10th YEAR AS A CATEGORY LEADER
Chartis names SAS a leader in both Model Risk Governance and Model Validation, 2023
SAS’s category leader position reflects a combination of features and functionality across the entire model lifecycle. SAS Model Risk Management enables users to deploy models at scale, integrate multiple data sources and support an app API-centric architecture. SAS’s position as a category leader is also supported by risk modeling visualization capabilities that support model testing/experimentation and validation process, while the ability to share parameters and integration with in-house development helps to create an efficient validation environment.
Explore More SAS Resources
To browse resources by type, select an option below.
-
- Select resource type
- 분석 보고서
- E-BOOK
- 백서
- 백서
- 기사
- 블로그 게시물
- 책 발췌
- 사례 연구
- 인포그래픽
- 회견
- R E S E A R C H
- 시리즈
- 동영상
- 웨비나
- 고객 사례
-
백서
Pioneering Ethical AI: The Crucial Role of Property and Casualty InsurersInsurers have long been global leaders in addressing risks and protecting people and businesses. As artificial intelligence continues to revolutionize how business gets done, it is redefining how insurers can deliver on their promises. Read this paper to learn from industry veterans and AI experts alike about:
• The state of AI regulations globally.
• The multifaceted role insurers can play in developing AI ethics.
• Why insurers are uniquely qualified to use AI (and GenAI) – and how they’re using these technologies today.
• An approach to an ethical AI framework that any insurer can follow to establish their own AI narrative.
-
기사
Model risk management: Vital to regulatory and business sustainabilitySloppy model risk management can lead to failure to gain regulatory approval for capital plans, financial loss, damage to a bank's reputation and loss of shareholder value. Learn how to improve model risk management by establishing controls and guidelines to measure and address model risk at every stage of the life cycle.
-
백서
Machine Learning Model GovernanceBanks are rapidly expanding their use of machine learning-enabled (ML) models, because they can provide step-level improvements in accuracy. But ML models need even more rigorous governance than traditional models. This paper explores what's required to implement effective ML model governance.
-
이벤트 자료
백서
Model Risk Management: Today's Governance and Future DirectionsA GARP-SAS Survey on Model Risk in the Age of Artificial Intelligence and Machine Learning.
-
E-BOOK
Unifying Model Management Across the BankHow banks can empower all departments to manage model risk effectively across the entire model life cycle.
-
분석 보고서
Chartis names SAS a leader in both Model Risk Governance and Model Validation, 2023.Chartis names SAS a leader in both Model Risk Governance and Model Validation, 2023.
-
고객 사례
리스크 모델에 대한 단일 정보 소스 구축TD Bank는 SAS Model Risk Management 솔루션 도입을 통해 리스크에 대한 실질적인 통찰력을 제공하는 단일 정보 소스를 구축했습니다. 이로 인해 리스크 관리를 개선하며 자본을 최적화하고 비즈니스 가치를 창출한 방법에 대해 알아보십시오.
-
분석 보고서
Chartis RiskTech100 2025SAS ranks #2 overall in the prestigious Chartis RiskTech100, 2025. Six category wins are AI for Banking, Balance Sheet Risk Management, Behavioral Modeling, Enterprise Stress Testing, IFRS 9 and Model Risk Management.
-
기사
What is a risk model?Banks use multiple models to meet a variety of regulations (such as IFRS 9, CECL and Basel). With increased scrutiny on model risk, bankers must establish a model risk management program for regulatory compliance and business benefits. Begin the planning by clearly defining what a risk model is.
-
고객 사례
Making faster, smarter credit decisions while elevating customer experienceAutomated credit risk management process puts ABBANK at the forefront of Vietnam’s credit revolution.
-
백서
Compete and win with better model risk managementAs explored in this paper, models can degrade over time, and sound model risk management (MRM) is the key to managing this risk.
-
분석 보고서
Chartis RiskTech100 2024SAS climbs to No. 2 in the prestigious Chartis RiskTech 100®, 2024, and bested seven technology award categories, including AI for Banking, Behavioral Modeling and Enterprise Stress Testing.
-
백서
Managing Models and Their RisksComputational and technological challenges present opportunities for a fast-evolving risk management discipline.