For the second consecutive year, the US P&C insurance industry has faced underwriting losses, according to a May 2024 report from the Insurance Information Institute and Milliman. Globally, broking giant Aon reported that insurance losses last year were 31 percent above the 21st-century average, exceeding $100 billion for the fourth year in a row. In an environment of continued economic volatility, high interest rates and inflation, rising replacement costs, and an increased frequency of covered risks, the pressure to enhance profitable underwriting in insurance has never been greater. To combat these challenges, insurers must scrutinize their underwriting processes, ensuring that managed rules are not only efficient but also hyper-effective and work in real-time across systems.

The Challenges of Modern Underwriting

The current underwriting landscape is shifting towards the straight-through processing (STP) model, a method that automates underwriting decisions to improve efficiency. However, while STP is undoubtedly fast, some systems can lack the agility and precision required to adapt to a rapidly changing market. Traditional underwriting and exposure management practices, reliant on historical data and intuition, are increasingly insufficient. This rigidity is exacerbated by the isolation of underwriting from pricing and rating functions, leading to a fragmented approach that can undermine profitability, and does not equate to the holistic view that the concept of STP ultimately promises.

The Need for Agile and Data-Driven Underwriting

To address these issues, insurers must transition to a more agile, data-driven underwriting and STP model. This involves integrating advanced analytics, machine learning (ML), and simulation techniques into the underwriting process. By doing so, insurers can move from a reactive to a proactive stance, using predictive analytics to foresee and mitigate risks more effectively.

A pivotal component of this transition is the management of underwriting rules. Effective rule management can significantly enhance the accuracy and efficiency of underwriting decisions. Here are our five best practices recommendations for managing underwriting rules that we have developed from our work with leading global carriers:

  1. Centralized Rule Management: Consolidating all underwriting rules into a single, centralized platform is essential. This approach allows for easier updates and ensures consistency across the organization. For agility and efficiency, it is critical that non-tech users such as underwriters are empowered to manage and update rules without extensive IT involvement.
  2. A/B Testing and Simulation: Implementing A/B testing to evaluate the impact of different underwriting rules. By comparing various scenarios side-by-side, insurers can identify the most effective strategies before deploying them in real-world applications. Advanced simulation techniques can forecast the outcomes of rule changes, providing valuable insights into their potential impact on the portfolio.
  3. Integration with Pricing and Rating: Ensuring that underwriting rules are closely integrated with pricing and rating functions. This holistic approach allows for better alignment and consistency, ultimately leading to more accurate and profitable underwriting decisions.
  4. Low-Code/No-Code Interfaces: Deploying low-code or no-code platforms will empower underwriters to create and manage rules independently. These user-friendly interfaces make it easier for underwriters to implement complex logic without requiring deep technical expertise.
  5. Continuous Improvement: Adopting a mindset of continuous improvement is essential. Regularly review and update underwriting rules based on new data and market conditions. Leveraging machine learning models can aid in this process by continuously refining and optimizing rules.

The Role of Technology in Underwriting Transformation

The transformation of underwriting processes is heavily dependent on the adoption of advanced technology. The most successful modern underwriting solutions combine traditional rules-based approaches with cutting-edge ML and simulation capabilities. This hybrid model not only enhances the precision of underwriting decisions but also improves time-to-market and overall business agility.

A key benefit of integrating advanced technology into underwriting is the ability to make faster and more accurate decisions. Fully automated underwriting decisions streamline the process, reducing manual work and minimizing the risk of errors. This not only enhances operational efficiency but also significantly improves the customer experience by providing quicker responses.

Furthermore, advanced simulation and A/B testing enable insurers to understand the impacts of underwriting changes before they are implemented. This foresight allows for better risk management and more strategic decision-making, ultimately leading to increased profitability.

The heart of unlocking profitability: Underwriting Expertise

To my mind this forward-thinking scenario-based testing gets to the heart of unlocking profitable underwriting because it addresses one of the most pressing issues facing insurers today: the effective utilization of underwriters’ expertise. Their time is valuable, and the future of underwriting lies in the seamless integration of traditional expertise with modern technology. By automating routine tasks and simplifying rule management, underwriters are freed to focus their time on more complex and value-added activities like testing for outcomes, leveraging their expertise to drive better underwriting.

Insurers that embrace this approach will be well-positioned to navigate the challenges of today’s market and emerge as leaders in the industry. The time to act is now – the tools and best practices are available, and the benefits are clear. It’s time to stabilize the foundation of underwriting and build a more resilient and profitable future.