There has been more remote advice, digital servicing and more interactive help with customer journeys, such as co-browsing capability, webchat and multi-channel.

Meanwhile there has been an increase in the use of automation to remove work-arounds.

But how insurers use big data and artificial intelligence to support their claims and underwriting strategies is likely to accelerate as a result of the Covid-19 pandemic.

We have now been living with the virus for many months, but it is still early days to really understand the impact of the coronavirus pandemic on mortality and morbidity, so insurers will be very cautious about how it is approached from an underwriting perspective.  

Ian McKenna, founder of FTRC, says in the context of Covid-19, big data and AI have an enormous role to play in helping medical science better understand the long-term impact of the virus. 

Such data will also significantly inform insurers’ long-term understanding and approach to the condition.

Key points

• Insurers may use AI to improve their underwriting
• Increasing use of AI may destroy the pooled risk concept
• AI could be used to streamline straight-through processing

He says: “Data from both iPipeline and Iress The Exchange show that [protection] quotation volumes fell away sharply in the spring, but have now returned to near previous levels.

“The reality is we just don’t know the long-term impact the illness will have on people. For the foreseeable future more medical evidence is likely to be requested, especially on larger cases, although firms are trying to use visiting nurses and other techniques to make decisions as quickly as possible.”

He adds: “It will have a huge role to play in how insurers and the medical profession understand the impact of Covid-19. 

“Big data makes it possible to see patterns related to demographics, genetics and other illnesses, existing medical conditions and how they impact both the treatment and consequences of illness.”

Underwriting rethink

A report published in July by consultancy McKinsey says Covid-19 lockdowns and ongoing distancing protocols reinforce the need to rethink underwriting. Algorithmic underwriting will increasingly become a prerequisite for staying on the shelf and maintaining current positions in the market.

And with Covid-19 only making today’s life product purchasing experience more difficult, many companies increasingly recognise that underwriting transformation is all the more urgent.

“But this is only the beginning,” the report adds. “Many current efforts to modernise underwriting are only digitally enabling yesterday’s products. Today’s consumers have different preferences and needs than they did several decades ago – yet the content of life insurance policies remain much the same.

“Streamlined underwriting will set the stage for future innovation in the industry. It will enable the improvement of collection techniques, assisted by new technology for gathering and analysing biometric data. 

“Insurance product sales will shift from low engagement, one-time transactions to an ongoing relationship between the customer and the insurance agency; this engagement will be defined by continuous underwriting and a greater focus on health and wellness.”

And increasingly, market segmentation will reach the level of individuals, with a richer understanding of each person in the risk pool. 

Pros and cons

Mr McKenna says although big data and AI have huge potential to transform the way protection products are underwritten, he warns that this can bring both positive and negative consequences. 

He adds: “These techniques will, in time, enable insurers to predict far more accurately which individual customers have a greater propensity to illness and disease. This actually threatens the whole concept of pooled risk on which insurance is based.” 

Even if insurers agree to not use some of this data, people will be able to understand far more accurately their need for protection products. 

If only consumers who have potentially poor health seek cover, premiums could in the long run become unaffordable. 

This is an enormous commercial and moral issue, which insurers and reinsurers are very aware of. 

According to Jon Dean, head of retirement strategy at Altus, AI and machine learning will be used to forecast trends; tracking problems in workflow back to root cause and improve process efficiency – moving AI from a customer focus to an operations focus.

Mr Dean says: “Combined with big data, this will increasingly be used to track and forecast trends. Firms are just starting to do this with vulnerability, identifying potential for customer harm based on large samples, and also for claims analytics, especially fraud detection, and underwriting.

“IBM Watson can already heavily automate the underwriting of risk with potential to minimise human interventions.

“This was already changing with pioneer firms but will accelerate with incremental capabilities of leading cloud services.”

Relationship with providers

Advisers could also see some changes in the way providers interact with them.

The use of AI and big data has already enabled insurers to streamline some application processes. 

However, such changes are easier to implement for direct applications, says Mr McKenna.

“In the advised market you would need to see the development of a new type of portal service which would interact directly with each individual insurer’s underwriting engines. 

“Knowledge being gained by insurers about how to use AI is considered very valuable intellectual property, so I would not expect to see them willing to share this with third-party underwriting engines that make each insurer use a version of their own software.”

In the longer term, AI has enormous potential for mass personalisation of life cover, although Mr McKenna says this could make it far harder to support adviser comparison services as it could present a challenge where each company is providing dozens of different options to clients. 

“There is going to be a real challenge for advisers to be able to cut through any noise and provide clarity to customers,” he adds.

“I expect some companies will increasingly focus on their own distribution leveraging AI, so it will be important to identify which insurers continue to have a real commitment to the adviser market.”

Much of the adviser-customer journey is already done online through portals or by phone and it is predicted the balance will tilt further in favour of digital for a greater percentage of transactions.

Upselling

Mr Dean says big data will be used by businesses to identify upsell opportunities for additional services.

For example, there will be more straight-through processing integration – which helps businesses speed up transaction processing by streamlining data sharing across multiple points in a fully automated manner – with adviser office solutions, with declining numbers accepting paper applications

“This should apply across cover updates, but protection claims is still a sensitive area best fronted by a human face: first notification of claim may be digital for some types of protection and claims validation more automated, but with communications still human-centric,” he adds.

On the investment side, as insured investment books mature, Mr Dean says an increasing proportion will be managed on modern platforms, with a greater degree of self-service and integration with a wider range of “open architecture” assets.

Original Source: Ima Jackson-Obot, Financial Times Advisor