Gareth Evans, 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.
Meanwhile, it is well known that our industry is facing a skills and talent shortage: experienced professionals are leaving the workforce and not being replaced.
However, we have found that when AI is applied to key underwriting and claims processes, you can replicate the expertise of underwriters and claims professionals at scale.
Additionally, by sharing this knowledge and having AI work in tandem with current employees, you significantly increase 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 increasing contributions is not enough to solve the problem.
Here, AI allows insurers to inject significant efficiency into key processes, such as fraud detection or underwriting.
Uncovering 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 to increase profitability is definitely good for business.
John Fearn, Client Director, Gallagher Bassett UK
Data plays a crucial role in every business.
Insurance companies need professionals who can extract valuable insights from data to make informed decisions.
As a result, there is a growing need for employees with the skills to effectively analyze and interpret large amounts of data.
From a business perspective, data analytics allows insurance companies to assess risks more accurately by analyzing large amounts of data.
This process helps identify patterns, trends and correlations that facilitate risk prediction and management. Insurers can develop more accurate underwriting and pricing models, reducing potential losses and improving profitability.
Historically, data analyst roles have been more prevalent in actuarial and underwriting divisions. The depth and breadth of data now captured and made available means that the possibilities for deeper analysis for actuaries and underwriters have evolved significantly.
This also means that there are increased opportunities in the claims and risk consulting space to use data analysts more effectively, increasing their attractiveness and creating more competition for this skill set.
It also transforms business models by enabling improved risk assessment, personalized offers, fraud detection and operational efficiency.
While technology allows professionals to effectively manage claims, maintaining a human touch of empathy and communication is crucial to building trust and providing cutting-edge risk management information and tools to help businesses succeed .
Nutan Rajguru, Head of Analytics, Verisk UK
The increasing integration of data analytics in the insurance industry has had significant implications on the war for talent and insurers’ business models.
In today’s extremely competitive job market, data science is emerging as one of the most sought-after career paths, attracting top talent like never before.
As a result, insurance companies are competing to attract and retain skilled data scientists who can leverage analytics to drive innovation and competitive advantage.
Additionally, the importance of data science highlights the critical role of data in refining insurance business models.
As demand for data intensifies, regulatory oversight of data use poses challenges. However, access to large pools of data is essential for developing robust models that accurately assess risks and enable personalized services.
As a result, 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 underscore the central role of data analytics in shaping the future of the insurance industry.
As companies navigate the complexities of sourcing talent and managing data assets within regulatory frameworks, those that know how to effectively leverage analytics are poised to thrive in an evolving risk management landscape and customer engagement.
Chris Haggart, Managing Director, Hedron Network
More and more companies are seeking the competitive advantage that effective data exploitation offers.
We are increasingly relying on data to guide decision-making, personalize the customer experience and identify opportunities to streamline business operations.
This increase in demand has fueled the market for individuals who can analyze data for practical use.
Careers in data analytics, data science and technology are hot and the growing appetite within insurance provides a fantastic opportunity to attract new talent with new perspectives and ideas to the sector .
At the same time, strategic adjustments can be made to service models and processes that allow businesses to be at the forefront and ensure that customers are served in the most proactive and cost-effective way possible.
By leveraging data, businesses are better equipped to personalize the services they offer, find the best deals in the market, assess risks and tailor products – and even predict which products a customer might need before asking for them. .
However, the rise of data does not mean the end of traditional service models.
Instead, it represents an opportunity to deliver hyper-personalized experiences that take relationships to a new, more powerful level.
Paul Hollands, Director of Data and Analytics, Axa UK
It’s no secret: the talent shortage in the insurance industry affects all areas of the market – and implementing new technology is one way to solve this problem.
Reducing the time spent on administrative tasks can improve our attractiveness in the labor market and our economic models.
It allows our teams and potential candidates to focus on development in areas that make the difference in their performance and career path.
From a business perspective, better data integration allows our teams to better understand our customers’ needs and improve products and services.
For example, at Axa UK we launched the Data Academy to upskill our employees across all divisions of the business, from underwriting and claims, risk and compliance to HR and finance.
The aim of the academy is to help our colleagues develop a broader understanding of what it means to integrate data and AI into their roles.
The academy will also help us develop our existing talent and attract new talent to Axa, with the opportunity to develop a career in data here.
We are currently exploring how to leverage data and AI to minimize the time our teams spend on labor-intensive activities.
For example, our cyber team uses AI tools to analyze vulnerabilities faster and at a larger scale to help them identify priorities and provide a better threat defense strategy.
Mariana Henriques, Senior Director of Product Marketing, FintechOS
Insurers have historically been limited in their ability to collect data on their customers due to the highly disintermediated nature of the industry.
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’ behavior and preferences.
The only caveat is that only those who can compete effectively for rare, highly specialized data talent will be able to take full advantage of this opportunity.
The next generation of low-code or no-code insurance platforms can play an important role in leveling the playing field and enabling sales teams to easily access, unify and leverage data to personalize pricing and proposals.
