The views and opinions expressed in this article are those of the thought leader as an individual, and are not attributed to CeFPro or any particular organization.
With the world facing a tough economic landscape, 2021 promises to be a testing time for businesses globally and the banks that serve and support them. As their corporate clients react to the emerging economic uncertainty, banks need to assess their lending practices to get a clear view of how the financial climate will impact the growth and performance of their business.
Even before the Covid-19 pandemic wrought havoc on the global economy, disrupting global trade and forcing businesses to rethink their plans, banks were facing a challenging environment. A globally sustained tendency toward low interest rates culminated in a sudden drop in 2020 that combined with the uncertainty of business growth and even survival, raising the prospect of substantial losses. The combination of decreasing interest margin revenue and increased risk of loan losses means that banks need to plan carefully for the future.
This uncertainty over future rate movements is putting pressure on net interest margins, making it a major concern for both banks and regulators. It also emerges as banks grapple with an underlying growth in complexity of treasury and asset/liability risk management (ALM) that has been ongoing for some time.
Against this backdrop, banks are realizing they need to proactively manage their balance sheets in order to maintain growth and enhance profitability. They need to analyze their lending practices, identifying sources of funding and qualifying loan targets to ensure proper loan management. Banks also need to fully understand their exposure to interest-rate and liquidity risk, assessing the mix of variable and fixed-rate products and adjusting their strategy in the face of changing marketplace dynamics.
All of this necessarily entails a re-evaluation of their internal systems’ ability to respond rapidly to changing economic conditions that can impact balance-sheet risk and returns.
The recent economic uncertainty has tested the fitness of internal systems used to monitor and manage balance-sheet risk, and many banks are concluding that legacy point solutions will not measure up to demands from the risk and finance departments to model numerous business and risk scenarios.
Systems that used to turn around scenarios in days and weeks are no longer acceptable, given the need to incorporate business inputs and generate data-driven scenario-based analytics that are required not only to respond to regulators, but also to properly inform bank executives and decision makers. These factors are contributing to a growing expectation from regulators that banks will have in place advanced computational capabilities and speed of processing, coupled with stronger governance over this function
How banks are responding
For many banks, the situation points to the need for a transformation to systems and processes capable of meeting the emerging challenge. Banks are now looking to combine the modeling capabilities of ALM systems with the governance and reach of planning systems and the analytical power of advanced BI tools. Only in this way can they be sure to maintain and perhaps improve profitability.
As part of this new approach, banks are no longer limiting asset liability management to regulatory compliance. The prevailing view is that they can move beyond mere compliance to the creation of business value though flexible scenario modelling that gives them a truly holistic view of the risk factors impacting future performance of the business.
This approach involves assessment across asset/liability risk, liquidity risk, credit risk and operational business planning. To benefit from adopting this kind of proactive approach to risk-adjusted profitability management, banks need to implement several key capabilities. These include methodologies and processes for interest-rate management and balance-sheet optimization as a framework for fast and efficient advanced scenario modelling.
Banks also need to analyze the results of their scenario modeling. For this, they need the analytical power to rapidly evaluate the options available to them as they react to market developments in order to maintain and enhance profitability.
Finally, banks need to act on this analysis. This requires them to put in place the management information tooling needed to enable customer-facing frontline staff to execute the rapid reaction option(s) chosen, as well as processes and metrics that allow management to assess the success or otherwise of any given measure.
Check List for Practitioners
As they move to effect this transformation to a holistic platform for risk-adjusted performance management, banks should bear in mind the following questions:
What factors are impacting earnings and liquidity within the changing environment?
Is the bank incorporating input from its market-facing staff related to growth, spreads and potential losses?
Is the bank taking a credit hit, and if so, how much?
Is the bank managing based on its current balance-sheet composition without considering future events, thereby counting on cash flows that might disappear?
Are the bank’s system capable of handling different interest-rate scenarios, including high volatility and negative rates? Can the bank measure the impact of these scenarios on liquidity and earnings?
Is the bank’s current asset liability management solution helping support decisions that will maximize stakeholder value?
Taking into account these considerations, banks are concluding that what’s needed is a solution that combines three key attributes. First is an asset/liability management system capable of creating multiple scenarios and with the performance required to quickly compute them from the bottom up. Second, the solution needs to include business analytical tools to compare and contrast the rapid reaction plans for prioritization and execution. And finally, it needs a risk-adjusted performance management (RAPM) tool to measure and manage the results.
Taking a Holistic Approach to Risk-Adjusted Performance Management
Past experience has shown that attempting to build a solution with this breadth of capabilities can itself be a risky business. With legacy point systems typically focused on addressing just one area of the overall requirement, banks are often forced to cobble together a fragmented solution to the challenge. This approach has its disadvantages, chief among them being the lack of a comprehensive or holistic view of the bank’s true risk position. Indeed, manual processes based on spreadsheets of general ledger data may provide a current view of the business, but fails to model for unforeseen risks or anticipate changing behaviors.
The result can be a disconnect between the bank’s view of the risks it faces and the true factors impacting the bank’s performance going forward, which undermines the entire raison d’etre of the exercise.
On top of that, dealing with multiple systems and suppliers can itself introduce risk into the situation, in the form of miscommunication, lack of clarity over ownership of key functions and poor interoperability that can potentially disrupt work flows. The use of multiple individual suppliers may require the bank to maintain multiple project teams with various specializations and vendor points of contacts, introducing complexity and expense.
For these reasons, banks increasingly are turning toward a more integrated approach combining risk, compliance and analytics to meet the challenge of risk-adjusted performance management.
Adopting a consolidated platform can give banks the consistency and agility to gain a true view of their risk situation.
Wolters Kluwer Financial Services’ OneSumX Risk Management, for example, combines comprehensive income calculations with scenario modeling and budgeting, allowing banks to get a clear view of performance analytics and management. The solution’s out-of-the-box functionality takes into account future revenues based on qualitative assessments and fixed/variable-rate product mix.
The solution’s modeling framework allows banks to model the impact on the balance sheet of various product scenarios. Its budgeting and planning function, meanwhile, provides an assessment across the whole bank, looking not only at assets and loans but also at payroll, fixed assets and equipment, and other non-income expenses, allowing analysis of performance by region, cost centre or other parameters. Integral to this is a data layer capable of handling data changes, as well as normalization and distribution to specific functions.
The result is a realistic, holistic view of the bank’s business trajectory, accessible and managed through a single point of contact, ensuring consistency of approach and operational efficiency.