Global Actuarial Modernization Survey 2025

Drawing on insights from over 200 insurers globally, our third survey edition offers a comprehensive perspective on the current actuarial modernization landscape, highlighting key priorities, progress, and emerging trends across the insurance industry worldwide.

Overview

The insurance industry has achieved several important milestones in its adoption of new accounting standards. Yet, the modernization journey is far from complete. Insurers continue to navigate an increasingly complex environment characterized by growing volumes of data, heightened uncertainty, multiple reporting frameworks, and evolving capital regimes and rapidly changing technology solutions. 

Actuarial processes and people are an integral part of the insurance company’s value chain.  As technology and regulation continue to evolve, actuarial transformation must keep pace, ensuring that tools, methodologies, and skillsets remain fit for purpose. Modernizing actuarial capabilities is essential for insurers to achieve their strategic goals, both in the near term and over the long horizon. 

Key Themes

Question: What is at the top of your mind for actuarial modernization?

The word cloud above highlights the themes most frequently cited by survey respondents when thinking about modernization. As expected, process efficiency, data quality, GenAI, and automation stand out as dominant priorities. What's more surprising however, is the comparatively limited focus on cultural change and talent areas we believe to be fundamental to sustained transformation. In our experience, the single greatest barrier to meaningful progress on modernization efforts over the past 7 years has not been technology itself, but rather the persistent challenges around resourcing capability building, and upskilling.

Impetus for modernization

The top drivers of actuarial modernization remain largely consistent with our last survey: process efficiency and quality, improved management insights, and regulatory changes. However, this year’s results reveal a sharper focus on process efficiency as the primary catalyst for transformation which is not surprising as companies shift from a focus on adoption to now driving down cost.

Following the implementation of LDTI and IFRS 17, it’s not surprising to see regulatory change decline as a motivator, from 77% in the prior survey to 54% today. That said, regulatory changes such as US Stat PBR, Bermuda CP2 and ICS will continue to drive future modernization efforts.

Beyond these core drivers, insurers also highlight increasing attention to strengthening analytical capabilities, enhancing governance, managing cost pressures, and building more resilient teams. Companies are also prioritizing better data foundations to support analytics and automation.  

Question: What is the main impetus for the actuarial modernization initiatives in your company? 

Achieving efficiency through automation

Survey participants were nearly unanimous (94%) in choosing efficiency as the main driver for their modernization initiatives, up from 77% in the last survey. While it’s no surprise that efficiency remains a central focus, the paths companies take to achieve it vary widely.

Despite this strong emphasis, progress in automation appears to have stalled. Survey results suggest that companies have made only modest gains in expanding automation since last polled. While areas such as data sourcing, model execution, and results consolidation show relatively higher levels of automation, the average self-assessed maturity score remains just 2.5 out of 5. This is not surprising given the scope and scale of many of the automation programs. The low maturity score combined with new Agentic tools underscores a significant opportunity to achieve efficiencies across the actuarial value chain.

Effective data management

Although data is the life blood of insurance, less than half of responding companies have consistent, normalized and automated data environments. As a result, actuaries continue to spend more than half of their time on data preparation, which is far from the ideal of allocating less than 25% of their time to such tasks, and more on high-value analysis.

Evidence-based decision making and regulatory requirements are increasing the volume of data that must be managed.  This underscores the urgent need to equip actuarial teams with curated, high-quality data and robust downstream capabilities such as visualization and advanced analytics. However, key data enablers for actuarial effectiveness remain underdeveloped at many organizations. These include a single source of truth, standardized and granular datasets, reliable ETL (extract, transform, load) processes, and fully automated workflows, all of which are essential to unlock scale and efficiency.

GenAI implementation on the rise

The disruption and potential of GenAI is immense. While some use cases are already in production and many more are still emerging, it’s clear that both the technology landscape and the broader business environment will continue to evolve rapidly as we have seen with Agentic AI. Across industries, we are seeing businesses shifting to the “how”; how to create measurable value from the many potential use cases, how to keep up with emerging technologies, and how to deliver responsible solutions. Our survey results indicate that many insurance companies are keeping up with that trend by beginning to define GenAI governance frameworks and actively exploring business-relevant use cases that add value.

Among use cases explored, GenAI is already showing early impact in actuarial modeling, particularly in accelerating model development and streamlining documentation processes. There are also some benefits observed in areas such as productivity, documentation, data extraction, and reporting. At PwC, we’ve seen promising applications of GenAI in real-world use cases like policy and reinsurance contract analysis, underwriting, model validation, and other agentic workflow accelerators, highlighting its potential to drive tangible business value.

Question: In your actuarial function, which tasks are currently performed using GenAI? 

Modeling ecosystem and cost navigation

As modeling capabilities grow and regulatory requirements continue to increase in the form of detailed disclosures, so does the need for greater computational runtime.  This rising demand is translating into higher cloud-related expenses. In fact, cloud usage costs are now outpacing traditional hardware and software licensing fees, with many large and mid-sized companies reporting that cloud spend rivals or exceeds their licensing costs.

Smaller insurers, on the other hand, have been more effective at managing cloud-related expenses. Their lower modeling volumes and continued reliance on local desktops or on-premise grids, which are used by 70% of respondents in this group, help keep costs down. In contrast, fewer than half of large-company respondents reported using on-premise infrastructure. Across the board, vendor-hosted cloud environments remain the most common setup for executing actuarial model runs.

Question: What is the current state of your actuarial modeling ecosystem?  

Modernization success factors

Actuarial modernization is an integral part of achieving many essential goals of the actuarial function. Through our experiences and learnings with modernization projects, we observed the following success factors:

Empowered teams

Establish strong executive sponsor with visible senior leadership to drive effort. Develop clear governance to drive accountability and decision making.

Clear vision and measurable outcomes

Over-communicate the transformation objectives, goals, and benefits. Put mechanisms in place to measure outcomes, not just activities.

Cross-functional collaboration

Operate cross-functionally, involve Finance, Actuarial, IT in defining objectives and developing squads that drive cohesive execution.

Build momentum with quick wins

Create a sense of urgency, with regular milestones to measure project progress. Continuously show progress by pursuing quick wins, utilizing MVPs, and breaking the work down into tangible components.

Accelerate through technology

Enable adoption of new tools and new ways of working with sufficient training and documentation.