The insurance industry needs to understand the demands of its future customers if it is to satisfy their expectations. EXL's head of UK and Europe and SVP Insurance, Nigel Edwards explains how smarter insurers will adopt personalisation and a frictionless purchasing and servicing experience to win out UK insurers are all aware that they need to prepare for the future, taking a digital-centric approach and meeting shifting customer demands. However, less than less than 25% of insurers feel well prepared to meet the needs of future insurance customers in 2030. To prepare for this future, insurance companies must first know what the industry will look like in the coming years. That's why EXL and Post conducted a joint survey into how insurance leaders believe the business will change by 2030, and how companies can begin adjusting to that future reality today.

Insurance industry has seen various up and downs in last decade, owning to a series of political and industry wide occurrences. Insurance has become one of the most challenging businesses over years and lot of insurers are venturing into newer products and line of areas. This is where the need of reinsurer has gained prominence recently. Munich Re Group or Munich Reinsurance Company is a reinsurance company based in Munich, Germany. It is one of the world's leading reinsurers.

Unlocking the business value from big data is probably the biggest challenge any company working on an analytics implementation can face. For any insurance industry player intent on designing products fit for the future, and fit for a diverse and ethically-driven organisation, there's a need to consider the ethical component being built into algorithms and scores. The financial regulator the FCA has published its vision for the use of AI and big data in insurance, and some important next steps. It has said the sophistication of AI has great potential for social good, and for solving many of the problems it faces from a supervisory perspective. There's already been some notable successes, for example in supervising large populations of small brokers and other firms, effectively being able to see the "wood from the trees".

In 2017, we're already seeing a growing list of insurers leverage artificial intelligence (AI) to transform their customer- and distributor-facing channels, including the use of robo-advisors to support customers in their purchasing decisions. In some cases, insurers are choosing to partner with emerging players like Motif or Betterment, and in others, they are developing their own capabilities. Consider the Allstate Business Insurance Expert (ABIe)--known as Abby. This virtual assistant with an on-screen personality helps agents quote and issue commercial insurance products. It finds answers through a combination of contextual knowledge and intelligent content.

Frustrated with automated answering machines before you finally get to speak with a customer service representative? When it comes to insurance, you'll just as likely end up dealing with a robot as a human within three years, according to a survey by Accenture Plc. About two-thirds of insurers already use artificial intelligence-based "virtual assistants," the consulting firm said in the report, which was published on Wednesday. Of the executives who took part in the survey, 85 percent said they plan to invest "significantly" in AI in the next three years. "It's coming pretty quickly," John Cusano, global head of Accenture's insurance practice, said in a telephone interview.

The insurance industry is one that is just beginning to tap into the potential of artificial intelligence. If you've been monitoring the ImageNet challenge over the years, you know that AI's image classification surpassed human accuracy about 18 months ago, indicating the technology is reaching a stable and mature state. Once a technology is customer-ready, it's important that it's also customer-centric -- in that it solves an inherent problem. Using AI technology to automate a visual task, such as inspecting damage to a car, is a nearly instant way to provide insurance customers with crucial information about the extent of the damage. Image classification AI within the app compares the customer's photos with thousands of other anonymized crash photos to generate a cost estimate for their repair.