Markerstudy Group CIO Dan Fiehn explains how he deals with the pace of technology innovation while battling the business change backlog

Markerstudy Group CIO Dan Fiehn is leading an ambitious digital transformation at the 16-year-old motor insurance company. The organisation has expanded aggressively in recent years through a series of acquisitions that led the company to grow from 400 employees to 4,000 in under five years. The acquisitions left them with a complex technology estate that was restricting innovation.

Their IT issues are common in the sector. According to Gartner, roughly 60% of insurance systems were implemented on or before 2009, of which 30% were implemented before 1999.

“It’s little wonder that on average 60% or 70% of our IT budgets are spent on keeping the lights on,” Fiehn explained at the IoT Smart Summit in London.

Automation is helping Fiehn turn his Makerstudy into a digital leader in the sector.

Data-driven

The CIO is pushing data-driven practices throughout the organisation and has developed a set of smart devices. It’s still a struggle to keep up with the rate of change.

“We live in truly exciting times,” says Fiehn, a member of the 2017 CIO 100 who joined Markerstudy in 2011.

“Technology is changing financial services and it’s hardly started. Things like automation, robotics, the Internet of Things, blockchain, 3D printing and machine learning are all having a profound effect on the market, our people, and will introduce unprecedented levels of operational efficiency.”

He was reminded of these changes when he recently came home to find his six-year-old child talking to someone in the back room. It was Siri. His daughter worked out it could give her answers to her maths homework.

Typing information into a search bar will soon seem ridiculous to his daughter, let alone her father’s former need to go to the library for information.

The time it takes different technologies to attract 50 million customers provides a vivid illustration of the growing rate of change. It was 75 years before the telephone reached the milestone, but fewer than four for Facebook. More recently, Pokémon Go got there just 19 days. In one weekend alone the AR game attracted 100 million new customers.

Customer experience and social media

Consumers now expect exceptional customer experience and ubiquitous connectivity.

“We’ve become obsessed with connected devices,” says Fiehn, whose own conduct serves as evidence. “Even at the most bizarre of times, digital has changed my behaviour.”

After pulling himself out of the water following the swim leg of an Iron Man triathlon, the first thing he did was instinctively check his watch.

Every week he pushes himself on his bike to climb up a hill and up the leaderboard of Strava, a social network for budding athletes.

“The interesting dynamic here is that I’m generating the data, and Strava is selling it back to me, because I believe they can give me more insight and an edge that I otherwise wouldn’t get,” he says.

Facebook sets the standard for smart products based on data such as Strava. The social network giant has more than two billion customers around the world generating hundreds of petabytes of data, which they can analyse in intricate detail to work out behavioural patterns.

Few organisations can compete with Facebook’s resources, but they are nonetheless being pushed to deliver smart solutions.

There is a shortage of talent in advanced coding, new recruits and also senior staff who struggle to keep up with the rate of change.

There also often isn’t the capacity to create these smart products.

“I believe we’re at a really pivotal moment in time and there’s this conflict where on the one hand we’re all used to this ever-increasing pace of technology, but on the other, we’re battling with the business change,” says Fiehn. “Now’s the time to act.”

Changes at Markerstudy

Fiehn is helping Makerstudy act on these developments in a number of ways.

The company created a virtual data map of its IT infrastructure using software developed by Dockland that will act as the foundation on which they can identify future AI projects.

Two years ago, the IT team used the data to predict when the service desk would receive calls. Their internal information was combined with external factors such as weather, and stock market changes to map the correlations that affect the likelihood of calls to the service desk.

The results can help them understand the type of smart systems and services that are needed in the insurance sector.

Markerstudy has partnered up with cutting-edge tech companies to harness the power of their data to develop these products. Their collaborators include Nexthink, which uses machine learning to understand when a member of staff will likely have an issue, and Darktrace, which applies algorithms to network traffic that can spot anomalies and shut them down as soon as they emerge.

