InsurTech 

Digital Transformation has emerged as a new ‘mega-trend’ where new technologies and processes are being used to fundamentally change our way of working in insurance. The key features of Digital Transformation are that it is customer centric (simplified and user-friendly) and data driven (mining the power of mass data to gain insights).

Digital transformation is increasingly being used in the insurance industry to re-engineer existing manual processes, such as applying for insurance and making a claim. The focus on a customer centric approach boosts the health and wellbeing of consumers by enabling insurance to be more tailored to individuals, providing a more user-friendly process, allowing for more accurate predictive analysis and even prevention of claims.

Since 2012, Insurtech companies have been harnessing digital transformation to disrupt the insurance market. The first five years of the InsurTech industry from 2012 until 2017 saw more than NZ$8billion of investment.¹ Examples of the use of Insurtech include:

• Parametric insurance using blockchain. This is where cover is triggered by a parameter and a pre-agreed payment is guaranteed upon the occurrence of a triggering event. For example, travel insurance for flight delays. The payment of a fixed amount is automatically paid to the customer’s bank account when the flight is delayed and there is no need for human interaction.

Since 2012, Insurtech companies have been harnessing digital

transformation to disrupt the insurance market.

• Chatbots as customer service using artificial intelligence (AI). Virtual assistants that provide immediate replies are pre-trained based on common questions, giving consumers faster speed of reply, support 24/7 and greater quality control of service. As AI continues to advance and more consumers interact with chatbots, the data generated will continue to “train” the chatbot assistants and broaden their learning and capacity.

• Internet of things (IoT) for claims prevention and claims assessment. An example of HealthTech merging with insurance is a stomach insert being created that would talk to your doctor’s health records and alert the doctor (and potentially your health insurer) prior to the onset of the health issue.

Autonomous vehicles are expected to reduce car crashes by alleviating

human errors, which will significantly lower car insurance premiums.

• Autonomous vehicles are expected to reduce car crashes by alleviating human errors, which will significantly lower car insurance premiums. Autonomous vehicles could also automatically notify insurers of losses and send evidence of losses following accidents, thereby minimising or removing the need for human assessment.

The other significance of InsurTech is using AI to use the large amounts of data held by insurers, based on the long claims history and large customer base. Big Data enables accurate premium calculation to individualise insurance products (by charging lower risks less premium and higher risks higher premium) and it can also predict trends, assist with customer service and fraud detection. Predictive data analysis can predict the driving style of an insured seeking motor vehicle insurance by the way they fill out the insurance application form. If they are hesitant with the form, they are more likely to be an indecisive driver. If they change their mind on the form it may suggest they are more likely to be dishonest at claims time.

Yet, alongside the benefits created, there are inherent issues. There is concern with open access of data, such as use of personal data and usage by powerful monopolies. The 2018 Facebook-Cambridge Analytica scandal revealed that millions of peoples’ data had been accessed and used in pro-Trump advertising for the US elections. The exposure led Facebook CEO Mark Zuckerberg to publicly apologise for the breach of private data and the introduction of new privacy tools on Facebook. This highlights the importance being placed on individuals’ rights in respect of their data usage around the globe. We have seen the introduction of the European Union General Data Protection Regulation (GDPR) on 25 May 2018 which is said to revolutionise the data protection regime and significantly affect how organisations worldwide collect, use, manage, protect and share personal data that comes into their possession. The sanctions are up to €20 million or 4% of a group’s annual worldwide turnover, whichever is higher. The proper use and storage of personal data needs to be taken into account when harnessing big data. It is also important to minimise data bias - while the technology is intended to avoid human bias, bias can creep into the data collected and as well during the coding stage.

Who is liable when it all goes wrong? Is it the software developer?

Can a machine or robot be a legal personality capable of liability?

The other issue to consider with the development of this technology is liability issues. Who is liable when it all goes wrong? Is it the software developer? Can a machine or robot be a legal personality capable of liability? The UK Law Commission is considering these issues as advanced technology develops faster than the pace of the law.

It is predicted that by 2035, AI has the potential to increase New Zealand’s GDP by NZ$54 billion.² While there are huge financial and social wellbeing advantages to the development of this technology, we need to be keenly aware of the ethnical, legal and moral issues with its development. We often look at the past to shape how we do things in the future, yet with new innovations in technology there is often no precedent to benchmark against. Nor should we be merely reactive to new claims coming in. To achieve the most equitable outcome in the future, we need to be aware of technological and industry developments and ensure individual rights are balanced at each step. As they say, prepare “to shape, or be shaped”³ .