Proactively manage the balance sheet with improved ALM and tight integration to stress testing and other risk and finance activities

Asset liability management (ALM) is a process financial institutions use to manage and balance their assets and liabilities in order to mitigate earnings risk and rate repricing risk and to ensure adequate liquidity is maintained while limiting risk to within their stated risk appetite.

An effective ALM program helps financial institutions build and maintain a balanced portfolio, improve earnings, mitigate risk and manage liquidity.

ALM helps in managing bank liquidity risk by ensuring that banks have sufficient cash and liquid assets to meet their short-term obligations.

The key risks associated with bank balance sheet management include credit risk, interest rate risk, liquidity risk and operational risk. Failure to adequately manage any of these can also impact reputational risk and trigger regulatory actions.

Regulatory requirements differ by region, but requirements largely leverage guidance from the Basel Committee. The main regulatory metrics employed for liquidity risk management are the liquidity coverage ratio (LCR) and net stable funding ratio (NSFR). Many supervisors also prescribe scenario-based stress testing as a means to ensure liquidity is maintained over adverse conditions.

Banks use stress testing to assess their ability to withstand liquidity shocks and ensure they have enough liquidity reserves to meet their obligations over severe, but plausible, adverse scenarios.

ALCOs serve as the internal governing body for asset and liability management at banks. They play a critical role in setting asset and liability targets, monitoring risk exposure and developing strategies to mitigate risk.

Technology and automation help banks streamline their processes, reduce manual errors and key person risks, improve auditability, and improve decision making through richer and more timely insights.

Cash flow projections allow banks to forecast future cash inflows and outflows and plan accordingly. A range of plausible scenarios should be applied to the forecast exercise.

Banks can optimize their liability management by diversifying their liabilities and assessing their run-off profile. They should also manage their funding sources using advanced analytics and regularly performed scenario analysis.

In light of recent bank failures resulting from inadequate liquidity management practices, banks should anticipate increasing regulatory expectations around their ALM programs. A volatile interest rate environment further challenges balance sheet management. Additionally, as in other industries, financial institutions are facing challenges around finding and maintaining a skilled workforce and operating in a hybrid work environment. To address these challenges, banks are increasingly leveraging technology and analytic advancements, such as cloud computing and AI/ML.