Insure Think

The way insurance companies respond to the COVID-19 crisis is indicative of how the industry will meet the biggest challenges going forward: the disappearing retail customer, over-regulation, shrinking product margins, low customer loyalty and public distrust.

It is critical to assess insurers’ internal operations and the implications for employees.

Catastrophe response is the insurance industry's stated goal. But currently, the sector has few answers for consumers.

It is of strategic importance that we ensure our information technology is supporting the entirety of the organization and its ability to communicate.

The situation is changing rapidly, testing organization capacity and operational planning.

Insurers will use AI across different channels – in context - to deliver experiences that make customers happy.

The future for insurance carriers looks bright when it comes to claims advancements this decade.

The insurtech movement has been underway for the better part of a decade. Now that we have entered the 2020s, it might be worth exploring what could be on the horizon.

Personal lines organizations need to look at their business structures from an outside-in, consumer perspective, as well as traditional inside-out, operational perspective, and then reimagine business units and operational outcomes.

Now more than ever, organizations realize that to manage their unprecedented data growth, a solid data strategy must be front and center for them to survive and thrive.

It is an exciting time for IT. But also an exceptionally unsettled one, as rapid evolution is the norm and change that will shape a business's destiny is coming from all directions.

Data analytics will become more embedded in day-to-day processes specifically to provide analytics and AI insights within the flow of business.

By starting fresh with clean data sets and modern technology, insurers will not only get out of the legacy data quagmire but also set themselves up to take advantage of more cutting-edge technologies.

Looking ahead into the new decade, we will begin to see an acceleration of AI adoption as the lines between data and AI begin to blur.

Attackers are always growing smarter, more creative and more aggressive, and environments are always growing more complex.

We can expect commercial auto premium will grow relatively in an autonomous world, while personal auto premium shrinks.

Insurers see the highest potential in machine learning, robotic process automation (RPA), and technologies to analyze unstructured data.

But many insurers are putting all their investment “eggs” into few baskets and ignoring – or at best shortchanging – other opportunities.

Heading into the New Year, many enterprises are looking at how AI and data analytics can drive their digital transformation journeys.

Even though the threats emerging in the New Year won’t be any less intense, complicated or difficult to manage, 2020 is likely to be the year of simplified security.

Digitizing flood insurance has the ability to automate claims, add consistency to regulatory compliance and assist with fraud control.

Here’s a look at two use-cases for AI in health insurance that are starting to make headway.

Insurance is not immune to the fundamental changes in the way we live, work, and communicate.

It’s critical to help ensure that business strategy and objectives are aligned with the downstream modernization initiative and that both business and IT stakeholders are involved early in the process.

Many insurers are reconsidering outdated product-driven business models and turning their focus to improving the customer experience.

Data quality and customer-centricity are crucial to getting value from initiatives.

Instead of overloading customers up front with a fog of terminology, we are trying to provide just the right information at the right time.

As digitalization accelerates and encompasses an ever-wider share of the insurance value chain, an improvement on the front end alone is not enough.

There’s a scramble going on to match business operations to new and emerging cultural and social expectations. For insurers, meeting these new expectations is about nothing less than the future of the insurance industry.

The traditional way of reaching pools of people – Super Bowl, Oscars, and other TV ads - is out now, and digital is taking over.

Sometimes, in an attempt to gather data or introduce simplicity using a technology solution, businesses and brokers can inadvertently expose themselves to elevated levels of cyber risk.

The global value of insurance premiums underwritten by AI have reached an estimated $1.3 billion this year.

Recognizing and knowing where to find the most common pain points in advance allows the organization to allocate the additional time or resources needed to prevent the whole project from stalling.

A well-defined strategy that focuses on organizational accountability and communication is essential to realizing goals.

In the past, speed was not critical for an insurer’s success. Today, the speed and agility of insurtechs are pushing traditional insurers to move swiftly.

Listening incorrectly to your metrics can sabotage your team in the growth stage.

A year-long pilot in Sacramento will enable members to get free rides to medical appointments, lab and radiology visits and to pharmacies.

Insurtechs are working to help consumers access coverage as risk grows and the National Flood Insurance Program struggles.

Departments of Motor Vehicles across the United States have been selling personal information to thousands of companies, including insurance agencies, towing companies and even private investigators.

Even for those who see the ultimate goal of data integration to be creation of a single customer view, nearly 40% are unsure as to when they’ll achieve it.

The issue here isn’t the source of the data; it’s that somewhere along the way, users’ functional and emotional goals aren’t being met.

The best integration plans contain system level standards, practices and enhancements of continuous improvement, continuous delivery and non-CI /CD system software.

While U.S. tech spending this year is less than the growth in 2017 and 2018, it is still relatively strong. But there are more downside risks than upside potential ahead.

Like bedroom closets crammed full of outdated clothes and unused gifts, legacy core systems in some organizations have become vessels of useless clutter.

In order to be a great data scientist and to land the job you want, you have to think about what your employer is looking for.

More good news is that the development of connected cars is making it easier to find new products and services to offer policyholders.

IT and data leaders are constantly challenged to keep up with new trends in emerging and disruptive technologies, and to determine how each can best aid the organization.

Many customers who bundled indicate lower satisfaction related to the combined experience.

Insurers need to press forward with creating new products that cater to autonomous vehicle owners, including commercial fleets.

Technology infrastructure and carrier cultures need to be adapted to fully realize digital's promise.

Old fears like channel conflict don't have to apply because the audiences for digital and traditional outreach differ.