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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Аналитический отчет
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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Технический документ
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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Технический документ
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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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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Технический документ
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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Аналитический отчет
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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Технический документ
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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Технический документ
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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Аналитический отчет
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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Технический документ
Modernizing Asset Liability ManagementChanging priorities in ALM technology, data and analytics.
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Аналитический отчет
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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Аналитический отчет
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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Article
Insights Page
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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Технический документ
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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Технический документ
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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Технический документ
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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Аналитический отчет
Chartis names SAS a Leader in Actuarial Modeling and Financial Planning Systems, 2022 -
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.
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Article
Будущее банковского стресс-тестирования с аналитикой SAS в AzureУзнайте о вызовах, с которыми сталкиваются компании при стресс-тестировании, и о преимуществах перехода в облако.
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Вебинар
Гибкий подход к автоматизации задач управления рисками: вопросы прогнозирования, оптимизации и подготовки отчетностиРыночная нестабильность и оценка рисков компании: на какие задачи в области управления рисками обратить внимание, какие метрики прогнозировать и как не только сохранить устойчивость бизнеса, но и сделать шаг вперед, сохранив и приумножив преимущества от использования инструментов SAS.
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Вебинар
Управление нефинансовыми рисками в свете новых требований Банка России и роль внутреннего аудитаНовые требования Банка России к системе управления операционным риском обязывают финансовые организации привести практики управления в соответствие с нововведениями. Чтобы правильно выстроить приоритеты задач и разобраться в тонкостях вышедших требований, приглашаем вас на вебинар.
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Вебинар
Управление моделями и автоматизация процессов валидацииНестабильный рынок и модели: как быстро адаптироваться к бурно изменяющимся условиям и правильно применять свои аналитические ресурсы. Как российские компании адаптируются к новым условиям рынка, и как инструменты SAS могут помочь в этом.
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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.
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Article
Препятствий для построения моделей с помощью технологий искусственного интеллекта и машинного обучения нетМодели машинного обучения уже на протяжении пяти лет применяются российскими финансовыми организациями для оценки кредитного риска и валидации моделей. О том, насколько регуляторы готовы работать с моделями на базе технологий ИИ и машинного обучения, и пойдет речь в данном интервью.
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Вебинар
Практика управления нефинансовыми рисками в свете новых требований Банка РоссииУзнайте как правильно выстроить приоритеты задач и разобраться в тонкостях вышедших требований Банка России к системе управления операционным риском
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Вебинар
Правильные решения в условиях кризиса: как организовать работу с аналитическими моделями в быстро меняющейся среде с помощью принципов ModelOpsНа вебинаре вы узнаете, как управлять аналитическими моделями во времена экономической нестабильности и при этом получать максимум практической пользы от внедрения технологий машинного обучения.
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Аналитический отчет
Chartis RiskTech Quadrant for Credit Risk Solutions 2020 -
Аналитический отчет
Risk Technology Awards 2020Consumer credit modelling software of the year – SAS
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Article
Страховой Дом ВСК: «Страховым компаниям сегодня жизненно важны IT-инновации»Какие технологии позволяют страховщику максимально учитывать характеристики автовладельца и транспортного средства и более объективно оценивать принимаемые риски, рассказал вице-президент Страхового Дома ВСК Василий Бусаров.
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Вебинар
Как удержать позиции на рынке медицинского страхования в условиях экономического спада.Стратегия и практика применения аналитических решений для повышения эффективности андеррайтинга и медэкспертизы
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Вебинар
COVID-19: управление рисками корпоративных клиентов во время нестабильностиИзменения в оценках рисков для клиентов корпоративного бизнеса и субъектов МСБ: новые вызовы в условиях пандемии. С какими сложностями сталкивается банковский сектор, и как инструментыSAS могут помочь их преодолеть.
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Article
Фокус – на контрольВремя характеризует наши запросы. Сейчас это оперативность, скорость, доступность и простота. Основополагающие изменения, отвечающие темпам жизни и набранным «сверхскоростям» и затронувшие все сферы жизни.
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Customer Story
Modernizing consumer lending in VietnamVietCredit aims to revolutionize the consumer finance market with SAS.
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Customer Story
Making faster, better lending decisionsLocal Government Federal Credit Union sees efficiency gains with SAS.
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Article
МСФО 17: нет времени на раздумьяМСФО 17 - это основанный на принципах стандарт бухгалтерского учета для ориентированной на будущее оценки договоров страхования. Предназначенный для повышения финансовой прозрачности, МСФО 17 требует, чтобы страховщики более подробно сообщали о том, как договоры страхования и перестрахования влияют на их финансы и риск.
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Article
Сценарное стресс-тестирование: выходя за пределы нормативных требований Благодаря регуляторному стресс-тестированию банки получили навыки управления в условиях определенности.
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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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Технический документ
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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Технический документ
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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Технический документ
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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Аналитический отчет
How Data Science Teams Leverage Machine Learning and Other Advanced AnalyticsGartner's 2017 customer reference survey for data science and machine learning platforms reveals how many organizations are undertaking data science initiatives.
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Технический документ
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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Технический документ
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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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.
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Технический документ
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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Article
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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Технический документ
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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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.
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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.
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Технический документ
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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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.
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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.
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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.
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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.
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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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Технический документ
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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Технический документ
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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Оперативная сводка
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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Технический документ
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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Технический документ
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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Технический документ
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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Технический документ
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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Технический документ
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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Технический документ
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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Технический документ
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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Технический документ
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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Технический документ
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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Event Collateral
Технический документ
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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Технический документ
Managing Models and Their RisksComputational and technological challenges present opportunities for a fast-evolving risk management discipline.
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Технический документ
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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Технический документ
From Crisis to Opportunity: Redefining Risk ManagementHow a more automated approach to risk management can transform banks’ performance, during the pandemic and beyond.
