Profitability Management in banking – how it relates to Asset and Liability Management (ALM), and how to solve the most common problems

This article provides all the basic information you need on the common challenges of Profitability Management in banks.

We’ll be going through the following subjects:

What is profitability management and why does it matter?

The main goal of Profitability Management

Four typical challenges banks face in Profitability Management

The key ingredients of ALM for Profitability Management

Best practice is built based on the key ingredients

How MORS helps banks solve their profitability challenges

MORS Integrated ALM for bank Profitability Management

What is profitability management and why does it matter?

Profitability management is an integrated part of ALM and is inherently linked to capital planning in banks. Current and expected profits and losses cascade through the Income Statement and impact banks current and forecasted capital adequacy ratios. Profitability of a bank matters for the bank’s external stakeholders, such as debt and equity investors and analysts, rating agencies, supervisors, and clients. All banks subscribe to and promote stable non-volatile earnings over time.

Why does a bank need to be profitable?

Being profitable is essential for banks because it leads to financial stability, strength and an ability to grow. Core equity or ‘own funds’ grow primarily through retained earnings allowing a bank to increase lending. Today’s losses diminish ‘own funds’ and constrain lending capacity in the future. It is equally important to understand that losses as part of bank’s ICAAP (Internal Capital Adequacy Assessment Process), over a 3-year time horizon under stressed assumptions, also acts as a constraint to growth.

What happens if a bank is not profitable? That is, it makes a loss and even worse, the outlook or forecast predicts further losses. Depending on the magnitude of losses (current and expected), equity and debt investors, including the public, might lose their confidence in the bank. They might for example start removing their deposits, which causes a liquidity crisis. Supervisory and resolution authorities are required to step in when banks breach or are likely to breach prudential thresholds of capital or liquidity, which could trigger the imposition of a recovery or resolution plan. Such a scenario may potentially lead to substantial losses for external stakeholders.

Profitability management in banks - what is a bank is not profitable?

Profitability is a supervisory concern

Bank profitability, particularly in Europe, has become a dominant supervisory concern, as the cost of capital exceeds the Return on Equity for most banks. Supervisors are concerned that low profitability, which in turn leads to low valuations, may lead to a situation in which raising capital is costly or even prohibitively expensive. Simply put, low earnings equal increased risk.

What are the key drivers of bank profitability?

To answer this, we should first ask whether all banks are equal – a bank is a bank is a bank, right? In a way, yes, but banking models and the markets in which banks operate can differ enormously. There are many types of banks: universal banks, investment banks, retail banks, private banks and so on. They all have slightly different drivers and a different emphasis on such drivers. In this article we will largely focus on the first three drivers listed below:

  1. The general level of interest rates, the term structure and the evolution of customer margins drive NII (Net Interest Income). This is the main source of income and profitability for universal, mortgage, retail, and regional lending banks.
  2. Net commission, as a relative part of the income statement, is becoming increasingly important for most banks. Net commissions can relate to retail and corporate banking fees, but also to asset and wealth management generated fees, or insurance fees.
  3. Current and expected losses related to lending and credit risk banks undertake in their role as facilitators of maturity and risk transformation in society is also very important.
  4. In the face of declining profitability, banks have become very cost-conscious. This is typically measured as C/I (Cost Income Ratio) and it varies largely between different bank categories.
  5. Fair value changes.

The role of Profitability Management in banks

Finance and the CFO office are responsible for profitability management in banks. They need to understand the profitability drivers listed above and how they might interact over time. Based on their understanding they are able to optimise the Balance Sheet and the strategic plan of the bank accordingly. Traditionally, ALM (Asset and Liability Management) and the wider Asset-Liability Committee (ALCO) may have focused largely on the Balance Sheet and the evolution of Net Interest Income (NII) and how this is balanced against all financial constraints. Given the decline in profitability, largely due to lower lending rates and floored liabilities, it is also very important to understand how changes in the interest rate environment may consequently affect net commissions and the Income Statement.

The main goal of Profitability Management

Profitability management is aimed at providing a predictable and steady income for the bank. This includes balancing ALM risks to stabilise and maximise Net Interest Income (NII) for the bank over time and against all constraints. This should manifest itself through stable and preferably rising Return on Equity (RoE) and the bank’s valuation versus peers. This in turn leads to stable dividends for equity investors and reduced funding costs alike. Additionally, and importantly, profitability reduces risk.

main goal

Banks are typically measured against their peers and competitors by external stakeholders, be that debt and equity analysts or ratings agencies, etc. A bank may not have to perform the best consistently, but being the weakest consistently is highly undesirable. As part of the Supervisory Review and Evaluation Process (SREP), banks in Europe are also organised, according to set criteria, into peer groups. Stable and profitable banks may benefit substantially, through lower Pillar 2 guidance and thus a lower set of regulatory thresholds and constraints. This increases the imperative for banks to stay profitable over time.

