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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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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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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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La IA y la humanidad: una colaboración para resolver los grandes retos del mundoLas comunidades desplazadas, la crisis alimentaria mundial y los desastres naturales no solo afectan a la calidad de vida, sino también a la capacidad de supervivencia. ¿Y si la inteligencia artificial fuera el impulso inesperado que la humanidad necesita? ¿Y si pudiera ayudarnos a lograr un cambio positivo y duradero? Descubra la forma en que la IA está contribuyendo a encontrar soluciones a los grandes retos del mundo.
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Cinco tecnologías de IA¿Cuál es la diferencia entre la inteligencia artificial y el aprendizaje automático? ¿Podría explicar los conceptos básicos de tecnologías como la IA generativa (GenAI) y los agentes de IA? Lea nuestra información general para entender estas y otras tecnologías que están detrás del auge de la inteligencia artificial.
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La IA transforma los seguros: ocho ejemplos de su funcionamientoEl uso de IA en seguros puede aumentar el valor para los clientes, las compañías de seguros y las partes interesadas por igual. Los ejemplos van desde una detección de fraude más fuerte y un servicio al cliente mejorado hasta procesos de suscripción optimizados y ventajas competitivas. Descubre más información sobre cómo la IA está transformando la industria.
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¿Qué son los modelos de IA?La modelización de IA implica la creación de programas que utilizan un algoritmo o una combinación de algoritmos para permitir a los ordenadores pensar, aprender y predecir resultados. Al igual que el cerebro humano, los modelos de IA absorben datos de entrada —números, textos, imágenes, vídeo, sonido— para aprender a predecir resultados o resolver tareas específicas sin instrucciones explícitas en cada paso.
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Así funciona la tecnología gemelos digitalesDescubra cómo la tecnología gemelos digitales está transformando sectores como la salud y la fabricación, y cómo puede marcar el futuro del modelado de datos y la optimización de procesos.
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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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Ansiedad frente a la IA: mantener la calma ante el cambioLa ansiedad frente a la IA no es ninguna broma.— Tanto si temes que tu trabajo se quede obsoleto, que la información se distorsione o simplemente perderte algo, comprender la ansiedad que provoca la IA puede ayudarte a vencerla.
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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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Datos sintéticos para impulsar avances de IADescubre por qué los datos sintéticos son vitales para las iniciativas de IA, cómo los utilizan las empresas para desbloquear el crecimiento y cómo pueden ayudar a abordar los retos éticos.
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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.
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¿Qué son las alucinaciones de IA?Separar la realidad de la ficción generada por la IA puede ser difícil. Aprende cómo los grandes modelos lingüísticos pueden fallar y conducir a alucinaciones de IA y descubre cómo utilizar la GenAI de forma responsable.
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¿Qué son los chatbots?Los chatbots son una forma de IA conversacional diseñada para simplificar la interacción humana con las computadoras. Aprende cómo se utilizan los chatbots en las empresas, cómo pueden incorporarse a las aplicaciones analíticas
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Data quality management: What you need to knowData quality isn’t simply good or bad. Data quality management puts quality in context to improve fitness of the data you use for analysis and decision-making.
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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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Intelligent policing: Data visualization helps crack down on crimeLearn how data visualization can give police real-time views of locations enriched with other data to help them make intelligent, fact-based decisions.
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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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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 & IoT IoT-powered digital twins revolutionize manufacturing with real-time data analysis, predictive maintenance and 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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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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Analytics leads to lifesaving cancer therapiesA long-shot treatment offers hope to 10-year-old Harrison after he learns the DNA profile of his cancer is resistant to chemo. Find out how data and analytics play a role in cancer research and cancer treatments that are saving lives.
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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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Are you covering who you think you’re covering? Payers often don't focus enough on healthcare beneficiary fraud in public and private healthcare plans. Before paying a claim, payers need to ensure beneficiaries are eligible. Advanced analytics applied to a broad range of data can help them accurately detect and prevent beneficiary fraud.
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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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