Collaborating Authors

AI, machine learning offer great opportunities and major risks for insurers


But with that promise comes risk – perhaps greater than the risks inherent with all new technologies – that the insurance industry needs to consider. The Financial Stability Board released a detailed report this month on the potential upsides and downsides of AI, most of which align with Novarica's research of the technology. Many of the risks highlighted in the report stem from the increasing reliance financial services companies will have on outside technology companies for key business components. Another source of risk is that the results of AI and machine learning may be too complex for humans to fully understand. As the FSB report puts it, "New trading algorithms based on machine learning may be less predictable than current rule-based applications and may interact in unexpected ways."

Facebook slaps down Admiral's plan to use social media posts to price car insurance premiums


UK insurance firm Admiral had intended to launch an app this week offering discounted car insurance premiums to first time drivers based on an algorithmic assessment of their Facebook posts. All drivers would have had to do is sign in with their Facebook login to grant permission to the company to scan their Facebook posts in order to get a potential discount on their car insurance premiums. However the experiment has fallen foul of Facebook's platform policy, which puts strict limits on how developers on the platform can use the information users share with them. Clause 3.15 of the policy also specifically prohibits use of data obtained from Facebook to In an interview with The Guardian about the opt-in firstcarquote app, project lead Dan Mines described it as "a test", saying: "We are doing our best to build a product that allows young people to identify themselves as safe drivers… This is innovative, it is the first time anyone has done this." The algorithms that Admiral had developed for the app apparently aimed to glean personality traits from users' Facebook posts by analyzing how posts were written -- with individuals who scored well for qualities such as conscientiousness and organization more likely to be offered discounts vs those who came across as overconfident/less well organized, as judged by their Facebook postings.

Predictive analytics power cyber-insurance industry - Raconteur


Dramatic advances in artificial intelligence and machine-learning technologies have accelerated the ability of insurers to predict risk. Algorithms can find trends and patterns that help forecast the probability of a risk situation occurring again. By utilising internal and external data sources, algorithms are selected according to how a specific model fits with the insurer's data. This model is applied to predict or detect the likelihood of an event happening, such as a person needing medical attention abroad for travel insurance or a house flooding for home insurance. Insurance and assistance provider The Collinson Group uses a variety of predictive analytical tools to flash through terabytes of data to find variables, some of which it hadn't considered, to help predict customer risk and purchasing behaviour.

Insurtech and Artificial Intelligence


The rapid development of converging technologies is bringing about fundamental changes to the insurance industry. In the long term, organisations that are slow to embrace these new technologies will struggle to compete and to retain their place in the market. In the insurance sector, the use of technology to innovate or disrupt is known as'insurtech'. This is an elastic term that takes in the use of new technologies by both start-ups and incumbent insurance companies to transform access to and analysis of data, build new products, drive customer engagement and squeeze inefficiencies from the current insurance model. Technologies such as telematics, the internet of things including smart home technologies, aerial imagery and drone technologies are giving insurers new ways to access data while developments in artificial intelligence (AI), machine learning and natural language processing are enabling insurers to process, analyse and gain insights from these large data sources.

How much snooping is too much?

The Independent - Tech

How appropriate is it for insurers, lenders and banks to snoop on their customers? It's an important question after Facebook felt compelled to take action against insurer Admiral last week - banning it from viewing young drivers' Facebook profiles to help set premiums. With their customers' permission the insurer had planned to use their posts and'likes' to help assess how safe they might be as drivers, and award discounts where it deemed them appropriate. For Facebook and many other critics that crossed a line. However, there are already many financial products and insurance offerings that require the provider to delve deep into the personal lives of its clients.