A panel of industry experts examine what the latest tech wave means for insurers and how they can keep pace with customers and competitors. This webinar was sponsored by LexisNexis Risk Solutions.
Machine learning is about taking vast amounts of data and making it actionable.
Machine learning can be as varied as the data itself, from text to image analytics to a widening array of sensor based data. The good news is that tools are advancing rapidly, and many are open sourced.
Tools to work with big data are becoming more accessible, but users need to understand what they're doing. That's where learning and experience take analysis to the levels where discovery occurs.
Start with a small project and solid data. Learn and build from there.
The speed of AI and its ability to retrieve information quickly means its a great tool in easing the path for prospective insureds.
Estimates of the transformative power of artificial intelligence and machine learning are running high, likely higher than most organizations' ability to harness the technologies.
Time is often a missing element in data sets. It's helpful to know a certain metric, but it's even more valuable to know how that's changed over time, and the direction of change.
In the ramp-up to utilizing artificial intelligence and machine learning, some make the mistake of assuming that all data is equal, and that all data is equally usable.
Regulators have become increasingly interested in what data organizations collect and retain about individuals, how that data is protected and ultimately whether that data is used appropriately.
Venturing into artificial intelligence and machine learning means bringing in new skills and personnel, but ultimately it may be less costly than many large-scale technology projects.