AI and advanced data analytics are already making waves in the insurance sector. Insurance Times interviews five industry experts to delve into their perspectives on the significance of this technological transformation for the industry.

Gareth Evans, head of customer success manager, Shift Technology

The adoption of artificial intelligence (AI) and advanced data analytics is already having a profound impact on the insurance industry. 

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Gareth Evans

Meanwhile, it is well known that our industry is facing a skills and talent gap – experienced professionals are leaving the workforce and they’re not being replaced.

However, what we have found is that, when AI is applied to key underwriting and claims processes, you can replicate the expertise of underwriters and claims professionals at scale.

Furthermore, by sharing that knowledge and having AI work in tandem with current employees, you significantly augment their ability to make the best decisions as quickly, accurately and fairly as possible. 

From a business model perspective, we know that the industry continues to face a combined ratio problem. Simply raising premiums is not enough to solve the challenge.

Here, AI allows insurers to inject significant efficiency into key processes, such as fraud detection or underwriting.

Finding more fraud is good for the business. Keeping a clean book of business is good for insurers. Shaving points off the combined ratio and helping drive profitability is definitely good for business.

John Fearn, chief client officer, Gallagher Bassett UK

Data plays a crucial role in every business.

John Fearn

John Fearn

Insurance companies require professionals who can extract valuable insights from data to make well informed decisions.

As a result, there is a growing need for employees who possess the necessary skills to effectively analyse and interpret large amounts of data.

From a business perspective, data analytics allows insurance companies to assess risks more accurately by analysing vast quantities of data.

This process helps identify patterns, trends and correlations that assist in predicting and managing risks. Insurers can develop more precise underwriting and pricing models, which in turn reduces potential losses and improves profitability.

Historically, data analyst roles have been more prevalent in the actuarial and underwriting divisions. The depth and breadth of the data now being captured and made available, means the opportunities for more insightful analysis for actuaries and underwriters has dramatically evolved.

It also means there are heightened opportunities in the claims and risk consulting space to utilise data analysts more effectively, which increase their desirability and creates more competition for this skill set.

It also transforms business models by enabling enhanced risk assessment, personalised offerings, fraud detection and operational efficiency.

While technology empowers professionals to navigate claims efficiently, maintaining the human touch of empathy and communication is crucial in building trust and providing market-leading risk insight and management tools to help businesses succeed.

Nutan Rajguru, head of analytics, Verisk UK

The growing integration of data analytics in the insurance industry has had significant implications for the war for talent and insurer business models.

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Nutan Rajguru

In today’s fiercely competitive job market, data science stands out as one of the most sought-after career paths, drawing in top talent like never before.

As a result, insurance companies are vying to attract and retain skilled data scientists who can leverage analytics to drive innovation and competitive advantage.

Moreover, the prominence of data science underscores the critical role of data in refining insurance business models.

As the demand for data intensifies, regulatory oversight on data usage pose challenges. Nonetheless, access to vast pools of data is indispensable for developing robust models that accurately assess risk and enable personalised services.

Consequently, insurers are increasingly turning to external data sources and advanced analytics to strengthen their data capabilities.

The convergence of talent acquisition challenges and the imperative for sophisticated data driven models underscores the pivotal role of data analytics in shaping the future of the insurance industry.

As companies navigate the complexities of sourcing talent and managing data resources within regulatory frameworks, those adept at leveraging analytics effectively are poised to thrive in an evolving landscape of risk management and customer engagement.

Chris Haggart, chief executive, Hedron Network

More and more firms are seeking the competitive advantage that is on offer by leveraging data effectively.

Chris Haggart GRP Hedron

Chris Haggart

There is an increased reliance on data to drive decision making, personalise client experiences and identify opportunities to streamline business operations.

This surge in demand has fuelled the market for individuals that can analyse data to drive practical utility.

Careers in data analytics, data science and technology are very much en vogue and the growing appetite within insurance provides a fantastic opportunity to attract new talent with fresh perspectives and ideas into the sector.

Meanwhile, strategic adjustments can be made to service models and processes that allow firms to get on the front foot and ensure clients are serviced in the most proactive yet cost effective way possible.

By harnessing data, firms are better equipped to personalise the services they offer, find the best propositions on the market, assess risks and tailor products – even predicting what products a client may need before they ask.

However, the rise of data doesn’t spell the end of traditional service models.

Instead, it represents an opportunity to deliver hyper-personalised experiences that bring relationships to a new and more powerful level.

Paul Hollands, chief data and analytics officer, Axa UK

It’s no secret that the talent shortage in insurance is affecting all areas of the market – and implementing new technologies is one way of tackling the issue.

Paul Hollands

Paul Hollands

Reducing time spent on administrative tasks can improve our appeal in the job market and our business models.

It allows our teams and potential candidates to focus on upskilling in areas that make a difference to their performance and career path.

From a business perspective, greater integration of data allows our teams to better understand our customers’ needs and improve products and services.

For exmaple, at Axa UK, we have launched the data academy to upskill our employees across all divisions of the business, from underwriting and claims, risk and compliance to human resources and finance.

The aim of the academy is to help our colleagues develop a broader understanding of what it means to embrace data and AI as part of their roles.

The academy will also help us develop our existing talent and attract new talent to Axa, with the ability to grow a career within data here.

We are currently exploring how we can leverage data and AI to minimise the time our teams spend on labour intensive activities.

For example, our cyber team is utilising AI tools to analyse vulnerabilities more quickly and on a larger scale to help them identify priorities and provide a better defence strategy against threats.

Mariana Henriques, senior director of product marketing, FintechOS

Insurers have historically been limited in their ability to gather customer data due to the heavily disintermediated nature of the industry.

Mariana Henriques Profile Photo

Mariana Henriques

However, the rise of new technologies such as wearables, IoT, telematics and third-party data providers presents a unique opportunity for insurers to gain a deep understanding of their customers’ behaviour and preferences.

The caveat is only those who can effectively compete for scarce, highly specialised data talent will be able to take full advantage of the opportunity.

The new generation of low-code or no-code insurance platforms can play an important role by levelling the playing field and making it easy for business teams to access, unify and leverage data to personalise pricing and propositions.