Implementing deep learning requires a creative approach


Implementing deep learning in enterprise settings requires a lot more than just downloading some open source algorithms, but with talent scarce, businesses are finding it takes creativity and an open-minded approach to achieve results. "Established industries are largely missing out on the benefits of AI," said Ryan Kottenstette, co-founder and CEO of Silicon Valley geospatial data company Cape Analytics LLC. "If you're not in the tech sector, you might be waiting a bit longer for the benefits of AI to be realized." In recent years, deep learning has taken huge strides. Algorithmic processes like neural networks, which historically lived more in the realm of mathematical theory, have moved into some enterprise use cases, like computer vision and process automation.

Humans start to put financial robots in their place


Regulators are beginning to teach robots who's the boss. After spending billions of dollars on cutting-edge artificial intelligence technologies, Europe's banks and insurers face tougher scrutiny of the tools they use to help root out fraud, check borrowers' creditworthiness and automate claims decisions. European Union General Data Protection Regulation (GDPR) rules starting this week will stress human oversight and consumer protection, which may hamper companies trying to build the tools of the future. "Companies developing AI technologies will have to consider and embed the data protection issues into the design process," said David Martin, senior legal officer at Brussels-based consumer advocate Beuc. "It's not something where they can just tick a box at the end."

Insurance drones, boots on the ground, and big data


Drones are often touted as being the answer to a great number of modern day challenges. Soon, we are told, they will be making shopping deliveries for us, dropping off pizzas, and even taxiing us around. A similar expectation about drone capability has been seen in the world of insurance. It was thought that insurers would have large drone divisions, allowing them to easily assess large or hazardous properties, or make claims assessments on otherwise difficult to view property. But this has not happened for a few reasons.

The Road Ahead for Autonomous Cars and Auto Insurance


The death of a pedestrian who was struck by an autonomous vehicle in Tempe, Arizona, has brought fresh scrutiny to the accelerating development of self-driving cars. The accident on March 18 is bound to be studied exhaustively, both to determine fault and to assess and refine the overall safety of autonomous systems. According to accounts of the accident, the vehicle, outfitted to test Uber's autonomous driving system, struck a woman at night as she pushed her bicycle across a road outside of a designated crosswalk. Video of the crash, released by Tempe police, shows a woman emerging from a darkened area seconds before she was struck; in the same span of time, the safety driver looks down multiple times for reasons that aren't clear. Uber pledged its full cooperation in the unfolding investigation but has already reached a settlement with some of the victim's family members, while others have come forward, according to multiple news reports.

Business News: Vlocity, Weather Analytics, Chubb


Vlocity, Inc., a cloud software company, announced the launch of automated claims features in their apps. The launch includes end-to-end management of property and casualty (P&C) insurance claims for policyholders, agents and claims handlers, and enables dynamic, digital claims interactions from any device. New features include peril-driven adjudication and an adjuster workbench that enhance a carrier's ability to run their entire business on Salesforce. Carriers can download pre-configured claims processes from Vlocity's Insurance Process Library and leverage a modern, optimized user experience. Carriers, if they prefer, can create a completely new experience from scratch in a code-free environment using Vlocity's intuitive design interface.

China Car Owners Use AI-Powered App to File Damage Claims


Assessing damage caused to their rides has just gotten a lot easier for car owners in China, with the rollout of a video-based, artificial-intelligence app from Ant Financial. The Alibaba affiliate last week launched version 2.0 of its Dingsunbao (Loss Assessment Master) app, giving drivers the same power in their hands to provide detailed car-damage information to insurers and claim vehicle insurance in real time as Ant Financial gave professional insurance adjusters just under a year ago. The first version of Dingsunbao has already helped insurers, including China Taiping, China Continent Insurance, Sunshine Insurance Group and AXA Tianping process claims tens of millions of times at a rate of speed much faster than human adjusters alone could handle. "Dingsunbao has already helped the insurance industry to save over RMB 1 billion on claims handling, while saving claims adjusters around 750,000 hours of effort," said Yin Ming, president of Ant Financial's Insurance Business Unit. The AI also ensures a high degree of accuracy in damage assessment, Ant Financial said when it launched Dingsunbao last June.

Realizing the full value of AI in Insurance Accenture


The future of artificial intelligence (AI) in the insurance workplace is not one of efficiency versus jobs. As our Future Workforce Insurance Survey shows, AI will enable collaboration between technology and employees. Insurers will achieve cost savings, but growth will be a much greater benefit--and most executives expect a net gain in employment. Insurance company employees, on the other hand, expect AI to create opportunities for them and to improve their work-life balance. But there's still a disconnect.

Sensing IoT AI Cloud Action Connected Insurance - Insurance Insights


At first glance there is a lot of enthusiasm in the insurance industry towards the Internet of Things (IoT) even if there is some uncertainty about exactly how to embrace the transformation and this new type of customer-centricity. When we look at the smart home for example, most of us think of it as an opportunity for remote control of the home with some risk sensing that insurers can tap into. But there is a deeper impact, about people living in a connected eco-system in the future. There is no sign that this prospect of hyper-connection is going to stop. For insurance companies facing big decisions about where to go next with strategic technology investments, it is a bit like Alice's world in Wonderland.

AI Eats Insurance – Lemonade Stories


When food delivery services talk breathlessly about machine learning, feel free to roll your eyes: it's baked salmon they're dropping off, not Bayesian statistics. Insurance is another kettle of fish altogether. The birth of statistics is usually dated to 1662, when John Graunt calculated the probabilities of Londoners surviving to a given age. Lloyds of London started shortly thereafter, and advances in statistics and insurance have been inseparable ever since. Insurers, of course, have machines too, but the machine's'secret power' is its ability to extract prophetic insights from inhuman quantities of data.

How Insurer Execs, Workers View Artificial Intelligence and Future Work


Insurers can seize major growth opportunities by redesigning work, bringing in new talent, and pivoting their existing workforces to work with artificial intelligence (AI), according to a new repot by Accenture. The report, Future Workforce Survey – Insurance: Realizing the Full Value of AI, maintains that insurers that invest in AI and human-machine collaboration at the same rate as top-performing businesses could, over the next five years, boost their revenue 17 percent and their employment 7 percent, on average. According to the report – based on two surveys, one of 100 senior insurance executives and another of more than 900 non-executive insurance workers in 11 countries– the insurance workforce needs to be trained to collaborate effectively with AI. For instance, the executives surveyed believe that only one in four of their workers are ready to work with AI, and more than four in 10 (43 percent) cite a growing skills gap as the top factor influencing their workforce strategy. A majority (61 percent) of the executives surveyed expect that the workforce of the future will be a blend of humans and machines.