Data modeling

Consider introducing specific touch points and service level expectations.

The idea is to use advanced analytics to drive innovation and create actionable insights throughout the insurance lifecycle.

Insurers can gain deeper insight into risks.

Alongside extreme weather events, issues like affordability and risk perception contribute to the lack of insurance protection.

Applying AI technology moves slowly, but has potential to produce more sophisticated insights

The conversion process can be fraught with integration complexities.

The predictive model is powered by AI analysis based on data from over 1,500 wildfire losses.

There's a growing collective effort by national regulators, state governments, insurers and banks to address impacts of a warming planet.

Transformational technologies will also be critical in advancing personal lines underwriting, with 81% of insurers saying they are pushing transformation forward.

Digital Insurance spoke with Eric Sellenberg, technical director, Zurich North America.

Underwriting technology company shifts focus to workbench product

Insurance data provider promises steady, time-saving operations.

Cybersecurity risk start-up sees biggest risks inside firewalls

How do you maximize efficiency in the application, quoting, and claims process and not invite new or additional fraudulent activity?

Digital Insurance spoke with Anshuman Prasad, global head of risk analytics at CRISIL, a risk advisory firm.

One example of a typical deep learning application is pattern recognition applied to digital images.

Big data provides an opportunity to instantly know more about a business than ever before.

Current actuarial techniques are good at quantifying in the aggregate – but less so in the detail.

Research shows rapid adoption of predictive algorithms and digital identity technology will stem the pandemic-driven fraud deluge. Insurance fraud causes more than $80 billion in losses annually in the U.S. alone, according to the report.

To understand how the idea of dynamic risk assessment works, we first need to unlearn certain assumptions.