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The risks and limitations of AI in insurance

IBM Big Data Hub

In my previous post , I described the different capabilities of both discriminative and generative AI, and sketched a world of opportunities where AI changes the way that insurers and insured would interact. The risk of privacy leakage from interaction with AI technologies is a major source of consumer concern and mistrust.

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Machine Learning Transforms Life Insurance Beyond the Actuarial Process

Smart Data Collective

The insurance industry is among those that has found new opportunities to take advantage of machine learning technology. Life insurance companies in particular are discovering the wondrous opportunities that AI provides, since this sector faces some unique challenges relative to other insurance offerings.

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Examples of IBM assisting insurance companies in implementing generative AI-based solutions  

IBM Big Data Hub

This approach can accelerate speed-to-market by providing enhanced capabilities for developing innovative products and services, facilitating business growth and improving the overall customer experience in their interactions with the company. Customer engagement Providing insurance coverage involves working with numerous documents.

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How insurers can better deliver at “The Moment of Truth”

Cloudera

Insurance is no different. Insurance is not something the average consumer thinks about every day but when a life changing event happens, insurance becomes extremely important. It is in this “Moment of Truth” that insurers excel or fail. To provide the best price, the insurer needs to better understand their customer.

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Using Technology to Reduce Operating Costs in Insurance

Decision Management Solutions

In February, we published a blog post on “Using Technology to Add Value in Insurance”. That post, referenced Matt Josefowticz’s article – Technology May be the Answer for Insurers, but What Was the Question? , in which he states that there are only three levers of value in insurance: 1. Sell More , 2. Cost Less to Operate.

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Optimizing Risk and Exposure Management – Roundtable Highlights

Cloudera

For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Attendees included senior risk managers and analytics experts from financial institutions and insurance companies. Now, risk management has become exponentially complicated in multiple dimensions. .

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How AI can boost customer satisfaction, retention, and loyalty in the contact center

CIO Business Intelligence

The contact center is where customers interact with companies through various channels, such as phone, email, chat, or social media. AI can help optimize processes in many different ways, for example: customers’ speech and text into different languages, dialects, or accents.

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