In the Spotlight
Investing in enterprise risk management? Discover why SAS is a leader.
SAS wins three Risk.net Risk Technology Awards
SAS again scored a collection of wins from Risk.net's prestigious 2022 Risk Technology Awards, with our best-in-class risk technology offerings earning recognition as consumer credit modeling software of the year, regulatory capital calculation product of the year and IFRS9 enterprise solution of the year.
Browse the latest e-books, white papers, webinars and more.
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E-BOOK
5 Steps to a Unified Enterprise Customer Decisioning StrategyIn an era of unprecedented technology-driven disruption, banks are facing a dual challenge: Meeting rising customer expectations while navigating increasingly complex regulatory demands.
To remain competitive, banks must not only innovate but also streamline operations and foster greater collaboration across departments, breaking down traditional silos and working toward innovation.
How can banks simplify their operations, future-proof their services, and drive growth? Enterprise customer decisioning is the answer. This ebook describes five important steps to making better decisions faster with enterprise customer decisioning.
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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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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.
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고객 사례
Accelerating stress testing in the cloudIntesa Sanpaolo enhances efficiency and meets stress-testing requirements six times faster with SAS Viya.
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백서
The balance sheet risk conundrumDiscover five key elements required to achieve the most possible value from a modernized ALM and liquidity risk management program.
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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.
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E-BOOK
The insurance data and AI revolutionInsurers face continual disruptions these days as they respond to price sensitivity, the push for sustainable practices, evolving regulations, climate change issues and all types of heightened risks. How should they respond?
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E-BOOK
Supercharge your ALM system: How treasury and finance departments can empower banks to brace for the unexpectedDuring a long period of economic stability, many financial institutions didn’t modernize their asset and liability management (ALM) programs to the same extent that they modernized other programs. The high-profile failures of several banks have since emphasized the importance of having a robust ALM program. As banks strive to enhance their ALM analytics to provide greater strategic business value, they must have a broader and more dynamic perspective of ALM – along with a comprehensive balance sheet management process that integrates multiple risk dimensions. Discover how SAS’ industry-leading analytical platform can help you achieve these goals.
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백서
How to compete in the new era of customer-centric insuranceLearn how to quickly respond to market changes by reducing the time needed to build hand-coded models and accommodating a range of programming languages.
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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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고객 사례
European Banking-as-a-Service leader strengthens its AML/CFT and fraud surveillance system with SASTreezor uses SAS Anti-Money Laundering to stay ahead of emerging risks, improve operational efficiency and expedite investigations.
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백서
Insurers: Are you ready for IFRS 17?This white paper explores what IFRS 17 means for insurers, challenges faced in the transition and the top 10 things they should have in their IFRS 17 information architecture.
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백서
The balance sheet risk conundrumHow SAS and Microsoft are modernizing asset liability management and liquidity risk management in turbulent times.
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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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분석 보고서
Chartis RiskTech Quadrant Asset and Liability Management, 2023SAS is named a category leader in Chartis Research's 2023 RiskTech Quadrant for ALM solutions, RiskTech Quadrant for FTP solutions, RiskTech Quadrant for LRM solutions and RiskTech Quadrant for capital and balance sheet optimization solutions.
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백서
Modernizing Asset Liability ManagementChanging priorities in ALM technology, data and analytics.
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분석 보고서
SAS is a Leader in The Forrester Wave™: AI Decisioning Platforms, Q2 2023.The Forrester Wave™: AI Decisioning Platforms, Q2 2023 recognizes SAS for seamlessly integrating world-class analytics for decisioning.
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고객 사례
Combating financial crime and terrorism financing with real-time sanctions screeningOrange Bank stays ahead of emerging risks and changing regulations with a cloud-based sanctions-screening solution from SAS and Neterium.
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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.
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고객 사례
Achieving regionwide IFRS 17 compliance for insurance reporting Tokio Marine Asia uses cloud-based SAS solution to attain complete, consistent compliance for insurance contracts across eight regional markets.
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기사
Why banks need to evolve their approach to climate and ESG riskManaging environmental, social and governance (ESG) risk is important to banks, regulators, investors and consumers – yet there are many interpretations of how to do it. To thrive, organizations must evolve their risk management practices – including those affected by ESG risk.
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백서
Banking in 2035: global banking survey reportWhat trends do banking leaders consider to be the greatest risks and the greatest opportunities? What internal and external barriers stand in their way? What technologies will help them harness the opportunities ahead? Download the report to explore.
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백서
Decision science: From automation to optimizationThis Risk.net white paper explores decision science and automation and the efficiencies it brings, and offers insight into why automation – married with adaptable analytics – is now crucial.
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백서
Banking in 2035: three possible futuresThis paper explores how the major forces affecting banks may evolve between now and 2035, seen through the lens of three potential scenarios.
