In addition to the plethora of data that insurers hold in their own systems, the Internet of Things, social media, and insurers' increasingly large ecosystems of partners and suppliers offer a wealth of structured and unstructured information that can be used to drive new business models, greater efficiency, and increased competitiveness. As a result, drivers can reduce their premiums and insurers can reduce risk, a win-win situation. Embedding machine learning intelligence into a cloud platform and applications supports more intelligent business processes. Discover Gartner's key findings and recommendations for insurance executives looking to drive digital transformation.
"Our experience working with insurers suggests that – by using machines instead of humans – insurers could cut their claims processing times down from a number of months to just a matter of minutes. But, when it comes to the advice and advocacy provided by an experienced broker, BizCover Managing Director Michael Gottlieb isn't convinced intermediaries are an endangered species. Suncorp's latest Insurance Insights white paper suggests that the automation of individual consumer products and small business packages is affecting the way that insurance professionals are recruited. However, BizCover's Michael Gottlieb approaches the human resource debate from a different angle, reflecting a more future-focused solution.
Apart from the likes of Google, Facebook, Amazon, and Tesla and their mainly digital business models and obvious applications of AI, a lot of traditional industries are employing intelligent algorithms to augment previously manual approaches. AI gives us means to automate processes, personalize products, communications and care, predict personal and collective developments, discover trends and unusual patterns in the data, and more. It has the potential to impact the insurance industry in numerous areas, such as marketing, customer interaction, claims processing, fraud detection, and underwriting. One use case for the application of AI lies in marketing and customer acquisition.
In the not-too-distant future, insurers will contend with the prospect of insuring driverless cars, operated entirely by AI innovations like sensors that help steer the vehicle. Touted as less accident prone than human-operated vehicles, driverless cars will nevertheless require new underwriting criteria. With so many parties involved in the manufacturing of an autonomous vehicle -- the car maker, various software developers -- insurers must assess risk and price insurance based on the data gathered from AI on the different self-driving car models, not individual drivers.
Apple's discussion focuses on being able to embed these technologies on the device with the Apps rather than perhaps the building of the models and the execution – much less focus on pushing data into the cloud. Insurers going through digital transformations and looking deeply at their analytics are finding they are competing with ever more unlikely companies for talent including rising InsurTech firms as observed in previous blogs. The good news is that basic machine learning capability and training is increasingly available as the democratisation of machine learning continues apace – in fact if you look at Apple's documentation this discusses the ease downloading and converting models and integrating them to Apps rather than the nuances of various training algorithms. The ease with which machine learning and AI can be embedded into simple applications now will only increase adoption and there are small things any insurer can do.
This is a new paradigm for financial institutions," Rob Hetherington, Global Head of Financial Services at SAP. We're going to see banks and insurers experimenting and working with partners to bring together Iot, blockchain, AI and machine learning." In the rush to build cool workspaces sporting major wow-factor technologies, David Dabscheck, Founder & CEO at Giant Innovation, urged the audience not to forget about people. California-based fintech startup Quantiply is using AI, machine learning and the SAP HANA in-memory database and predictive analytics to tackle money laundering, one of the world's toughest problems.
Going beyond traditional banking or insurance needs, financial services now interact directly with customers' personal virtual assistants (regardless of whether it's Samsung's Bixby, Amazon's Alexa, Google's Assistant or Microsoft's Cortana), one that acts as the customer's personal financial advocate. Banks now help consumers track spending patterns and present recommendations to save money or reduce debt, whereas insurers present clients with recommendations for healthier lifestyle or safer driving and travel tips, all embedded seamlessly via personalized interactions with AI-powered virtual assistants. Led by government institutions, the entire ecosystem of financial services now performs digital security authentication and verification on a standardized public registry of digital identity. Having embraced digital payment channels, customers view payment processes as a background activity seamlessly done via mobile devices agnostic to technology platforms whether it's contactless NFC (Apple Pay), wearables, Smart TV or distributed blockchain ledgers.
More than half of today's insurance companies use machine learning for predictive analytics, according to a new report by Earnix, an analytics software provider for the financial services industry. Roughly 200 insurers were surveyed as part of Earnix's global "Machine Learning: Growing, Promising, Challenging" study, and they were prompted to select all business areas applicable to them. In total, 70% deployed the technology for risk modeling, the study found. Industry consensus is machine learning will bring significant change to insurance over the next five years, with 71% of companies believing investments in the technology will increase, Earnix says.
Babies born this year may never need to take a driving lesson as self-driving cars could hit Britain's roads within 15 years, says the boss of a UK insurance company. Technology is developing at such a rate that autonomous vehicles could be available by 2032, meaning "babies born today may never have to take a driving test", Axa UK chief executive Amanda Blanc told the Daily Telegraph. Ms Blanc said that insurers have a key role to play in building a new framework for the driverless future, adding that autonomous vehicles "will not be able to take the roads [without that]". Insurance costs are expected to fall in line with lower accident rates and Ms Blanc admitted that driverless cars would make roads "much safer and increase mobility for vulnerable members of society", as more people will be able to get insurance.
According to the professional services company's "Technology Vision for Insurance 2017" report, insurers face challenges integrating AI into their existing technology, with issues such as data quality, privacy and infrastructure compatibility representing some of the roadblocks. They are looking to empower agents, brokers and employees to enhance the customer experience with automated personalized services, faster claims handling and individual risk-based underwriting processes, Accenture said in a statement. Back at Accenture, John Cusano, senior managing director and global head of the Accenture Insurance practice, said, "The adoption of artificial intelligence is gaining momentum within insurance, with executives pointing to AI's potential to revolutionize the customer experience and empower agents, brokers and employees," summarizing the "Technology Vision for Insurance 2017" report in a media statement. In a statement about the Technology Vision report, Accenture noted that 79 percent of the executives surveyed believe that AI will revolutionize the way insurers gain information from and interact with their customers.