Global law firm identifies new "mega trend" in the insurance sector

It is being used to re-engineer manual processes such as insurance applications and making a claim

Global law firm identifies new "mega trend" in the insurance sector

Technology

By Roxanne Libatique

Digital transformation has emerged as a new “mega trend” in the insurance sector, according to global law firm DLA Piper.

Data driven and customer centric, it is increasingly being used in the insurance sector to re-engineer existing manual processes such as applying for insurance or making a claim.

According to the law firm, focusing on a customer centric approach could boost the health and wellbeing of customers as insurance becomes more tailored to individuals and more user-friendly and allows for more accurate predictive analysis and 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,” DLA Piper said.

Some examples of the use of insurtech include: parametric insurance using blockchain; chatbots as a form of customer service using artificial intelligence (AI); Internet of Things (IoT) for claims prevention and claims assessment; and autonomous vehicles alleviating human errors to reduce car crashes and therefore lowering car insurance premiums.

Another significant element of insurtech is using AI to harvest large amounts of data held by insurers, based on a long claims history and large customer base.

“Big Data enables accurate premium calculation to individualise insurance products and it can also predict trends, assist with customer service and fraud detection,” DLA Piper said.

However, the law firm warned about liability issues and concerns with open access data, including the use of personal data and usage by powerful monopolies.

“The proper use and storage of personal data needs to be taken into account when harnessing big data,” the law firm advised.

“It is also important to minimise data bias - while the technology is intended to avoid human bias, bias can creep into the data collected.”

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