SAS IS A CATEGORY LEADER
Chartis RiskTech Quadrant for Credit Portfolio Management Solutions, 2023
SAS scored four out of four stars in all six vendor capability measures. According to this Chartis report, our solutions can integrate various components smoothly throughout the credit management process. From data management and credit scoring to risk modeling and compliance, the platform creates a unified environment.
SAS stands out in the CPM landscape for its strong suite of advanced analytics capabilities. In an industry where practical insights are crucial, SAS’ expertise in handling complex statistical models and predictive analytics is particularly advantageous for financial institutions looking for a nuanced approach to credit management. This capability isn’t just theoretical – it is a practical tool for those dealing with the complexities of CPM for which there is value in actionable analysis.
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분석 보고서
Chartis RiskTech Quadrant Asset and Liability Management, 2024SAS is named a category leader in Chartis Research's 2024 RiskTech Quadrant for ALM solutions, FTP solutions, LRM and reporting technology solutions, capital and balance sheet optimization solutions., hedging and risk management solutions, and financial planning and budgeting solutions.
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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.
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고객 사례
Calculating credit risk in half the timeTo stay compliant with Basel regulations, Yapi Kredi relies on SAS to handle millions of data sets.
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고객 사례
Austrian bank uses integrated risk and carbon calculation engine to steer toward net-zero by 2050Erste Group extends its SAS Solution for Regulatory Capital to help understand and reduce impact of climate change on its portfolios
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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.
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E-BOOK
Unifying Model Management Across the BankHow banks can empower all departments to manage model risk effectively across the entire model life cycle.
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기사
Credit risk management is the answerLending and loan volume is back up to pre-crisis levels. But banks are facing higher delinquencies as well. That's why improving credit risk management is crucial.
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기사
IFRS 9 and CECL: The challenges of loss accounting standardsThe loss accounting standards, CECL and IFRS 9, change how credit losses are recognized and reported by financial institutions. Although there are key differences in the standards for CECL (US) and IFRS 9 (international), both require a more forward-looking approach to credit loss estimation.
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백서
Tackle the Complexity of IFRS 9 and CECL StandardsThe US standard for CECL increases the complexity of the allowance estimation process. Outside the US, IFRS 9 is having the same effect. Learn about best practices for getting this right.
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고객 사례
자금세탁 범죄에 맞서는 이스라엘의 위험 기반 전략SAS® Anti-Money Laundering 활용으로 의심스러운 활동을 모니터링하고 까다로운 규제 요건을 준수할 수 있게 되었습니다.
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백서
CECL: Don't Neglect the FundamentalsFirms that proactively implement a CECL process that is controlled, efficient, collaborative and sustainable will find themselves with a competitive advantage over time. This paper discusses the long-term benefits of this holistic approach.
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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.
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백서
Basel IV: The push you neededIn a landscape of great uncertainty and the economic crisis sparked by COVID-19, financial institutions must address the challenges Basel IV will bring. An integrated risk management approach is the best path forward to meeting ever-evolving regulatory needs.
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E-BOOK
Adapting to the New Age of Risk AnalyticsRapid advancements in technology are leading to a new age of risk analytics. The availability of commercial and open source software – coupled with significantly improved integration using industry standard tools – has made analytics more user friendly, expanding its reach to a broader range of business professionals.
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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.
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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.
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백서
Risk-Aware Finance and the Changing Nature of CreditNew research by Chartis and SAS highlights how financial institutions must align finance and risk departments to accurately assess future risks and bolster budgeting and forecasting capabilities. This paper explores how risk-aware finance is becoming essential to meeting future regulatory and competitive demands.
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기사
Risk data infrastructure: Staying afloat on the regulatory floodWhat are the challenges of a risk data infrastructure and how can they be addressed? Here's what you need to know to build an effective enterprise risk and finance reporting warehouse that will effectively address compliance requirements.
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기사
CECL: Are US banks and credit unions ready?CECL, current expected credit loss, is an accounting standard that requires US banking institutions and credit unions to estimate life-of-loan losses at origination or purchase.
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기사
Understanding capital requirementsCredit risk classification systems have been in use for a long time, and with the advent of Basel II, those systems became the basis for banks’ capital adequacy calculations. What is needed going forward is an efficient and honest dialogue between regulators and investors on capitalization.
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기사
Understanding capital requirements in light of Basel IVMany financial firms are already using a popular 2012 PIT-ness methodology for internal ratings-based models. This article examines eight ways the industry is successfully using the methodology – and why this approach can bring synergies for banks, value for regulators, and major competitive advantages.
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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.
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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.
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기사
IFRS 17 : 방치는 해답이 아닙니다.IFRS 17은 보험 계약의 미래 지향적 평가를 위한 원칙을 중요하게 여기는 회계 기준입니다. 재무 투명성을 높이기 위해 설계된 IFRS 17은 보험사에게 보험 및 재보험 계약이 재무 및 위험에 미치는 영향에 대해 더 자세히 보고하도록 요구합니다.
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기사
Risk capital and lessons from the TitanicEconomic capital is that something extra that senior management needs for staying financially afloat in tough economic times. SAS uses the tale of the Titanic to describe risk capital risk management best practices.
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기사
Five myths and misconceptions community banks have about Basel IIIMyth No. 1: Basel II didn't pertain to us, so Basel III won't either. Wrong. The US Basel III Final Rule provides capital frameworks commensurate with bank size, so the rules apply to nearly all banks in the US. Myths 2-5...