SAS® Insights
Новости и мнения аналитиков
Популярные статьи
-
- Выберите тему
- Анализ клинических данных
- Развертывание облачных технологий
- Интеллектуальный анализ данных
- Управление данными
- Управление рисками
- Artificial Intelligence
- Data for Good
- Fraud
- IoT
- Marketing
- Аналитика
- Бизнес-аналитика
-
AI in government: The path to adoption and deploymentGovernments hold rich data and rising public expectations. Now’s the time to harness artificial intelligence (AI) and shape the future of AI in Government.
-
Как визуализация данных помогает в борьбе с преступностьюПравоохранительные органы по всему миру все больше используют технологии визуализации данных. Так, в Северной Америке полицейские активно работают с системами видеонаблюдения, которые в реальном времени собирают сводки о преступлениях, сведения о дорожной ситуации, геопространственные, метеорологические и другие данные. Решения принимаются на основе достоверных и надежных сведений, что позволяет своевременно выделять необходимые ресурсы для результативного вмешательства и предупреждения преступлений. Визуализация данных открывает широкие возможности. Воспользуйтесь ими и вы!
-
Beyond IFRS 17 – what's next?IFRS 17 is not just another accounting standard. It represents a long-term investment that will pay off for insurers with a clear vision for future goals. Learn how IFRS 17 can provide transparency and insight to an insurance business while identifying strengths and areas for improvement.
-
AI transforms insurance: See 8 examples of how it worksUsing AI in insurance can boost value for customers, insurance companies and stakeholders alike. Examples range from stronger fraud detection and improved customer service to optimized underwriting processes and competitive advantage. Learn more about how AI is transforming the industry.
-
AI and humanity: Collaborating to solve global problemsЧто происходит, когда искусственный интеллект и люди работают вместе во имя решения глобальных проблем?
-
What is AI modeling?AI modeling involves creating programs that use one or a combination of algorithms to allow computers to think, learn and predict outcomes. Much like a human brain, AI models absorb input data – numbers, texts, images, video, sound – to learn how to predict outcomes or solve specific tasks without explicit instructions at every step.
-
Five AI technologiesОт машинного обучения до компьютерного зрения. Эти технологии подпитывают всеобщее помешательство на ИИ.
-
Understanding digital twin technologyLearn how digital twin technology can change industries from health care to manufacturing, and shape the future of data modeling and process improvements.
-
What is synthetic data? And how can you use it to fuel AI breakthroughs?There's no shortage of data in today's world, but it can be difficult, slow and costly to access sufficient high-quality data that’s suitable for training AI models. Learn why synthetic data is so vital for data-hungry AI initiatives, how businesses can use it to unlock growth, and how it can help address ethical challenges.
-
Big data in government: How data and analytics power public programsBig data in government is vital when analyzed and used to improve the outcomes of both public and private sector programs – from emergency response to workforce effectiveness. The vast volumes of data created every day are the foundation of insightful changes for government agencies across the globe.
-
Unlocking a strategic approach to data and AIAI is only as good as the data that powers it – this is a fundamental truth about data and AI that defines the limits of what’s possible with artificial intelligence. It may seem surprising, but it's rarely a bad algorithm or a bad learning model that causes AI failures. It's not the math or the science. More often, it's the quality of the data being used to answer the question.
-
AI anxiety: Calm in the face of changeAI anxiety is no joke. Whether you fear jobs becoming obsolete, information being distorted or simply missing out, understanding AI anxiety can help you conquer it.
-
Fraud detection and machine learning: What you need to knowМашинное обучение является важной частью инструментария обнаружения мошенничества. Вот что вам нужно для начала работы.
-
Fraud detection and machine learning: What you need to knowМашинное обучение является важной частью инструментария обнаружения мошенничества. Вот что вам нужно для начала работы.
-
6 ways big data analytics can improve insurance claims data processingWhy make analytics a part of your insurance claims data processing? Because adding analytics to the claims life cycle can deliver a measurable ROI.
-
What are AI hallucinations?Separating fact from AI-generated fiction can be hard. Learn how large language models can fail and lead to AI hallucinations – and discover how to use GenAI responsibly.
-
What is a data lake & why does it matter?A data lake is a storage repository that quickly ingests large amounts of raw data in its native format so you can see and respond to new information faster. As containers for multiple collections of data in one convenient location, data lakes allow for self-service access, exploration and visualization.
-
Why banks need to evolve their approach to climate and ESG riskManaging environmental, social and governance (ESG) risk is important to banks, insurers, regulators, investors and consumers – yet there are many interpretations of how to do it. To thrive, organizations must learn how to evolve their risk management practices.
-
Shut the front door on insurance application fraud!Как выявить, что вас обманывают агенты и страхователи, а также распознать первые признаки будущего мошенничества.
-
What are chatbots?Чат-бот – это форма разговорного искусственного интеллекта, предназначенная для упрощения взаимодействия человека с компьютерами. Используя чат-ботов, компьютеры могут понимать и реагировать на приход человека через устную или письменную речь.
-
Управление качеством данных: что вам нужно знатьКачество данных не является хорошим или плохим, высоким или низким. Это диапазон или показатель работоспособности данных, проходящих через вашу организацию.
-
Next generation anti-money laundering: robotics, semantic analysis and AIAdding AI and machine learning to your anti-money laundering program can combat rising compliance pressures, complexity and risks. Learn about the results innovative financial institutions around the globe are getting from next-generation AML.
-
Next generation anti-money laundering: robotics, semantic analysis and AIAdding AI and machine learning to your anti-money laundering program can combat rising compliance pressures, complexity and risks. Learn about the results innovative financial institutions around the globe are getting from next-generation AML.
-
4 strategies that will change your approach to fraud detectionAs fraudulent activity grows and fighting fraud becomes more costly, financial institutions are turning to anti-fraud technology to build better arsenals for fraud detection. Discover four ways to improve your organization's risk posture.
-
The importance of data quality: A sustainable approachBad data wrecks countless business ventures. Here’s a data quality plan to help you get it right.
-
Ключевые вопросы для запуска ваших проектов по аналитике данныхНет единого плана по работе над проектом по аналитике данных. Эксперт по технологиям Фил Саймон предлагает рассмотреть эти десять вопросов в качестве руководства.
-
Analytics tackles the scourge of human traffickingVictims of human trafficking are all around us. From forced labor to sex work, modern-day slavery thrives in the shadows. Learn why organizations are turning to AI and big data analytics to unveil these crimes and change future trajectories.
-
10 ways analytics can make your city smarter From child welfare to transportation, read 10 examples of analytics being used to solve problems or simplify tasks for government organizations.
-
How to uncover common point of purchaseFraudsters use many techniques to steal card data. Banks that want to stay ahead of common point of purchase (CPP) and contain the costs of fraud need to implement advanced analytics techniques to strengthen their fraud prevention programs.
-
Viking transforms its analytics strategy using SAS® Viya® on AzureViking is going all-in on cloud-based analytics to stay competitive and meet customer needs. The retailer's digital transformation are designed to optimize processes and boost customer loyalty and revenue across channels.
-
ТОП-5 схем мошенничества по предоплаченной картеЛучшие практики для предотвращения мошенничества, защиты репутации и обеспечения качественного клиентского обслуживания.
-
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.
Подпишитесь на рассылку инсайтов от SAS