately, this can cause an inefficient allocation of investment. Prioritization: Investment will always be a scarce resource and demand for investment, as well as ideas for programs of work, will typically outstrip supply. Prioritization of initiatives is imperative and should be supported by data. Categorization: Categorization of expenses into buckets in order of criticality avoids exhausting time focusing on cutting back critical spend, such as growth enabling investment. Collaboration: Adopting a cross functional, front to back approach will set cost optimization efforts up for success. The power of this method is often underestimated. Many projects require cross functional input and breaking down silos and barriers enables the right decisions to be made. Execution discipline: Large-scale programs can last 2+ years and will likely change considerably over their lifecycle. Therefore, management must monitor performance and proactively reallocate investment. Benefits and associated investment should be monitored, tracked, and challenged. Sustainability: The quality of cost savings is often overlooked. Firms need to ask themselves whether the savings attributed in return for investment are temporary or truly sustainable. Other considerations Allocations: In most banks, the allocation methodology is by no means perfect. Banks continue to grapple with how to best align costs to businesses and products, while business areas challenge allocations, typically failing to understand the basis and justification for allocated expenses. Analyzing and dissecting the cost base, starting with the back office where cost originates, will help isolate any noise and get to the root cause of where inefficiencies exist. Timing: Expense and headcount analytics are often perceived as time consuming exercises. Partnering with third party experts makes comprehensive analyses possible within a matter of weeks, and benchmarking enables management to pinpoint focus areas quickly and easily. How we can help We work with most major banks to help carry out benchmarking and analytics of revenues, front to back costs, headcount, and capital using GAUGE financial benchmarking. Our market leading analytics and customized benchmarking have consistently enabled our clients to see where they currently stand and identify where any cost saving opportunities exist. Cost Analytics: How to Uncover the Opportunities that Drive a $1 Billion Cost Optimization Program 5

Specifically, the areas where we can help include: Cost driver analytics: Using KPIs, such as cost per revenue and cost per capita, to identify areas of inefficiency for further investigation. Providing data points and analyses to uncover the root causes of cost inefficiencies, including grade pyramids, location analysis, internal vs. external spend mix, and non-compensation deep dives. Operating model assessment: Comparison of peer operating models, including onshore vs. near shore vs. offshore mix, internal and external headcount, centralized vs. embedded headcount model, spans & layers, and grade pyramids. KPIs, such as functional heads per front office head. Evaluating the effectiveness of control functions. Talent and reward analytics: Breakout of compensation data, leveraging our proprietary dataset, including fixed and variable pay analysis, payout ratios, and talent strategy advisory. Proprietary insights on geographical and functional compensation strategies and future trends. Opportunity analysis: Targeting areas of improvement by dissecting the cost base by location, sub-function, and cost type. Drilling down into specific account lines to identify quartile deviations, even for functions or cost types that are above average at the top level. Quantifying opportunities based on scaled metrics. To learn more about cost optimization for your firm, please contact our team. Cost Analytics: How to Uncover the Opportunities that Drive a $1 Billion Cost Optimization Program 6

Author Contact Information Chris Blain Partner, Head of GAUGE, McLagan Aon +44 (0)20 7086 5022 cblain@mclagan.com Nicholas Yazdani Director, McLagan Aon +44 (0)20 7086 0997 nicholas.yazdani@mclagan.com About McLagan McLagan provides tailored talent, rewards, and performance expertise to financial services firms across the globe. Since 1966, we have partnered with the largest and smallest financial services firms to help them make datadriven decisions to hire, retain, and engage the top talent for keeping the global economy running. Our compensation surveys are the most comprehensive, in-depth source of rewards data covering over 150 countries from more than 2,500 clients. Our consultants work with hundreds of firms annually to design total rewards programs and benchmark financial performance for boards of directors, executives, employees, and sales professionals. McLagan is a part of Aon plc (NYSE: AON). For more information, please visit mclagan.aon.com. About Aon Aon plc (NYSE:AON) is a leading global professional services firm providing a broad range of risk, retirement and health solutions. Our 50,000 colleagues in 120 countries empower results for clients by using proprietary data and analytics to deliver insights that reduce volatility and improve performance. For further information on our capabilities and to learn how we empower results for clients, please visit http://aon.mediaroom.com. This article provides general information for reference purposes only. Readers should not use this article as a replacement for legal, tax, accounting, or consulting advice that is specific to the facts and circumstances of their business. We encourage readers to consult with appropriate advisors before acting on any of the information contained in this article. The contents of this article may not be reused, reprinted or redistributed without the expressed written consent of McLagan. To use information in this article, please write to our team. 2018 Aon plc. All rights reserved Cost Analytics: How to Uncover the Opportunities that Drive a $1 Billion Cost Optimization Program 7