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분석 보고서
Chartis names SAS a Leader in Actuarial Modeling and Financial Planning Systems, 2022SAS is a leader in the categories of asset and liability management, risk and capital management, and financial planning and analysis.
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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
Are you good at scoring?Credit scoring is the foundation for evaluating clients who apply for a loan (or other types of exposure for the bank). It is not unusual for it to take up to 12 months to build and deploy a new credit scoring model. Reforming the process will help minimize losses, increase earnings and reduce operational risk.
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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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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.
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고객 사례
Fintech company’s rapid growth leads to consistent cloud strategyauxmoney saves resources, gains flexibility and scalability with risk management in the SAS Cloud hosted on Microsoft Azure.
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고객 사례
Analytic models spotlight risky loansItaly’s Ministry of Economy and Finance uses advanced analytics on SAS Viya to quickly calculate risk on financial guarantees.
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고객 사례
Building reliability in riskBanca Mediolanum uses SAS Viya to develop high-performing, reliable credit scoring models.
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고객 사례
Finland’s top retail bank applies AI to improve customer service and credit scoringS-Bank provides better customer service and faster, more accurate loan processing time using SAS Viya on Azure.
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기사
IFRS 17의 도래 – 무엇이 변하는가?IFRS 17은 단순한 새로운 회계 기준이 아닙니다. 궁극적인 목표는 보험 사업에 투명성과 통찰력을 요구하는 동시에 기업의 장단점을 파악하는데 있습니다. 장기 목표를 달성하고, IFRS 17에 따른 개선안을 넘어 더 나아가 광범위한 비즈니스 가치를 달성하는 방법을 알아보십시오.
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고객 사례
Stress testing becomes competitive advantage with advanced analyticsStandard Chartered Bank uses SAS Analytics to meet stress-testing requirements and assess the effect of crisis scenarios on its future P&L and balance sheet.
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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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고객 사례
Advanced simulations and ‘stress-proof’ models help digital bank successfully navigate uncertain scenariosBanca Progetto relies on predictive analytics and a cloud-first approach to mitigate risk, better serve clients and plan for the future.
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기사
Risk data aggregation: Transparency, controls and governance are needed for data quality and reportingFinancial institutions’ data aggregation and reporting techniques and systems are receiving increased attention both internally and externally. Find out how to take a comprehensive approach to BCBS principles and risk data aggregation and management.
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기사
IFRS 17 and Solvency II: Insurance regulation meets insurance accounting standardsIFRS and Solvency II encourage comparability and transparency from a regulatory and accounting perspective for insurers, but there are important differences.
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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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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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고객 사례
Modernizing consumer lending in VietnamVietCredit aims to revolutionize the consumer finance market with SAS.
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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
시나리오 스트레스 테스트 : 규제 준수 이상의 사안.시나리오 스트레스 테스트는 은행에 다각도의 조건과 심각도 수준을 활용해, 금융 위기 대응 시뮬레이션을 진행 할 수있는 방법을 제공합니다.
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E-BOOK
Stress and Strategy: A C-Suite Guide to Scenario-Based Risk ManagementThis e-book from SAS and Argyle explores some of the ways that top-performing organizations are undertaking scenario-based risk assessment to develop and manage their business strategies.
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백서
Keys to robust credit risk modeling and decisioning for better customer experienceModernizing and automating the end-to-end process for origination and servicing – from data management to model development to credit decisions – can reduce credit losses and boost performance. This paper explores how infusing machine learning into this process supports more effective credit decisions for individuals, products or portfolios.
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기사
분석이 가능한 CRO와 위험을 인식하는 CFO.리스크를 사전 조치하는 기업 문화를 형성하기 위해, CRO의 가장 중요한 협력 관계는 CFO 및 재무 팀입니다. 예산 편성 및 감독을 담당하는 임원인 CFO와 CRO는 경쟁 목표에 휘말리는 경향이 다소 있습니다.
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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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백서
Designing the Infrastructure for Credit Risk Model Development and Deployment in UtilitiesExplore the challenges of setting up credit risk modeling – and how to establish an effective program through better planning and design.
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고객 사례
Cultivating a risk cultureBank of Baroda strengthens governance and fosters trust using SAS Governance and Compliance Manager.
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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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백서
Designing the Infrastructure for Credit Risk Model DevelopmentExplore the most common problems organizations face when setting up infrastructure for analytics – and credit risk modeling specifically – and learn about ways to increase productivity and reduce problems through better planning and design.
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기사
frtb: a wait and see strategy could be riskyFRTB, fundamental review of the trading book, is a regulation that changes how banks analyze market risk in the trading book to address systemic challenges.
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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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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
Analytics Platform and Program: Keys to Success for Regulatory Compliance in Financial ServicesAdvanced analytics is at the heart of regulatory compliance processes in financial services. This paper discusses data enormity and preparation for analysis; flexibility in computing platforms; and a comprehensive program for data, analytics and models.
