ANALYTICS INSIGHTS
Transform data into the best decisions
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Article
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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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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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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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 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.
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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