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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.
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Intelligent policing: Are data analytics systems the key to public safety?Police agencies are navigating rapidly changing landscapes, rising data volumes, evolving threats, and growing expectations for transparency and coordination. They can't keep pace if they're dependent on siloed data, aging platforms and legacy practices. Intelligent policing can help. This evolution from reactive to problem-oriented policing relies on shared data, visualization and a scalable analytics ecosystem.
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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.
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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.
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IFRS 17 and Insurance Capital Standards: Insurance regulation meets insurance accounting standardsIFRS 17 and ICS facilitate comparability and transparency for insurers from a regulatory and accounting perspective. Explore their similarities and differences, recognizing how clear communications can help stakeholders navigate regulatory and statutory reporting changes, increase confidence, and help mitigate adverse effects on share prices and ratings.
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AI and humanity: Collaborating to solve global problemsDisplaced communities, the food crisis and natural disasters – these situations affect quality of life, and even the ability to survive. Could artificial intelligence be the unexpected boost humanity needs? Could it accelerate our ability to make a positive, lasting impact? Learn more and read examples of how AI is being used to find solutions to global problems.
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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.
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Five AI technologiesDo you know the difference between artificial intelligence and machine learning? Can you explain the basics of AI technologies like GenAI and AI agents? Read our overview to understand these and other technologies behind the AI craze.
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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.
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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.
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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.
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AI como fonte de ansiedade: Manter a calma perante as mudançasA AI como fonte de ansiedade não é uma brincadeira. Quer receie certos trabalhos tornarem-se obsoletos, distorção da informação, ou simplesmente deixar escapar oportunidades, compreender a AI como fonte de ansiedade será fundamental para ultrapassar esses sentimentos.
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Fraud detection and machine learning: What you need to knowMachine learning and fraud analytics are critical components of a fraud detection toolkit. Discover what you’ll need to get started defending against fraud – from integrating supervised and unsupervised machine learning in operations to maintaining customer service.
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Utilização de*** dados sintéticos para impulsionar avanços na AIAprenda porque é que os dados sintéticos são vitais para as iniciativas em AI, como os negócios os utilizam para desbloquear o crescimento, e como podem ajudar a fazer face aos desafios éticos.
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Conheça 6 formas de utilizar a análise de big data que podem melhorar o processamento dos pedidos de indemnização de segurosPorque é que deve incluir a análise de processamento de dados nos seus pedidos de indemnização de seguros? Porque é que juntar a análise e a AI, ao ciclo de vida dos pedidos de indemnização, pode proporcionar um ROI quantificável.
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O que são alucinações de IA?Separar os factos da ficção gerada pela IA pode ser difícil. Fique a saber como é que os grandes modelos de linguagem conduzem a alucinações de IA – e descubra como usar a GenAI de forma responsável.
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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.
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Data lake and data warehouse – know the differenceIs a data lake just marketing hype, or a new name for a data warehouse? Find out what a data lake is, how it works and when you might need one.
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Shut the front door on insurance application fraud!Fraudsters love the ease of plying their trade over digital channels. Smart insurance companies are using data from those channels (device fingerprint, IP address, geolocation, etc.) coupled with analytics and machine learning to detect insurance application fraud perpetrated by agents, customers and fraud rings.
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O que são chatbots?Os chatbots são uma forma de IA conversacional desenhados para simplificar a interação humana com os computadores. Aprenda mais sobre os chatbots que são utilizados em negócios e como estes podem ser incorporados em aplicações analíticas.
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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.
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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.
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A data scientist’s views on data literacyData literacy is a social imperative – and understanding data and data analysis is critical for being a responsible citizen. Get a data scientist and teacher's perspective on the value of having foundational knowledge so you can more easily tell data facts from data fiction.
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How AI and advanced analytics are impacting the financial services industryTop SAS experts weigh in on topics that keep financial leaders up at night – like real-time payments and digital identity. See how advanced analytics and AI can help.
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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.
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Modern manufacturing's triple play: Digital twins, analytics and IoT IoT-powered digital twins revolutionize manufacturing with real-time data analysis, predictive maintenance & optimized production. Discover their transformational impact.
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Public health infrastructure desperately needs modernizationPublic health agencies must flex to longitudinal health crises and acute emergencies – from natural disasters like hurricanes to events like a pandemic. To be prepared, public health infrastructure must be modernized to support connectivity, real-time data exchanges, analytics and visualization.
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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.
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Know your blind spots in tax fraud preventionTax agencies sometimes miss fraud that's happening right under their noses – despite robust external fraud prevention efforts. Find out where traditional tax fraud prevention and detection efforts fall short, and how analytics can change that.
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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.
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Containing health care costs: Analytics paves the way to payment integrityTo ensure payment integrity, health care organizations must uncover a broad range of fraud, waste and abuse in claims processing. Data-driven analytics – along with rapid evolutions in the use of computer vision, document vision and text analytics – are making it possible.
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Key questions to kick off your data analytics projectsThere’s no single blueprint for starting a data analytics project. Technology expert Phil Simon suggests these 10 questions as a guide.
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