David King: Using AI for algorithmic underwriting

On this episode, Sabine VdL interviews David King, Co-Founder and Chief Commercial Officer of fast-growing InsurTech startup, Artificial Labs or Artificial.io to discuss the company's strengths and how sport influences David's choices and business outlook.

 

KEY TAKEAWAYS

• Artificial is very much focused on facilitating algorithmic underwriting within the insurance sector. That means that the Artificial team works with brokers and underwriters to get the data into the right format so that it can be shared between the two and, once it’s been shared... define what the process, pipeline and fundamentals should be to improve decision making and customer experiences and interactions.  
• Insurance is an industry where data AND relationships are really important. We use technology (and algorithms) to help automate the decision making process. The number of variables that a human can take into account in order to make a decision is between 5-7 variables. If you keep on adding more to the decision-making process, then the accuracy of models and algorithms start to decrease. If a business is supported by the right technology, one can make a decision that’s either automated or presented in a detailed and informed assessment of risk. This enables human actors that would make key decisions to make the right commercial risk decisions, even if partly automated. 
• It’s not just about the ability to train a model to assess risks to improve your underwriting performance and make it efficient, it is also about the ability to operate within ecosystems. Part of our secret sauce is that we have a domain-specific programming language that allows us to codify an underwriter’s appetite and to leverage and integrate with any data source or service in order to make a decision. 
• More data are going to be available in future. It is a fact. Are underwriters going to have to be more sophisticated in the way they make decisions? Definitely. Is the market going to become more efficient and therefore does the operational cost ratio need to be lower? Even more... Yes. I think underwriters will need to work closely with portfolio managers, people with more maths skills – I don’t necessarily think that means machine learning/ data scientist type skills will become closer to the underwriting decisions on a day-to-day basis, but I do think that you may have a multi-disciplinary team that understands where the data is coming from and what’s driving true decisions.

 

BEST MOMENTS

‘I’ve always been quite competitive and love "sport." I like team sports probably because my own abilities are quite poor. If you’re a team player you can leverage the abilities of other people and I look to elite sport to understand what cultures drive performance and how people operate too.’

‘Technology won’t take over and make all the decisions. Still, you’ll have strategies that are set by very data-informed people and you can execute that across a broad spectrum of products, services, and classes.’

‘The models are only as good as the data you provide to them, but the models don’t exist in isolation, they also exist in a business that needs to be operationally efficient.’

‘You now need to operate while understanding that you’re not going to have all the components end-to-end, so you need to be able to play nicely with others. This will lead to greater efficiency that provides greater experiences to customers. This also means you keep them longer and can then sell them more things.’

 

ABOUT THE GUEST

David King has worked in digital media and technology since graduating from Nottingham University Business School with a degree in Industrial Economics in 2005. After spending a gap year as Troop Commander in the British Army, King spent time as a Digital Planner for Carat, where he worked with global brands such as Yahoo!, British Gas and Santander.

King moved on to become Director at Sure Insurance Services in 2009 where his knowledge of the digital space helped to bring innovative insurance products to market in the medical and health insurance sectors. It was here that his understanding of the insurance market grew, setting the stage for his later foray into space with Artificial Labs. 

Following his time at Sure, King set up his own digital services company called Data Stripes in 2011. The company delivered highly polished, data-intensive, digital applications for some of the world's biggest brands. 

In 2013, the success of Data Stripes led King to merge with Johnny Bridges' company ConceptMill, creating Artificial Labs. The company provided high-quality, data-led design to global clients such as BMW, Levi's and Betfair. 

In 2016, Artificial pivoted into the insurance space, building partnerships with firms such as AXIS and Ambris. King's existing industry experience, combined with Bridges' previous work in insurance companies, meant that the company could take advantage of a growing need for high-quality data and digital platforms amongst insurance companies. 

Since 2017, King has been steering the commercial ship at Artificial, helping to develop partnerships with global insurance brands such as Convex, Chaucer, Aon and TMHCC. With years of experience in technological innovation now under its belt, the company is prospering as a provider of algorithmic underwriting technology to the London market and beyond.

Websites: https://www.linkedin.com/in/malarkeyking/ and https://artificial.io/ 

 

ABOUT THE HOST

Sabine is a corporate strategist turned entrepreneur. She is the CEO and Managing Partner of Alchemy Crew, a venture lab that accelerates the curation, validation, & commercialization of new tech business models. Sabine is renowned within the insurance sector for building some of the most renowned tech startup accelerators around the world working with over 30 corporate insurers & accelerating over 100 startup ventures. Sabine is the co-editor of the bestseller The INSURTECH Book, a top 50 Women in Tech, a FinTech and InsurTech Influencer, an investor & multi-award winner. 

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