Four typical challenges banks face in Profitability Management

Managing profitability as part of the financial planning process is not easy. The risks faced by the banks are multi-dimensional and interconnected. Also, the Balance Sheet of a bank is typically multifaceted and full of complex detail linked to risk. To complicate matters further, items outside of the Balance Sheet, which may correlate with Balance Sheet exposure, such as Net Commissions may have a significant impact for many banks.

The following are typical challenges that banks face from a Profitability Management point of view. These challenges can have significant impact on the performance of a bank in the short, medium, and long term.

Challenge #1 – Changes in market rates, client margins and customer behaviour

Interest rates and general interest rate risk levels may change for many different reasons. When interest rates change, current Balance Sheet values and future cash flows also change. Client margins also vary and recently margins have been under pressure in most developed banking markets. This pressure reduces NII and thus impacts profitability negatively. Lastly, changes in customer behaviour, such as the propensity to pre-pay mortgages early, impacts NII and profitability negatively as old high-margin lending is replaced, at best, with new lower margin lending.

Challenge #2 – Changes in current and expected credit losses

Presently, as many banks and markets have adopted the new IFRS 9 framework, a new complicating factor has emerged. Banks need to assess and account for both current and expected credit losses (ECL). Therefore, banks have to assess the impact on ECL as part of their Financial Planning process as changes in macro-variables within the ECL framework can have a significant impact on the bank’s performance. This adds a further layer of complexity and uncertainty to the process of Profitability Management.

Challenge #3 – Balancing and understanding impacts between the Balance Sheet and the Income Statement

ALM and managing Interest Rate Risk in the Banking Book (IRRBB), has traditionally been almost exclusively focused on the Balance Sheet and stabilising NII and earnings over time. As NII has been under severe pressure for almost a decade in many markets, banks have tried to compensate by increasing fee-based income related to Asset & Wealth Management (AWM), Retail Banking, Corporate Banking, etc. It is complicated to balance and understand the impact of changes in market rates on these types of fees and the business segments generating these fees, such as AWM, e.g., will Assets Under Management (AUM) decrease for AWM if interest rates rise?

Challenge #4 – Managing profitability within internal and regulatory constraints

This is where things can get very complicated indeed. Picture the following: a bank’s local Financial Services Authority (FSA) has capped the possibility to model and utilise the inherent duration of its core Non-Maturing Deposits (NMDs) as part of its IRRBB framework. So, under regional Pillar 2 requirements, the bank would be forced to capitalise the impact on its Economic Value of Equity (EVE). However, according to the bank’s internal assessment and evaluation NMD duration is much longer and therefore causes a mismatch. Thus, hedging the ‘real’ exposure, will impact the bank’s Pillar 2 requirements. This may be worthwhile, as at least earnings and ‘real’ risk will be stabilised.

The key ingredients of ALM for Profitability Management

The three key ingredients of ALM, emanating from the challenges listed above, that ensure successful Profitability Management are as follows:

  1. Product and Client Level Decisions. Measuring and managing profitability on a product and client level is important. Decisions on what products with what features should the bank offer and to whom, will optimise profitability over time. A simple example could be to offer certain clients Fixed Rate Mortgages, as this will stabilise earnings and reduce pre-payment risk to some extent in some markets. However, it is equally important to understand how this can benefit the client. For high Loan to Value (LTV) borrowers, protection (through fixed rates) versus higher rates in a rising rate scenario protects the client and insulates the bank from potential credit losses.
  1. Include All/ ‘Widening the Scope’. Banks are increasingly gearing themselves towards fee-based income streams as net commissions increase in relative terms. Therefore, it is vital to understand and assess the correlation and interaction between how changes in market interest rates and customer behaviour affect both NII and net commissions. This requires an integrated view of the Balance Sheet and Income Statement.
Banks are increasingly gearing themselves towards fee-based income streams as net commissions increase in relative terms
  1. Scenario Analysis. Capability to run scenario analysis is the key to assess and understand how changes, in a wider scope, will impact both the Balance Sheet and the Income Statement over time. In addition, the ability to clearly visualise the multi-dimensional effect a scenario may have is essential. Presenting visually the analysis results against all the bank’s financial resources, such as capital and funding, and how profitability is impacted in different scenarios, facilitates the ability of the bank’s senior management team to respond and act quickly.

Best practice is built based on the key ingredients

In some respects, the key ingredients listed above may be somewhat obvious. However, best practice dictates that it is putting them together into one holistic and complete process that supports Profitability Management and optimises profitability over time.

