Improved analysis underpins coverage to smooth the intermittent nature of wind, hydro, and even solar power

There are valuable lessons to be gleaned from approaching cyber risk as you would an active volcano.

Mid-size employers transitioning from fully insured health care plans are intrigued by stop-loss captives.

Site-specific risk assessments do what standard models can’t, benefitting both insurer and insured.

The threat of a catastrophic cyber attack on our infrastructure is real.

Modeling cyber risk accurately is key to avoiding a subset of D&O claims.

How a smart shirt and lifting weights can trump Big Data.

Changing market forces are driving pessimism among independent insurance agencies.

Insurers and brokers are developing unique tools to help insureds stay ahead of global political risks. 

The private insurance market needs to better understand exposure to flooding.

Models analyze variables at intake and afterward to identify claims that may become adverse.

Complex supply chain risks are prime territory for analytics to close coverage gaps, root out weak or risky suppliers, and ensure business continuity.

With the rise of the Internet of Things, wearable tech and “people analytics” could put you out of a job.

More companies are harnessing industry data to cut down claim duration and overall cost.

A combination of technology and data-centric risk management almost guarantees resilient supply chains.

Expanding powers of analytics are fine and good. But without the wisdom of experienced risk managers, they’re not much good at all.

Simply having lots of data gets us nowhere. We need a different approach.

The location of suppliers should be a key consideration in supply chain risk management.

Modeling will make the market, experts at a New York industry event said.

The Texas flooding is a prime opportunity for insurers to learn more about automobile technology’s impact on claims numbers.