ANALYTICS INSIGHTS
Transform data into the best decisions
Recent Analytics Insights
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Insurance customer retention in the AI ageInsurance customer retention has shifted with AI. To enable growth, insurance companies must reduce churn, keep policyholders renewing coverage over time, and protect policies in force. Retaining loyalty now requires insurers to lean into new technological capabilities. See what the "96% rule" means, how our customers are breaking free of the customer retention hole, and the role analytics and AI play.
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Quantum AI examplesQuantum AI has seemed theoretical for years. But it’s gaining momentum in real-world applications. Explore quantum AI examples across financial services, insurance, health care and manufacturing to see how problems beyond classical AI’s reach are solved. And learn about hybrid quantum-classical approaches, where quantum systems and classical computing work together, each handling the parts of a problem they solve best.
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4 strategies to change your approach to fraud detectionFraud detection methods must evolve as fraud threats continue to evolve rapidly. See how financial institutions are using analytics and AI to refine their fraud strategies – and discover four ways to improve your organization's risk posture.
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Trustworthy AI: How to move from ambition to ROITrustworthy AI is artificial intelligence technology that is designed, developed and deployed with human-centricity and other core principles in mind. Learn what it means to trust AI in the face of constant, real-world business pressures. And see why treating trustworthy AI as a repeatable operating model provides a long-term business advantage – and financial returns.
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Benefits of cloud services for analytics and AIThe benefits of cloud services include flexibility, efficiency and strategic value. Learn how cloud services and managed cloud work – including how they help organizations move faster, control costs and modernize legacy systems. Dig into their advantages, including core infrastructure components, delivery models and the strategic value of scalability, security and cloud sovereignty.
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Accelerating innovation with smarter AI hardwareAI is now woven into strategic objectives, and the energy efficiency of AI hardware directly affects operational expenses, geographic decisions and ESG commitments. But AI hardware systems in their current form and at their current growth rate are not sustainable. Leaders must begin to recognize hardware choices not as a technical detail but as a key part of their strategy.
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Fraud detection and machine learning: What you need to knowМашинное обучение является важной частью инструментария обнаружения мошенничества. Вот что вам нужно для начала работы.
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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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AI and humanity: Collaborating to solve global problemsЧто происходит, когда искусственный интеллект и люди работают вместе во имя решения глобальных проблем?
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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 technologiesОт машинного обучения до компьютерного зрения. Эти технологии подпитывают всеобщее помешательство на ИИ.
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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.
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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 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.
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Fraud detection and machine learning: What you need to knowМашинное обучение является важной частью инструментария обнаружения мошенничества. Вот что вам нужно для начала работы.
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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.
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Shut the front door on insurance application fraud!Как выявить, что вас обманывают агенты и страхователи, а также распознать первые признаки будущего мошенничества.
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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.
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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.
Analytics: The Basics
- Overview
- Big Data Analytics
- Data Mining
- Predictive Analytics
- Statistical Analysis
- Blockchain
- Neural Networks
- Data Science
- Algorithm
- Data Scientists
Analytics
If you're reading this, you probably know at least a little – maybe even a lot – about analytics. According to Wikipedia, analytics is "the discovery and communication of meaningful patterns in data." Seems obvious, right? Where the real story with analytics lies, however, is in what you can do with it. Think in terms of possibilities. Opportunities. Discoveries. Made possible by technological advancements in analytics that were never even dreamed of not so very long ago, within your lifetime. So let's explore the topic of analytics together. We'll share insights from the brightest minds in analytics – insights that you can turn into ... well, it's up to you.
Big Data Analytics
As data floods your organization on a daily basis, the question is no longer "What is big data?" Instead, it's "What can we do with the big data we have?" The answer, of course, is integral to the future of your business. And big data analytics opens up the world of the possible. With big data analytics, you can implement data mining, predictive analytics, text mining, forecasting and optimization to explore your options and make the best possible business decisions.
Data Mining
Have you heard the one about the retailer that discovered diapers and beer are often purchased together? What about the telco that can predict your likelihood to switch carriers based on how many of your friends have already switched? These businesses used data mining to uncover completely unexpected insights in their data. What secrets are hiding in your ever-growing data stores? Find out with data mining.
Predictive Analytics
So you’ve embraced the power of collecting and analyzing data. That’s a great first step, but it just scratches the surface. To get the most out of your data, you need to anticipate the future, not just analyze the past.
Whether you want to attract new customers, assess payment risk, identify fraud or forecast energy demand, predictive analytics can provide answers to your most complex questions.
Statistical Analysis
Statistical analysis isn’t just for sports geeks and political pollsters. Every day, statistics plays a critical role in informing public policy and improving human welfare. The field of statistics has grown from sampling populations to analyzing even the biggest of big data sources.
Today’s statisticians are tracking endangered species, improving agricultural processes and predicting the best treatments for complex diseases. There's a lot going on with this influential field and the statistical programming techniques used by today’s statisticians.
Blockchain
What can you store in blockchain besides Bitcoin transactions? Insurance claims, medical records and even voting records can all be stored in blockchain. Simply put, blockchain is a distributed data architecture that stores data and transactions – and validates the accuracy of those transactions by consensus. Learn more about blockchain and how you can analyze blockchain data.
Neural Networks
Neural networks are computer programs designed to imitate how the human brain learns and searches for patterns. Often referred to as artificial neural networks (ANNs), they are ideally suited to solving real-world problems in different fields. Much like a human brain, they can be trained over time to improve their interpretations of data.
Data Science
Data science remains one of the hottest fields in analytics. It’s also the hardest to staff and define. We explain it here with examples, use cases and plenty of data science resources.
Algorithm
If you watched a movie recommended to you, searched for a recipe or talked directly to your phone today, you interacted with an algorithm. How do algorithms work and how pervasive are they? We have the answers to those questions and more.
Data Scientists
Explore the transformative role of data scientists in today's digital era. Understand their skills, the evolution of their profession, and the impact they bring to modern businesses.
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