Best practice is built based on the key ingredients

Having access to individual contract level data and the ability to process large volumes of data is absolutely essential. All too often banks are forced to choose between plague and cholera, i.e., choosing between speed and performance of analytical processes or a low-level data granularity for their planning and profitability management process and the systems these processes rely on.

Combining the key ingredients into the best practice

Modern technology with in-memory analytics and virtual modelling allows banks today to combine the key ingredients into the best practice by:

  1. Firstly, building from the bottom up. Having access to very granular data, covering all risk surfaces in a harmonised way, allows banks to transparently measure and manage change versus all their constraints. Thereafter the bank can begin to understand how these elements interact with profitability over time. This allows Finance and the CFO office to thoroughly analyse what drives RoE at a product and client level.
  2. Secondly, widening the scope and understanding of the interaction and inherent correlation between Balance Sheet and fee-generating items in the Income Statement. For example, what is the overall interest rate sensitivity on net commissions in a wider context? For many banks this could be significant and obviously needs to be taken into consideration. Also, how would credit risk and future ECL provisions react in different scenarios? Can substantial macro-variable and rate changes lead to substantial changes? For this type of analysis and understanding of underlying drivers, reliable granular and harmonised data is vital as is the ability and capacity to process it.
  3. Thirdly, with the level of complexity and multi-dimensional interaction between drivers and constraints, strong scenario analysis capability is essential as is the ability to visualise (online and in realtime) different outcomes and how they impact profitability. The process and system must facilitate online analysis, discussion, and the decision-making process alike. Traditionally and way too often, the process becomes a game of ping-pong. At the beginning of the COVID-19 pandemic, banks altered their strategic plans and updated their stress tests. However, the slow and labour-intensive process, led in many cases to a situation in which the scenarios and stress tests eventually presented where already out of date.

While the aforementioned tasks might sound simple, the complexity is in the detail. Success is determined by how well all aspects listed above are integrated into a seamless and systematic process to facilitate optimal decision-making.

How MORS helps banks solve their profitability challenges

Many banks struggle to manage the much-needed lowest level of data granularity. Creating a holistic view that includes granular Balance Sheet data and the ability to assess the impact of changes therein on the Income Statement as well as understanding what drives RoE, might easily seem like an overwhelming task. Managing all the data and the processes that use it requires a systematic approach. A comprehensive and dedicated software solution is essential.

The MORS integrated ALM solution is built on a unique data management architecture that allows banks to build their analysis (stresses and scenarios) based on contract and transaction level data. MORS creates a harmonised view. The use of granular data provides the ability to cover all risk surfaces in one integrated solution. MORS can perform quickly and at scale (high volumes) because it uses in-memory analytics and virtual modelling. This facilitates real-time online scenario analysis providing immediate and accurate support for the decision-making process.

Banks need to have an integrated ALM solution because Profitability Management is directly related to decisions made in ALM.

Banks need to have an integrated ALM solution because Profitability Management is directly related to decisions made in ALM.

MORS can readily and easily meet the following requirements for an integrated ALM and Performance Management approach:

  1. Gather complex and granular Balance Sheet data and Market Data easily, transparently and in an automated, systematised and repeatable manner.
  2. Create understandable scenarios for internal and external requirements.
  3. Calculate multiple scenarios quickly and in a cost-efficient manner.
  4. React to the results with rapid and informed decision making.

MORS is designed to help banks meet and overcome data aggregation challenges. The information required for Finance, Risk Management and the decision-making processes therein is constantly and automatically updated in MORS. The level of data detail in MORS is so high, it provides in-depth analysis to facilitate all decision making and an understanding of all aspects of the drivers of profitability in any bank.

Read more about Profitability Management and MORS integrated ALM.

MORS Integrated ALM for bank Profitability Management

Why do we and our customers believe that MORS Integrated ALM provides the right Profitability Management approach for the CFO office and Finance Operations in banks?

  • MORS has a very user-friendly and intuitive scenario generation and stress testing engine
  • MORS data is always up to date which accelerates the bank’s ability to react to changes in the market
  • The level of granularity and the overall quality of MORS data facilitates effective and accurate decision making
  • MORS ‘forward-looking’ analytics drive profitability through balance sheet optimisation
  • MORS is highly cost efficient with low maintenance costs.
  • New versions are always included in MORS software licenses.

Further questions on MORS and Profitability Management? Please ask our experts

Please contact our experts if you would like to discuss how MORS can help overcome your banks profitability management challenges. By engaging with us in a dialogue about your bank’s requirements, we will be able to help you fulfil your system needs.