Thursday, 29 August 2019, 5:03 pm
Article: DLA Piper
By Misha Henaghan
29 August 2019
Digital Transformationhas emerged as a new ‘mega-trend’ where new technologies andprocesses are being used to fundamentally change our way ofworking in insurance. The key features of DigitalTransformation are that it is customer centric (simplifiedand user-friendly) and data driven (mining the power of massdata to gain insights).
Digital transformation isincreasingly being used in the insurance industry tore-engineer existing manual processes, such as applying forinsurance and making a claim. The focus on a customercentric approach boosts the health and wellbeing ofconsumers by enabling insurance to be more tailored toindividuals, providing a more user-friendly process,allowing for more accurate predictive analysis and evenprevention of claims.
Since 2012, Insurtech companieshave been harnessing digital transformation to disrupt theinsurance market. The first five years of the InsurTechindustry from 2012 until 2017 saw more than NZ$8billion ofinvestment. Examples of the use of Insurtech include:
1. Parametric insurance using blockchain. This is wherecover is triggered by a parameter and a pre-agreed paymentis guaranteed upon the occurrence of a triggering event. Forexample, travel insurance for flight delays. The payment ofa fixed amount is automatically paid to the customer’s bankaccount when the flight is delayed and there is no need forhuman interaction.
2. Chatbots as customer service usingartificial intelligence (AI). Virtual assistants thatprovide immediate replies are pre-trained based on commonquestions, giving consumers faster speed of reply, support24/7 and greater quality control of service. As AI continuesto advance and more consumers interact with chatbots, thedata generated will continue to “train” the chatbotassistants and broaden their learning and capacity.
3. Internet of things (IoT) for claims prevention andclaims assessment. An example of HealthTech merging withinsurance is a stomach insert being created that would talkto your doctor’s health records and alert the doctor (andpotentially your health insurer) prior to the onset of thehealth issue.
4. Autonomous vehicles are expected toreduce car crashes by alleviating human errors, whichsignificantly lowers car insurance premiums. Autonomousvehicles can also automatically notify insurers of lossesand send evidence of losses following accidents, therebyminimising or removing the need for human assessment.
Theother significance of InsurTech is using AI to use the largeamounts of data held by insurers, based on the long claimshistory and large customer base. Big Data enables accuratepremium calculation to individualise insurance products (bycharging lower risks less premium and higher risks higherpremium) and it can also predict trends, assist withcustomer service and fraud detection.
Predictive dataanalysis can predict the driving style of an insured seekingmotor vehicle insurance by the way they fill out theinsurance application form. If they are hesitant with theform, they are more likely to be an indecisive driver. Ifthey change their mind on the form it may suggest they aremore 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 ofpersonal data and usage by powerful monopolies. The 2018Facebook-Cambridge Analytica scandal revealed that millionsof peoples’ data had been accessed and used in pro-Trumpadvertising for the US elections. The exposure led FacebookCEO Mark Zuckerberg to publicly apologise for the breach ofprivate data and the introduction of new privacy tools onFacebook. This highlights the importance being placed onindividuals’ rights in respect of their data usage aroundthe globe. We have seen the introduction of the EuropeanUnion General Data Protection Regulation (GDPR) on 25 May2018 which is said to revolutionise the data protectionregime and significantly affect how organisations worldwidecollect, use, manage, protect and share personal data thatcomes into their possession. The sanctions are up to €20million or 4% of a group’s annual worldwide turnover,whichever is higher. The proper use and storage of personaldata needs to be taken into account when harnessing bigdata. It is also important to minimise data bias – while thetechnology is intended to avoid human bias, bias can creepinto the data collected and as well during the coding stage.
The other issue to consider with the development of thistechnology is liability issues. Who is liable when it allgoes wrong? Is it the software developer? Can a machine orrobot be a legal personality capable of liability? The UKLaw Commission is considering these issues as advancedtechnology develops faster than the pace of the law.
Itis predicted that by 2035, AI has the potential to increaseNew Zealand’s GDP by NZ$54 billion. While there are hugefinancial and social wellbeing advantages to the developmentof this technology, we need to be keenly aware of theethnical, legal and moral issues with its development. Weoften look at the past to shape how we do things in thefuture, yet with new innovations in technology there isoften no precedent to benchmark against. Nor should we bemerely reactive to new claims coming in. To achieve the mostequitable outcome in the future, we need to be aware oftechnological and industry developments and ensureindividual rights are balanced at each step. As they say,prepare “to shape, or be shaped” .
© Scoop Media
Scoop Citizen Members and ScoopPro Organisations are the lifeblood of Scoop.
20 years of independent publishing is a milestone, but your support is essential to keep Scoop thriving. We are building on our offering with new In-depth Engaged Journalism platform – thedig.nz.
Find out more and join us:
Scoop Citizen MembershipScoopPro for Organisations