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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分析报告
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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分析报告
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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客户案例
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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客户案例
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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分析报告
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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电子书
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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文章
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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文章
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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白皮书
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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客户案例
A risk-based approach to combat money laundering in IsraelSAS Anti-Money Laundering helps Ayalon Insurance monitor suspicious activity and meet challenging regulatory requirements.
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白皮书
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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白皮书
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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白皮书
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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电子书
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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活动相关资料
白皮书
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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白皮书
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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白皮书
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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文章
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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文章
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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文章
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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文章
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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客户案例
A model solutionTD Bank uses SAS Model Risk Management to stay on top of regulatory requirements, facilitate cross-functional collaboration and drive business value.
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文章
IFRS 17: Waiting is not an optionIFRS 17 is a principles-based accounting standard for the future-oriented valuation of insurance contracts. Designed to increase financial transparency, IFRS 17 requires insurers to report in more detail on how insurance and reinsurance contracts affect their finances and risk.
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文章
超越 IFRS 17，未来业务展望这篇洞察文章揭示了保险公司除了满足新的IFRS 17会计准则的报告要求外，如何更好地利用数字，并探索进一步的分析，以增加业务价值。
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文章
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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文章
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.