Traditional IT department typically moves in an orderly but slow fashion. To make the team at Markerstudy more agile, Fiehn flattened the hierarchy of its structure.

“We consciously have created small freely autonomous teams who move in a different direction,” says Fiehn.

“For this truly to work we’ve had to really push down the decision-making so the teams can make a lot of the decisions themselves to move with the utmost velocity.”

Machine learning and automation

Markerstudy has also partnered with DataRobot to improve the machine learning capabilities that determine its insurance pricing. DataRobot takes all of the algorithms available on the open source market and provides a platform on which they compete against each other.

As data enters the system, the algorithms are displayed on the interface in order of accuracy, allowing Markerstudy to choose the best predictive model for a specific dataset.

“We combine now hundreds of algorithms simultaneously, and the strongest ones are the ones that survive,” says Fiehn.

“The more data that we put through, the better they get. That means that whereas before our pricing teams may have been able to run two or three models a month, we can now literally run hundreds a week, which means that the degree of accuracy has improved a hundred-fold.”

As an experiment, they pitted the machine against the hundreds of years of experience in the human pricing team to discover which could most accurately predict the prices at which insurance policies were sold based on MoneySuperMarket figures.

The machine took a week to process the data and made predictions that were 30% more accurate on average than the pricing team, which spent a month on the task. In a third of the cases, the automated prediction was exactly the same as the real sale price of the insurance.

Markerstudy can now apply this system to prices offered at the point of quote.

The team also used it to calculate their retention rates, by mapping the renewal price of an insurance policy against the occasions when they raised or reduced the price and assessing how this affected the customer’s decision to renew their policy.

“As you’d expect, if the insurance premium goes up, you get less people that renew your policy, and if you drop the price more people keep it,” says Fiehn.

“But what is interesting is we found that actually, it doesn’t matter how much we reduce the price. The retention rate is about the same. So we can use the algorithms to calculate what the renewal sweet spot is, so that we don’t give away more money than we actually need to.”

Dangerous driving

There were 1,792 fatalities and almost 200,000 injuries on the road in 2016, according to the Department for Transport. Markerstudy has produced a digital business called VisionTrack to help reduce these figures.

Markerstudy sourced a high-definition telematics camera from a manufacturer in Korea that contains a SIM card to transmit information about the driver in real-time.

They then partnered with Microsoft to create an IoT platform that connects VisionTrack with all of Markerstudy’s drivers around the world. It can monitor their speeds, provide real-time images, and send text messages to the device that are then automatically converted to audio if they need to talk to the driver. The device also comes with a panic button that the driver can hit if they’re in a situation of distress.

“This has had a profound effect on driver behaviour,” says Fiehn. “The fact that they know we can see what they can see has really moderated their style.”

Markerstudy can also compress the data to reduce the traffic emitted so that they only receive the information that they need. This has kept the cost of ownership down and given the capacity to stream real-time video from the camera.

VisionTrack

The company can use this footage to verify the cause of an accident. For example, one driver claimed to his boss that he had left the handbrake off when he crashed into the back of another car.

Markerstudy reviewed the footage and saw he had stopped off for a bite to eat and the lunch he bought had hit the dashboard, causing the collision, and that his handbrake was still on when he hit the vehicle.

VisionTrack won Markerstudy the Gartner Financial Services Eye on Innovation award for Most Innovative Digital Customer Service or Product. Since then the camera has become much smaller and cheaper. The latest version faces the driver. It can recognise when a driver picks a phone up, yawns or isn’t looking and then send an alert.

It can also assess the proximity between the driver’s car and the vehicle in front to identify tailgating and review the driver’s performance.

“I believe we’re in the middle of a conflict at the moment,” says Fiehn. “On the one hand, we’ve got all this cool tech, and the pace of technology is unstoppable. But on the other hand, we’ve got the creeping normality of business change. I guess the question I have is are you winning that battle or are you losing it?”