By Andrew Pollard, Insurance Specialist at SAS UK & Ireland.
Special deals and tailored offers have become the norm, with customers expecting personalised experiences as opposed to standardised policies. Though this adaptation may seem like an easy win, insurance companies need to ensure they’re pricing these appropriately - or risk making a loss.
Dynamic Actuarial Modeling (DAM) is proving a game changer here, simplifying and speeding up the premium creation and maintenance processes, ensuring that they are well-governed, traceable and easily summarised in comprehensive reports.
Powered by artificial intelligence (AI), this technology incorporates new data types, such as low-frequency climate risk data, into its modelling to give a more accurate overview.
How AI helps actuaries enhance their modelling
The insurance industry is experiencing a profound transformation, fueled by technological advancements and evolving revenue models. In this dynamic environment, actuaries must refine every aspect of their operations to stay competitive.
Central to this transformation is pricing - a critical process that directly impacts profitability, market reach, brand integrity, and long-term success. DAM revolutionises pricing by simplifying premium creation and management while ensuring robust governance, traceability, and effortless reporting.
This equips actuaries with advanced modelling tools, including transparent machine learning models that promote clarity and informed decision-making. By offering diverse modelling options and actionable insights, DAM makes even the most intricate pricing challenges manageable, driving innovation and precision.
In an era of data abundance, capturing portfolio complexity and heterogeneity is essential. DAM enables insurers to compute premiums tailored to individual risks, ensuring competitive rates that reflect nuanced realities. Integrating cutting-edge technology into the pricing process allows actuaries to not only enhance operational efficiency but also deliver value-aligned, data-driven decisions that resonate with today’s dynamic market demands.
As the industry continues to evolve, embracing such advanced tools is not merely an option - it is imperative for insurers seeking to thrive in an increasingly competitive and customer-centric world.
The changing environment
The way people navigate their lives has undergone a profound transformation in recent years, largely driven by the digital revolution that has been seen across industries.
For example, new work models have also come into place, meaning flexible working arrangements and remote opportunities are now the norm. Over half of companies report increases in remote employees and nearly three-quarters of departments are expected to include remote roles in the near future.
This has given rise to “portfolio careers,” where individuals blend multiple jobs, freelance gigs, or side hustles, and has significantly reshaped traditional life choices, such as home and car ownership. For many, these once-essential purchases are now viewed as burdensome liabilities. Younger generations increasingly prefer the flexibility of renting, sharing, or using app-based services.
This shift in consumer behaviour has had significant implications for the insurance industry. To remain competitive, insurers must adapt to changing demands with tailored solutions and seamless digital experiences.
Modern customers expect intuitive, user-friendly platforms and a frictionless process across all touchpoints. They also require insurance products that reflect their evolving lifestyles, such as pay-as-you-go auto policies, on-demand professional indemnity coverage, and health insurance that rewards active habits.
Learning from what works
Insurers are facing increasing pressure to deliver competitive, personalised pricing while managing data complexity and cost efficiency. Real-world use of DAM demonstrates how it can simplify data integration, improve data quality, and reduce costs.
Its intuitive, visual modelling interface accelerates data exploration and discovery, enabling insurers to blend traditional methods with advanced machine learning techniques - such as neural networks and gradient boosting.
These can be mastered quickly, enabling teams to perform granular scenario comparisons and analyse large datasets with ease. This empowers insurers to make agile, data-driven pricing decisions tailored to their specific objectives.
To accelerate the deployment of complex premium models and real-time pricing strategies, actuaries benefit from underwriting engines that support advanced decision-making workflows. These systems allow premium models and underwriting policies to move seamlessly from rate books into decision flows, enabling thorough testing without requiring time-consuming re-coding.
By incorporating elements such as comparative market analysis and behavioural data, these tools facilitate the creation of dynamic pricing models and discount strategies that align with evolving market demands and consumer behaviours.
For example, Spanish insurer Caser Seguros has already harnessed DAM, generating results such as refined pricing models and enhanced customer retention.
Looking to the future
As actuaries face increasing pressure to meet evolving customer expectations and navigate a dynamic marketplace, the expanding role of AI in actuarial modeling has never been more crucial.
The modern insurance landscape demands greater agility and precision, and AI-powered tools enable actuaries to develop more accurate and personalised pricing models that reflect the unique needs and behaviours of individual customers.
As the industry continues to embrace these tools, AI will play an integral role in helping actuaries stay ahead of the curve, offering personalised coverage and dynamic pricing models that meet the demands of today’s fast-paced, data-driven world.
Learn more about dynamic actuarial modelling.
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