Solution Brief
Effective ALM and Liquidity Risk Management
Proactively manage the balance sheet with improved ALM and tight integration to stress testing and other risk and finance activities
The issue
As financial institutions operate in unpredictable macroeconomic conditions, an ever-changing regulatory landscape and the desire to improve business performance, many have begun rethinking their asset and liability management (ALM) and liquidity risk management processes. With an initial goal of improving both the efficiency and quality of their ALM, banks started to focus on automation and enabling more flexible but still risk-siloed, what-if analyses.
Increasingly, banks are looking for ways to enhance their ALM data to provide greater strategic business value. This demands a broader and more dynamic perspective of ALM, with a more comprehensive balance sheet management process that integrates multiple risk dimensions (e.g., market risk, credit risk, liquidity risk, capital standing, etc.). To succeed, the approach must link tightly with other risk management functions while remaining agile enough to accommodate changing business conditions.
The challenge
Economic uncertainty
Financial institutions must effectively manage their portfolios through market uncertainty. SAS provides capabilities for managing interest rate risk and liquidity risk, including stress testing, funds transfer pricing and risk-adjusted performance analysis.
Cost and complexity
Banks face heightened regulatory expectations around liquidity risk and resolution planning. The scalability of SAS risk data and AI, including out-of-box models plus industry-leading data management and reporting capabilities, enables improved performance optimization and significant operational savings.
Extensive system fragmentation
Banks remain challenged by inefficiencies that prevent greater integration with stress testing and capital planning. The SAS Asset and Liability Management solution, powered by Kamakura Risk Manager, supports multiperiod, scenario-based, integrated simulation and valuation for risk management, capital allocation and total balance sheet risk hedging performance management. Optimizing risk and return profiles leads to improved shareholder value.
Dated technology
Legacy ALM solutions limit capabilities and comprehensiveness. SAS enables fast, highly granular what-if and simulation analysis with scalability and traceability.
(Spend more time analyzing results and less time on production processes.; Get unique analysis and insights based on the scenarios you provide.; Use a unified platform for broad, forward-looking balance sheet management.; Improve accuracy of downstream predictive modeling for events.; Easily adapt to changing requirements – integrate ALM with credit risk, market risk and enterprise stress testing.)
Our approach
Financial institutions must operate their ALM processes with a high degree of granularity and transparency. We approach the problem by providing a comprehensive package of analytical, computational and governance capabilities that include:
Cash flow generation and valuation coverage
Generate contractual and behavioral (interest and capital) cash flows for a large set of accounts and instruments. Value the most common instruments and integrate additional pricing functions and external pricing libraries.
Analyses for interest rate risk and liquidity risk
Use scalable grid computing to quickly perform diverse calculations for interest rate and liquidity risk. Use powerful data and AI to optimize your cash flow strategy.
Stress testing and simulations
Analyze static or dynamic balance sheets using diverse business and economic scenarios. Refine analyses with balance sheet evolution assumptions. Incorporate historical and model-based simulations to test portfolio robustness.
Regulatory and internal reporting
Lighten regulatory compliance burdens and streamline internal reporting. Gain the ability to automate standard reports while maintaining granular computational data so it can be reviewed with drilldowns to unlock insights.
SAS difference
As an industry-leading analytics solution provider, SAS has successfully worked with financial institutions of all sizes to address their most pressing analytical challenges.
Our ALM and liquidity risk management solution provides:
A best-in-class data and AI platform
- SAS provides a broad range of integrated capabilities in data management, modeling, simulation and reporting supported by the highly scalable power of grid computing technology.
Comprehensive ALM functionality
- Our solution supports a wide variety of ALM functions, including interest rate risk and foreign exchange risks, liquidity risk stress testing and optimization, risk-based funds transfer pricing analysis, and regulatory reporting.
Flexible, out-of-the-box capabilities
- You can easily configure our industry-leading capabilities to address your unique business requirements while maintaining transparency and traceability.
A scalable, adaptive architecture
- SAS solutions scale to the size and complexity of your organization and its processes.
Constructive collaboration with SAS experts
- SAS has centers of excellence around the world that are staffed by subject-matter experts who can provide support at all stages of your journey.
SAS facts
#2
In 2024, SAS ranked No. 2 overall in the Chartis RiskTech 100
In 2024, SAS ranked No. 2 overall in the Chartis RiskTech 100 and was the category winner in:
- Artificial Intelligence for Banking
- Balance Sheet Risk Management
- Behavioral Modeling
- Enterprise Stress Testing
- IFRS 9
- Model Risk Management
- Risk and Finance Integration