Insurance


How machine learning will change the insurance industry

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Looking for patterns in large volumes of data is hardly new for insurance companies. In fact, big data is almost the foundation upon which the insurance industry is built. It's how decisions are made and policies are determined.


USAA Rolls Out Innovative Conversational AI Solution

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Going beyond traditional rules-based voice or chatbot digital banking solutions, a non-bot, natural language banking experience is being offered to USAA members in an Amazon Alexa pilot with Clinc. The intelligent personal assistant uses sophisticated natural language processing engines that have been trained with a deeper knowledge of the financial and banking industry as opposed to using a rules-based approach. In a display of market need and institutional confidence, USAA has partnered with Clinc, integrating Clinc's artificial intelligence platform with the existing Alexa skills at USAA. Several other organizations are testing conversational AI for banking services, most notably Bank of America with their Erica solution.


Machine Learning in Insurance: Nature Abhors a Straight Line...What About Actuaries? - DataRobot

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Colin Priest is a Fellow of the Institute of Actuaries of Australia and has worked in a wide range of actuarial and insurance roles, including Appointed Actuary, pricing, reserving, risk management, product design, underwriting, reinsurance, relationship management, and marketing. Photo: "Chiswick Gardens" designed by William Kent Source: Patche99z – Own work, CC BY-SA 3.0 The generalized linear models (GLMs) that actuaries commonly use were first developed back in the 1970s, a time when computers were not powerful and data was small. But even though my 2017 computer can fit a GLM in seconds, that doesn't mean that building pricing models with GLMs is a quick process taking mere seconds of my time. Modern machine learning algorithms are designed for modern, powerful computers and bigger data.


The data don't lie: Using machine learning to fight insurance fraud

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So, how can insurers effectively analyse data help to combat insurance fraud? In addition, telematics-based solutions are helping insurers reduce fraud and manage risk effectively using big data technologies. Organisations such as Octo Telematics have transformed how insurers assess risk, deliver crash and claim services and detect fraud. The ability to identify high-risk policies early on and spot more valuable business opportunities will save insurers time and money dealing with expensive and complex policies down the line.


How AI Will Transform Insurance Claims - Insurance Thought Leadership

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The fast-growing technology has the potential to disrupt the entire industry and greatly improve the insurance customer experience. Traditionally, insurance companies used blanket methods like cold calling customers, but today's customers expect personalized sales tactics. Instead of spending valuable time and money on the underwriting process, which typically includes invasive questions and surveys about to dictate premiums, artificial intelligence could automate the entire process. However, the combination of a new wave of thinking and newly developed artificial intelligence technology has the potential to completely change the customer experience to provide great service in a way that resonates with modern customers.


Investments in Insurtech Expected to 'Keep Booming' in 2017: KPMG Report

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The range of "disruptive insurtech solutions" introduced last year include some aimed at unbundling insurance offerings, while others aim to provide niche insurance offerings "outside the purview of traditional insurers," the report said. The report noted that traditional insurers also made significant fintech investments in 2016, "both by setting up fintech innovation labs and by investing in fintech companies more directly." Acknowledging that 2016 was a challenging year for fintech investment, the report explained that investors became more cautious after the Brexit vote in the UK, the US presidential election, a perceived slowdown in China and exchange rate fluctuations across the globe. However, enthusiasm for specific fintech areas helped keep overall interest in fintech high, the report said, pointing to insurtech, along with regulatory tech (regtech), artificial intelligence (AI) and data and analytics, which all have a positive outlook for growth in the next 12 months.


Insurers Using Drones To Replace Agents In Claim Processing, Study Says

International Business Times

The push towards automation is largely driven by customers' need for faster and more convenient processing of claims. " In a traditional insurance setup, an adjuster -- a person who assesses insurance claims goes to the field, inspects the insured instrument, whether a vehicle, a property or anything else and prepares an estimate. The use and adoption of new claim processing technology might also help new players compete with large, traditional insurance companies with a slow rate of adoption for automation. Clearly, the industry is moving toward increasing automated claims handling processes driven by technology-enabled solutions that yield benefits for both carriers and customers" the study says.


Applications of Deep Learning

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There is a correlation between unstructured data and text mining as many unstructured data is qualitative free text like loss adjusters' notes, notes in medical claims, underwriters' notes, and critical remarks by claim administration on particular claims and so on. In initial benchmarking tests, Enlitic's Deep Learning tool regularly detected tiny fractures as small as 0.01% of the total x-ray image Enlitic's Deep Learning tool is designed to simultaneously support hundreds of diseases (not just a limited specialization of diseases or one disease) [6]. On the other hand, Firms like Narrative Science and Automated Insights working on text analytics are utilizing Deep Learning to create lively and interactive narrative reports out of data and numbers. For predictive analytics part, the startup MetaMind is working to help financial firms assess chances of selling of stocks by going through corporate financial disclosures [9].


Clinc and USAA Partner on Innovative Conversational AI Solution

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Going beyond traditional rules-based voice or chatbot digital banking solutions, a non-bot, natural language banking experience is being offered to USAA members in an Amazon Alexa pilot with Clinc. The intelligent personal assistant uses sophisticated natural language processing engines that have been trained with a deeper knowledge of the financial and banking industry as opposed to using a rules-based approach. In a display of market need and institutional confidence, USAA has partnered with Clinc, integrating Clinc's artificial intelligence platform with the existing Alexa skills at USAA. Several other organizations are testing conversational AI for banking services, most notably Bank of America with their Erica solution.


Max Life's digital endeavour begins to pay rich dividends

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Until even 18 months ago, the proportion of customers that used digital channels to buy insurance from Max Life Insurance Co. Ltd was less than 5%. When the agent meets the prospective client, the conversation can start from retirement plans, since that is what the client looked up online and for which the agent "already has the context". Nangia acknowledges the role of digital competitors such as PolicyBazaar.com in "doing a good job as aggregators," but adds that there is ample scope in the market for companies with different business models and customer segments for tapping into the insurance sector. The younger generation, especially millennials, are agreeing to share a lot of their data online, which is opening up newer possibilities in insurance, according to Nangia.