JERSEY CITY, N.J., June 21, 2018 - Verisk (Nasdaq:VRSK), a leading data analytics provider, today announced it has acquired Validus-IVC, a top provider of claims management solutions and developer of the leading subrogation portal in the UK, verify(TM). Validus-IVC has offices in Norwich and Bath, United Kingdom. The integration of Validus-IVC's verify platform with Verisk's industry-leading global claims analytic services will allow customers to take advantage of enhanced analytic and technology tools to help improve and automate the claims settlement process. With the addition of a well-established subrogation platform to its existing claims solution set, Verisk is uniquely positioned to support the UK insurance market at every stage in the life of a claim. "We're pleased to offer our UK customers access to our distinctive cloud-based platform that enables the exchange of claims information in real time and provides automated processing for reduced expenses and greater claims outcome consistency," said Mark Anquillare, chief operating officer of Verisk.
As in so many other industries, disruption is affecting insurance, and machine learning is both the cause of and the cure for that disruption. Industry leaders have seen success result from pairing insurance and machine learning. As these leaders become more adept at extracting value from unstructured and real-time data, they have realized a competitive advantage and profitable growth. Their success exerts pressure on their competitors, who face a choice: lose business or figure out how to use machine learning to their own advantage. Let's consider a real-world example.
As with so many other industries, insurance is being disrupted on a digital level, and data is both the cause and the cure for that disruption. The availability of new data sources has created new opportunities to reduce risk and exposure as well as creating tailored products based on customer profiles. Simultaneously, however, this has caused complexity and the sheer scale of data has overwhelmed many organisations. Insurance firms need to become more adept at extracting value from unstructured and real-time data, as well as utilising it for predictive analytics and machine learning. Once they have a handle on this, the idea of risk within insurance will be transformed and the way brokers, underwriters and claim handlers operate will be changed forever.
The interest in machine learning and the associated appetite to drive business outcomes from such investments continues to build. I've been talking to many insurance organisations over the past 18 months around machine learning and four consistent areas tend to arise as organisations grapple with the application and value of machine learning. As 2017 gets well underway, I thought it prudent to share and gather opinion experiences in the insurance industry and I've also summarized these points of view as part of Louise Matthews' 'Five Minutes with….' video series. First and foremost, machine learning WILL change the way insurers do business. The insurance industry is founded on forecasting future events and estimating the value/impact of those events and has used established predictive modeling practices – especially in claims loss prediction and pricing – for some time now.
Despite dire predictions of an "Automation Apocalypse," it turns out that automation has only obliterated one job in the last 60 years. However, the steady encroachment into the workplace of automation, robotics and cutting edge technologies is all too real. For businesses, the potential boons are obvious: reduced labor and operational costs, reduced turnover and fewer injuries from repetitive tasks, increased overall safety, production speed and quality. Some economists project that current trends will eventually lead to lower prices and increased demand. The potential risks are evolving just as fast as the technology itself, and both insurers and insureds will be hard-pressed to keep up.