New age of underwriting
As the insurance industry rapidly evolves, the integration of AI and data analytics is reshaping the underwriting landscape. The rise of data-powered underwriting offers significant opportunities to streamline routine tasks, enhance accuracy, and allow underwriters to focus on more complex cases. However, this transformation also highlights a critical skills gap within the underwriting workforce.
To stay competitive, insurers must address these skill shortages while leveraging technology to optimise their operations.
Fisokuhle Nkosi, Head of Professional Indemnity at iTOO Special Risks, shared insights with FAnews about how insurers can prepare their teams for the future, the role of technology in automating and improving underwriting processes, and strategies for bridging the skills gap to ensure a forward-thinking and effective underwriting workforce.
The skills gap in underwriting
A key challenge in the evolving insurance sector is the skills gap that limits the effective implementation of data-powered underwriting. According to Nkosi, “Data analysis skills would be one of the skills identified as lacking in underwriting,” especially when it comes to using data to formulate pricing methodologies. This is essential for leveraging AI tools and data-driven approaches to underwriting.
Insurers must adopt strategies to upskill their current underwriting teams to handle data-driven tools and methodologies. Nkosi suggests that “when a new system or tool is introduced, employees should be included in the process before implementation, allowing for adequate feedback from employees.” This ensures smoother adoption. Additionally, she stresses the importance of “ongoing onboarding and training in using such tools and methods” and creating a “how-to-use guide” for future reference. Nkosi also advocates for implementing a data policy to ensure the ethical use of systems and tools: “Implementing a data policy and ensuring employees are aware of such policy to ensure ethical use of such systems and methods.”
The role of AI and data analytics tools
AI and automation are increasingly being used to eliminate mundane tasks in the underwriting process, allowing underwriters to focus on more complex cases. Nkosi emphasises that AI can “assist with creating efficiencies, eliminating mundane tasks in the underwriting analysis process” and “assist with data capturing of information previously manually captured by underwriters.” She also notes that AI can identify “risk themes and trends that can be used for future purposes even quicker than before,” helping create an underwriting database that gives insurers a competitive edge. “When an insurer can tap into databases with themes and trends, they can make pricing decisions faster than the rest,” Nkosi adds.
Several AI and data analytics tools have proven effective in enhancing underwriting accuracy and efficiency. Nkosi highlights tools like generative AI, including ChatGPT, Microsoft Co-pilot, and Google Gemini, which can provide “quick responses for risk analysis.” However, he cautions that the information generated by these tools must be fact-checked to ensure its accuracy: “Information and source verification is important when using these tools. Fact-checking is key.” Additionally, technologies like Distributed Ledger Technology (DLT) and Blockchain are being explored for their potential to lower costs and detect fraudulent transactions, which could have a transformative impact on the industry.
Managing complex cases with automation
The automation of routine tasks also enables underwriters to manage more complex and nuanced cases effectively.
Nkosi points out that with automation, underwriters are less prone to errors when processing information, which reduces the time spent correcting mistakes. “With less reliance on manual processes, underwriters can benefit from accuracy in their decision making, which will in turn have a positive impact on risk management strategies of the organisation,” he explains.
Automation allows insurers to process larger volumes more efficiently, leading to “immediate decision-making” and improved underwriting quality.
The future of the underwriting workforce
As AI and data analytics continue to reshape the insurance industry, Nkosi foresees significant changes in the underwriting workforce over the next 5-10 years. “Data analytics skills are becoming more prevalent, underwriting roles in the future will involve a large part of data analytics.” However, she stresses the importance of maintaining a balance between AI and human employees: “Organisations still need to maintain a balance between AI and human employees, both are still important for customer relations.”
To prepare the underwriting workforce for the future, continuous learning and professional development will play a vital role. Nkosi emphasises the need for insurers to foster a learning culture, where employees are encouraged to keep up with changes in the industry: “Create and foster a learning culture and environment where employees are encouraged to learn and keep themselves abreast of the changes in the underwriting landscape.” She also highlights the importance of ongoing training: “Continuous upskilling, training, and onboarding will be essential to fostering a symbiotic relationship between AI and humans.”
Talent and building a culture of innovation
In a competitive job market, insurance companies must implement strategies to attract and retain talent skilled in data analytics and AI for underwriting roles. Nkosi recommends creating a flexible environment that supports research and development as part of employees' daily responsibilities. “Flexible environment, allowing employees time for research and development as part of their ordinary roles and responsibilities” is one approach. Additionally, insurers should prioritise work-life balance: “Work/life balance – prioritising mental wellbeing.”
To embrace technological advancements, insurers must create a culture that encourages innovation within the underwriting team. Nkosi advises that companies foster an environment where employees are encouraged to learn and stay informed about developments in the underwriting landscape. “Transparency and communication, including educating employees on the ethical use of AI” are crucial to ensuring responsible AI implementation. She also suggests offering competitive packages and benefits to retain top talent.
Measuring AI success and ROI in underwriting
While the benefits of AI may not be immediately visible, insurers must be patient in evaluating the ROI of AI investments. Nkosi notes that “The results of these may not be immediate, it may take some time post-implementation to see the ROI.” Ensuring that employees are well-trained and understand the advantages of these tools will help mitigate challenges and drive successful implementation.
Ethical considerations in AI underwriting
Finally, Nkosi highlights the ethical considerations that insurers must address when implementing AI in underwriting. One of the primary concerns is underwriting bias, as algorithms using historical data may inadvertently perpetuate unfair practices. “Underwriting bias remains the main issue, algorithms using old, historic data could create more harm than good,” she explains.
Ensuring fairness and accuracy, maintaining privacy and security, and obtaining consent for data use are all essential to mitigate potential risks associated with AI implementation: “Ensuring that information is anonymised and ensuring that consent is obtained and that there is no copyright infringement of any information obtained from the various data sources.”
In conclusion, the future of underwriting will be shaped by the effective integration of AI and data analytics. While this offers exciting opportunities to enhance efficiency and accuracy, insurers must focus on upskilling their workforce, creating a culture of innovation, and addressing ethical concerns to ensure a successful transition to data-powered underwriting.
Writer’s Thoughts
As the underwriting landscape transforms through AI and data analytics, success will hinge not just on technology adoption but on the industry's ability to upskill its workforce and foster innovation. By investing in continuous learning and ethical implementation, insurers can future-proof their operations while maintaining the human insight essential to sound underwriting. Do you agree? Please comment below, interact with us on X at @fanews_online or email me your thoughts at [email protected].
