Insure Think

AI has the potential to make our lives safer and easier, if we train the systems to be inclusive and use them wisely.

Getting an architectural artifact translated into a practical system implementation has always been problematic, but it doesn’t have to be.

The state of ransomware demonstrates that no organization, municipality or person is immune and that the threats are getting worse.

In order to compete in the age of the customer, your data strategy must be top-flight. The vast majority of firms come up short in this regard.

To reap the full benefits of AI, there’s an entirely different type of AI we should be exploring that’s been largely ignored. It’s specialized (or augmented) intelligence systems.

Many organizations start their analytics journey eagerly, but without a clear strategy. This approach often leads to failed pilot projects, which have not provided the needed insights to answer business questions.

Distributed ledger technology can improve the ease of access to various records and reports such as motor vehicle, CLUE, and credit reports; as well as court records.

Here are some changes - attitudinal and operational - that organizations need to undertake today to get the most out of ML and AI in the near future.

Unlike CIOs of old, today’s technology leaders may have to set aside personal and professional opinions, embracing a range of resources, tools, and processes versus one set in stone, universal approach.

Cloud adoption has more than tripled over the last three years for insurance carriers, primarily because it is the true digital facilitator.

The use of drones combined with AI technologies, like computer vision, are allowing many industries to automate or assist with what would have previously been arduous tasks.

Packaging coverages to create more options, simplifying applications, and offering video chat during the claims process are just a few examples of innovation.

Carriers have seen how insurtechs are looking to attack the sector, and are now pivoting their strategies to match.

If we, as an industry, continue to seek only incremental change, we will wake up in three to five years to discover that we have missed out on opportunities to advance.

Two recent articles in highlight the simultaneous offer of promise and peril that AI brings. One article describes the meteoric rise of a start-up; the other the failure of another.

It is possible that carriers and agents could use digital to preserve and expand their customer relationships, doing an end-around on those that would disintermediate them.

Companies are tempted to view transformation as a predominately organizational journey, but they need to think much more holistically in order to achieve success.

Insurers must listen to their customers and deliver on their expectations before someone else does, says Aflac exec.

The insurance world was caught by surprise last October when Google’s Capital G investment arm announced a substantial investment in Applied Systems.

Technologies like telematics and video cameras as well as the data captured by these innovations are being used to address a profitability crisis.

Can the automaker really compete with established insurance companies on managing the risk of its vehicles?

Once a company knows what’s coming their way, and understands their value chain, they make fewer mistakes and take better-informed risks.

Starting with claims gives carriers quick wins on the road to revamping processes across the enterprise.

How can we develop solutions that prioritize both without creating frustrations for the end user? These are questions we must explore in order to promote positive growth and innovation.

Food sellers, like insurers, faced intense competition from Amazon after its acquisition of Whole Foods. Here's how customer experience helped winners emerge.

Machine learning and RPA are among the cognitive computing technologies that will help insurers win in a changing market.

Big data offers ample opportunities, but also increases security concerns because online data is so much more vulnerable to cyber attacks.

It’s not enough for any insurer to know the right data exists in-house, it must be in the right format and accessible at the right time.

As business leaders build a deeper understanding of analytics success, IT leaders must establish the right skills, tools and technologies.

Conversational technologies are becoming attractive supplemental channels for insurers.

This is particularly problematic for insurers selling a significant number of policies though independent agents.

There is little debate that we are in the beginning stages of monumental transformation, and the implications for the insurance industry couldn’t be greater.

Insurtechs have pointed the way toward the type of flexibility in contract lengths customers have begun to demand.

This combination ensures accuracy over time and enables the ability to analyze information and provide it quickly.

The challenge for both consumers and businesses is comparable — and ironic: It’s difficult and often expensive to connect connected systems.

Before you can reliably introduce the ‘cool stuff’ at scale, there are a lot of less cool, but important areas to address.

Consumers report broad concerns about the fairness and acceptability of using computers for decision-making in situations with important, real-world consequences.

Ultimately, a digital strategy must focus on improving business processes and outcomes, like offering new digital products or increasing your customer engagement.

Consolidation and the desire to drive down costs are incentivizing innovation in health insurance between a range of stakeholders.

Once considered the best way to do business, the basic functionality of spreadsheets is now under question as the right tool for the job.

Thanks to explosions in data and analytics capability, carriers have more options than ever to avoid leaning on controversial tactics like credit scores.

Most organizations think of asset management as the practice of tracking and managing IT devices such as routers, switches, laptops and smartphones. But that’s now only part of the picture.

Insurers must decide which business problems they need to address first, which require more data, and how to operationalize models in their core production system.

The point of visualizing data is to engage the user, deliver information faster, and otherwise enable business insight.

Dynamic pricing is an example of an emerging blockchain-enabled innovation that benefits both the insurer and the customer, with broad-ranging potential.

There is no single technology that will redefine IT operations or business strategies. Instead, technologies must be stacked together to produce new and innovative solutions.

The importance given to understanding and preventing bias and unfairness is evident in the mainstream artificial intelligence conferences.

For healthcare payers, the answer depends on more than just saving money—optimizing health should be the basis for adoption.

A new report, as well as several other studies, confirm a frustrating problem: The AI hype is making it impossible to figure out how much businesses really need it and are using it.

With the California mandate to take effect by January 2020 and a potential new U.S. federal privacy law that could supersede it, firms need to start taking stock of their privacy practices.

The visionaries are leveraging the data that sits in the ecosystems around them—and are applying AI on top of the data to turn it into predictive insights.