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

Asset & Liability Risk Management

Discover how you can align ALM with other risk and finance functions and reduce manual effort and risk with a highly transparent process. 

In The Spotlight

Chartis RiskTech Quadrant® for ALM Solutions, 2023

SAS distinguishes itself as a strong category leader in analytics solutions for asset and liability management, as well as being recognized as a category leader with integrated solution offerings for funds transfer pricing, liquidity risk management, and capital and balance sheet optimization.

How SAS Supports Asset & Liability Management

A holistic, granular approach to balance sheet and liquidity risk management

Economic volatility and longer-term technology and regulatory trends are driving financial institutions to adopt a more holistic and granular approach to balance sheet management and liquidity risk management. SAS provides powerful analytical, computational and governance capabilities in a scalable, high-performance platform.

Comprehensive ALM functionality

  • Includes interest rate sensitivity and stress testing, considering repricing risk, optionality, yield curve and basis risk.
  • Enables interest income and EVE simulation using multiple approaches.
  • Calculates risk sensitivity measures including durations and convexities for rate-sensitive instruments and Greeks for derivatives.
  • Performs scenario-based ALM and liquidity risk analyses on static or dynamic balance sheets.
  • Incorporates credit and behavioral assumptions along with macroeconomic and market scenarios.
  • Performs risk-adjusted profitability calculations, including funds transfer pricing (FTP).
  • Includes regulatory reporting classification and calculation for Basel III liquidity risk ratios (LCR and NSFR) and interest rate risk in the banking book (IRRBB).

Powerful data management with integrated governance & controls

  • Supports both ad hoc analyses and fully automated production runs with sophisticated error detection, process monitoring and calculation transparency.
  • Efficiently connects to virtually any data source while maintaining full auditability.
  • Provides a user-friendly reporting framework that lets business users create their own reports or customize existing reports.

Robust, flexible architecture

  • Integrates open source, in-house proprietary, and third-party libraries and risk models.
  • Performs timely, on-demand analysis using high-performance execution.
  • Adapts to changing business needs and market requirements.
  • Provides great scalability with simplified maintenance through cloud-native, microservice-based architecture.

Why choose SAS for asset & liability management?

SAS provides a high-quality, integrated solution for ALM

Achieve greater efficiency with less risk

Reduce or eliminate manual effort and the resulting risk of misreporting or late reporting with a highly automated and transparent process. SAS allows you to spend less time moving data and performing calculations and more time analyzing the results.

Gain improved capabilities & controls

Perform fast and highly granular analyses with an underlying high-performance analytics platform that provides rich data management, analytics and reporting capabilities. It also incorporates robust workflow functionality for orchestrating the entire process with full transparency and auditability.

Align ALM with stress testing & other risk & finance functions

SAS asset and liability management offerings integrate with components for stress testing, CECL, IFRS 9 and model risk management. This allows you to achieve tighter alignment across risk and finance functions, as well as maximize your return on investment.

RiskTech100® Awards

Chartis Names SAS a Winner in Seven Categories

Chartis RiskTech 100 2024 Award logo
Chartis RiskTech 100 2024 AI in Banking Award logo

Continuing its march up the world’s foremost ranking of the Top 100 risk management and compliance technology providers, SAS bested seven technology award categories, including AI for Banking, Balance Sheet Risk Management, Behavioral Modeling, Enterprise Stress Testing, IFRS 9, Model Risk Management, and Risk & Finance Integration.

Frequently Asked Questions

What is asset liability management?

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.

Why is ALM important for banks and financial institutions?

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

How does ALM help in managing bank liquidity risk?

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

What are the key risks associated with bank balance sheet management?

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.

How do banks use stress testing to manage liquidity risk?

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.

What is the role of asset-liability committees (ALCOs) in bank balance sheet management?

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.

How does technology and automation help in managing bank balance sheet and liquidity 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.

What is the importance of cash flow projections in managing bank liquidity risk?

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.

How can banks optimize their liability management?

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.

Connect with SAS and see what we can do for you.