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SAS® Expected Credit Loss

Efficient IFRS 9 and CECL compliance – controlled, sustainable and flexible.

Easily tackle the added complexity of the new impairment accounting standards – both IFRS 9 and CECL. Respond dynamically to evolving interpretations of the principle-based guidance. With a centralized, flexible, high-performance analytics environment from SAS, you can meet the challenges of expected loss modeling – while advancing your risk management and financial reporting capabilities.

SAS Expected Credit Loss screenshot showing IFRS 9 stage movement report on desktop monitor
SAS Expected Credit Loss screenshot showing IFRS 9 stage movement report on desktop monitor

Get results quickly.

Take advantage of prebuilt model templates – or use your existing impairment models, regardless of platform – for a faster implementation. A user-friendly dashboard and out-of-the-box visualizations make it simple to capture data, execute models and generate reports. You can easily customize accounting rules and data flows, and quickly produce results to assess the financial impacts of the new impairment standards.

SAS Expected Credit Loss screenshot showing IFRS 9 disclosures on desktop monitor
SAS Expected Credit Loss screenshot showing IFRS 9 disclosures on desktop monitor

Establish control and transparency.

A model implementation platform with a centralized model library enables you to effectively monitor the entire modeling process – so you can identify, report and resolve issues quickly. SAS Expected Credit Loss delivers a well-controlled, flexible and scalable solution that supports risk and finance integration capabilities, allowing you to address both current and future IFRS 9 and CECL requirements. Automated reconciliations and comprehensive audit trails ensure reliable financial reporting and transparency to meet the stringent expectations of directors, regulators and auditors.

SAS Expected Credit Loss screenshot showing IFRS 9 process flow chart on desktop monitor
SAS Expected Credit Loss screenshot showing IFRS 9 process flow chart on desktop monitor

Create sustainability in expected credit loss modeling.

Perform calculations faster than ever before with high-performance analytics. You can streamline processes and eliminate bottlenecks to efficiently meet financial reporting deadlines quarter after quarter. SAS Expected Credit Loss ensures reliability and repeatability, while reducing your code base, for greater transparency and lower ongoing maintenance costs.

SAS Expected Credit Loss screenshot showing IFRS 9 MIP model group on desktop monitor
SAS Expected Credit Loss screenshot showing IFRS 9 MIP model group on desktop monitor

Adapt and grow.

A centralized library enables fast, efficient model management, while fostering collaboration between your risk and finance organizations. With the solution's highly flexible, open and user-friendly platform, you can easily assess the impacts of changing data, models and assumptions, as well as add functionality and optimize your workflows over time as needs change.

SAS Expected Credit Loss screenshot showing IFRS 9 model implementation platform run on desktop monitor

Features

  • Expected credit loss assessment and monitoring. Allows centralized management and controlled orchestration of the entire expected loss modeling process via a user-friendly dashboard.
  • Flexible reporting. Easily manage accounting rules. Automate disclosures and posting into accounting ledgers.
  • Full transparency. Comprehensive audit trails provide support for results.
  • Adaptability and scalability. Provides a single management platform and modular structure that let you customize workflows to capture data, execute models, and consolidate and report results. Also scales to support other risk initiatives, such as enterprise stress testing.
  • Open platform. Supports deployment of models built in SAS, Python, R or other programming languages.
  • Simplified coding requirements. Enables efficient implementation, increases transparency and reduces maintenance effort.
  • Centralized model library. Supports strong model governance and promotes efficient reuse, which reduces model risk.
  • High-performance capabilities. Provides extremely fast computational speeds through parallel task execution, in-memory processing and grid optimization.

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