InsurTech is a topic taking the industry by storm. However, there’s’ a lot of confusion concerning what the array of different terms in relation to InsurTech actually mean. Glen Clarke, Head of Transformational Propositions at Allianz explains more:

InsurTech – is simply the application of innovations in technology to any aspect of insurance.

Start-Up – is typically a young but potentially fast-growing business that aims to solve a customer or business problem by developing or offering an innovative product, process or service. The rise in the number of start-ups has been driven by the open source availability of advanced software as well as the emergence of cloud computing solutions meaning it is now viable for a small firm to design technically scalable software at low cost.

Internet of Things (IoT) – is the interconnection of devices over the internet, allowing them to transmit data to is and each other. It is estimated that there are already 15 and 20 billion connected devices worldwide with that number widely expected to grow exponentially. An example of this would be smart alarm, which could detect intrusion, make calls to your smartphone or the emergency services and take pictures and videos. Within insurance, the real-time data collected by IoT could be used to improve and tailor insurance offerings, prevent damage, predict accidents, detect fraud and validate claims.

Big data– a term that refers not only to the increasingly huge volume of data being generated in today’s digital world but also the variety (text, social media, pictures/video, audio as well as traditional structured/descriptive data traditionally found in databases) and velocity of the data which can be generated, accessible and analysed in almost real time. The term also covers not just the data but to some degree the hardware and software required to store and manipulate the data.

Artificial intelligence (AI)– is the overarching term for development of computer systems able to display characterised similar to human intelligence. In recent years, AI has been propelled by the explosion of bug data and cloud computing solutions. Simply speaking,  AI is the ability to build software that learns from experience/historic data and applies this learning to improve future tasks without being recoded. This capability to learn and to interact is being developed through techniques like machine learning and, more recently, deep learning.

Blockchain– refers to the technology now being used to make a secure, traceable and permanent digital record of an event such as a financial transaction or any transaction where there is an exchange of value. In essence it is shared by its users with no central version – this is why it is often called decentralised or distributed ledger.

All users have an up to date version of the database, or blockchain, and all users have to verify any proposed transaction that would change the database – this is done algorithmically. Once any new transaction is verified by the users the transaction is recorded as a new ‘block’ to add to the history of transactions, ‘the chain’, held against the item of value.

This theoretically makes the system incorruptible with the complete history of the transactions available for all to see – a permanent record that cannot be disputed. The most famous application of the technology is underpinning bitcom, the digital currency.