Machine learning

Competitive pressures mean insurers are highly incentivized to automate more processes where they can to meet customer expectations, says KPMG.

Leandro DalleMule takes job as GM of North America for the insurance data platform.

New data quality management practices, data discovery techniques and predictive and prescriptive analytics tools will be among the top trends impacting analytics and business intelligence.

Machine learning adoption has been growing at a rapid pace, and there is no end in sight. Recent forecasts say pilots and implementations, as well as investments, will increase 400 percent by 2021.

Despite the strong and inherently negative narrative around the impact on jobs, the bulk of the impact from the automation of work through AI will result in a 'displacement' of work not a 'replacement' of work.

Representatives of multiline insurers

Leadoff speakers from Digital Insurance's Insurance Analytics & AI conference in New York illustrate an industry operationalizing advanced technology.

Expect to see major changes in how organizations use AI, the rise of new ‘digital workers’ and increased competition for data professionals with AI skills, says Forrester Research.

Rapid deployment of new tool led to use in more than a quarter of claims

Reinsurance company will host startups at Bermuda conference.

While most executives expect AI to have a transformative impact on economic growth and competitiveness, executives may need to temper near-term expectations.

Leaders of the finance organizations want to be leaders in developing data and digital strategy, according to Accenture survey.

For AI in insurance, the conversations have moved beyond the use cases and on to the pragmatic details.

Technologies such as autonomous vehicles, AI, wearables, the Internet of Things, and more have emerged as power players.

One of the most important aspects of data management is ensuring data quality. Without this, capabilities such as machine learning and advanced analytics might yield faulty results.

While several emerging technologies are grabbing plenty of headlines this year, there are many “digital disruptions” that may catch chief information officers off guard.

Data trash engineers, algorithm bias auditors, virtual identity defenders and cyber calamity forecasters are among the jobs that will play critical roles in the new digital workforce.

Many carriers are leveraging some type of artificial intelligence to solve widely variant business problems.

Many insurers are hesitant to invest in AI without proof that these theoretically smart systems will yield real-world returns.

AI-powered assistants will change the customer experience for the better, but first they must achieve a more human level of service, according to panelists.