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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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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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기사
New attitudes for liquidity risk managementRecent liquidity risk shocks and regulatory pressures have highlighted the need for agile liquidity risk management and planning systems. To manage liquidity risk more strategically, banks will need the right strategy, solution architecture and IT systems – plus governance to manage the process.
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기사
Should banks adopt regulations as best practices?The regulatory tsunami isn't letting up, but is there value to be gained in adopting, for instance, BCBS 239 principles?
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기사
Retail cyber risk toleranceManage your data assets just as you would any of your physical assets by putting security plans in place for any and all contingencies.
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백서
Firmwide Scenario Analysis and Stress TestingThis paper explores the two most commonly used firmwide scenario model approaches for stress testing, firmwide risk capital measures and how regulatory stress testing is different from the firmwide risk capital approach mandated by CCAR and EBA.
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고객 사례
보고 체계 개선을 통한 위험 관리에 대한 이해 개선SAS Visual Analytics helps Erste Bank Croatia tackle diverse data for accurate analysis.
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고객 사례
Forecasting helps Wescom Credit Union save millions of dollarsWescom Credit Union increases lending decision accuracy by at least 50%.
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기사
IFRS 9 impairment regulation: How to prepare for the data tsunamiBanks will have to update ECL amounts at each reporting date for credit risk changes, significantly increasing impairment calculations and data collection.
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고객 사례
A faster, comprehensive way to manage portfolio riskBank of India uses SAS to improve risk analysis, automate processes and meet both regulatory and internal requirements.
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고객 사례
Fast track to advanced operational risk managementBank of India uses SAS Governance and Compliance Manager for operational risk management capabilities to improve loss data quality and reporting.
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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...
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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
Data quality: The Achilles' heel of risk managementGiven the tightly regulated environment banks face today, the importance of data quality cannot be overstated. Beyond the obvious benefits of staying one step ahead of regulatory mandates, having accurate, integrated and transparent data drives confident, proactive decisions and supports a solid risk management foundation.
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기사
A new arms race: Analytics for commodity market complianceRogue trading and dodgy deals are not the only things keeping chief risk officers awake. Today’s regulators now employ big data analytics to uncover troubles in the commodity swaps market. Staying ahead of innocent compliance errors – and quickly identifying the occasional bad actor from within – will require some tough analytics of your own.
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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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고객 사례
Low-risk strategy delivers top-level returnsBank Leumi uses SAS to achieve superior shareholder returns in a competitive environment and with high capital reserves.
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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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백서
Scenario-Based Risk Management: Overcoming the ChallengesAs regulatory stress test regimes mature, financial institutions are looking for ways to harness investments they made in stress testing programs to gain additional business value.
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백서
Stress Testing 2.0: Better Informed Decisions Through Expanded Scenario-Based Risk ManagementA road map for those who are starting to build – or are rethinking their approach to – their stress testing infrastructure and strategy.
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경영진 요약정보
Climate RiskA collection of articles from Risk.net on the impact of climate change on banks. SAS provides some key ideas for companies performing a self-assessment of their maturity in climate risk management.
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백서
The Value of Credit Risk Transformations and the Role of AIAs banks seek continued progress in their credit risk transformation journey, the insights gathered by SAS and GARP reveal the obstacles they face.
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백서
Seven trends that will transform bankingAdvanced analytics and big data are enabling smarter decisions and more efficient processes, from credit to compliance and risk management.
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백서
LDTI: Finding a solution for today and tomorrowSAS can help insurers address the data and technology complexities of LDTI with a solution that solves the problems of today while looking ahead to obstacles of the future.
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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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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
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
Artificial Intelligence in Banking and Risk ManagementGlobal Association of Risk Professionals (GARP) and SAS survey drew more than 2,000 responses from across the financial services industry to answer questions about the current and future state of AI in risk.
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백서
Outrunning risk with cloudBy employing cloud-based risk modeling and decisioning capabilities, banks can make faster, more sophisticated risk calculations that keep them one step ahead of existing and emerging threats.
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백서
Building Artificial Intelligence in Credit Risk: A Commercial Lending PerspectiveWhat will it take for banks to trust artificial intelligence (AI) and machine learning (ML) with judgments about data accuracy and leverage it for commercial lending process automation?
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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
Managing Models and Their RisksComputational and technological challenges present opportunities for a fast-evolving risk management discipline.
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백서
Intelligent Decision Automation for Telecommunications in the Digital AgeLearn how communications providers who adapt and embrace analytics and AI will unlock opportunities by converting current processes to be reliably smart, such as credit risk, fraud and collections.
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백서
From Crisis to Opportunity: Redefining Risk ManagementHow a more automated approach to risk management can transform banks’ performance, during the pandemic and beyond.
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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
