Data architecture

Cybersecurity risk start-up sees biggest risks inside firewalls

High-resolution, high-frequency imagery assists insurers with claims processing, underwriting and post-disaster property inspections.

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.

The fastest growing job roles will be data scientist, machine learning design/development/engineer and data engineer.