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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.
- Analyst Report 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.
- White Paper 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.
- Customer Story Accelerating stress testing in the cloudIntesa Sanpaolo enhances efficiency and meets stress-testing requirements six times faster with SAS Viya.
- White Paper The balance sheet risk conundrumDiscover five key elements required to achieve the most possible value from a modernized ALM and liquidity risk management program.
- Customer Story Making faster, smarter credit decisions while elevating customer experienceAutomated credit risk management process puts ABBANK at the forefront of Vietnam’s credit revolution.
- 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?
- White Paper 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.
- Analyst Report 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.
- Customer Story 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.
- White Paper 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.
- White Paper The balance sheet risk conundrumHow SAS and Microsoft are modernizing asset liability management and liquidity risk management in turbulent times.
- Analyst Report 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.
- White Paper Modernizing Asset Liability ManagementChanging priorities in ALM technology, data and analytics.
- Analyst Report 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.
- Customer Story 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.
- Analyst Report 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.
- Customer Story 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.
- Article Insights Page Porque é que os bancos precisam de uma abordagem ao clima e risco ESG mais evoluída?A gestão do risco ambiental, social e de governança (ESG) é importante para os bancos, entidades reguladoras, investidores e consumidores – no entanto, existem muitas interpretações sobre como fazê-lo Para florescerem, as organizações têm de desenvolver as suas práticas de gestão do risco – incluindo aquelas que são afetadas pelo risco ESG.
- White Paper 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.
- White Paper 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.
- White Paper 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.
- Analyst Report 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.
- Customer Story 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.
- Customer Story Analytic models spotlight risky loansItaly’s Ministry of Economy and Finance uses advanced analytics on SAS Viya to quickly calculate risk on financial guarantees.
- Customer Story Building reliability in riskBanca Mediolanum uses SAS Viya to develop high-performing, reliable credit scoring models.
- Customer Story 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.
- Customer Story 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.
- Article 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.
- Customer Story 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.
- Article 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.
- Article 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.
- Article 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.
- Article Beyond IFRS 17 – what's next?IFRS 17 is not just a new accounting standard. Its fundamental objective is to provide transparency and insight to the insurance business while identifying strengths and areas for improvement. Learn how to keep a long-term vision and achieve broader business value beyond the immediate demands of IFRS 17.
- Customer Story A risk-based approach to combat money laundering in IsraelSAS Anti-Money Laundering helps Ayalon Insurance monitor suspicious activity and meet challenging regulatory requirements.
- Customer Story Modernizing consumer lending in VietnamVietCredit aims to revolutionize the consumer finance market with SAS.
- Article 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.
- Article Scenario stress testing: Beyond regulatory complianceScenario stress testing offers banks a way to simulate responses to a financial crisis using a wide range of conditions and levels of severity.
- 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.
- White Paper 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.
- Article The analytical CRO and the risk aware CFOTo create a more risk-aware organization, the most important collaborative relationship for the CRO is with the CFO and the finance team. The CFO and CRO – as the executives responsible for budgeting and supervision – tend to get caught in the middle of competing objectives.
- White Paper 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.
- White Paper 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.
- White Paper 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.
- White Paper 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.
- Customer Story A model solutionTD Bank uses SAS Model Risk Management to stay on top of regulatory requirements, facilitate cross-functional collaboration and drive business value.
- White Paper 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.
- Article CECL: Are US banks ready?CECL, current expected credit loss, is an accounting standard that requires US banking institutions to estimate life-of-loan losses at origination or purchase.
- White Paper 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.
- Article 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.
- Article 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.
- Customer Story Calculating credit risk in half the timeTo stay compliant with Basel regulations, Yapi Kredi relies on SAS to handle millions of data sets.
- Article 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.
- Article 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?
- Article 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.
- White Paper 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.
- Customer Story Better reporting yields better understanding of risk managementSAS Visual Analytics helps Erste Bank Croatia tackle diverse data for accurate analysis.
- Article 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.
- Customer Story Forecasting helps Wescom Credit Union save millions of dollarsWescom Credit Union increases lending decision accuracy by at least 50%.
- Article 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.
- Article 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 will drive confident, proactive decisions to support a solid risk management foundation.
- Article 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.
- Article 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.
- Article 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.
- Article Attitudes toward liquidity risk have changedIn 2008, most banks took for granted that they would always have access to liquidity, and so they didn’t worry too much about liquidity risk. Even regulators worried little about it – until the danger was exposed.
- Customer Story Low-risk strategy delivers top-level returnsBank Leumi uses SAS to achieve superior shareholder returns in a competitive environment and with high capital reserves.
- 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.
- White Paper 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.
- White Paper 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.
- Executive Brief 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.
- White Paper 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.
- White Paper 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.
- White Paper 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.
- White Paper 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.
- White Paper 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.
- White Paper 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.
- White Paper 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.
- White Paper 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.
- White Paper 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?
- Event Collateral White Paper Model Risk Management: Today's Governance and Future DirectionsA GARP-SAS Survey on Model Risk in the Age of Artificial Intelligence and Machine Learning.
- White Paper Managing Models and Their RisksComputational and technological challenges present opportunities for a fast-evolving risk management discipline.
- White Paper 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.
- White Paper From Crisis to Opportunity: Redefining Risk ManagementHow a more automated approach to risk management can transform banks’ performance, during the pandemic and beyond.
- Customer Story 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