Insurance Sector Focus: Do Your Underwriters Have the Data Skills to Succeed?

Underwriters must adapt their analytical and problem-solving skills to a data-driven world. In recognition of this, forward-looking L&D teams at insurance firms are increasingly focusing talent strategies around digital skills development for their valued employees.   

The vast amount of data available for many industries is a game-changer, providing deeper insights and opportunities for businesses to understand their customer base and grow. The insurance sector is no different. Data is now the lifeblood of the insurance industry, and access to new data sources and external data is changing how organisations assess customers’ risk and pricing policies. This is expected to increase over the next three years (Deloitte, 2020) and beyond. 

The insurance industry is ripe for innovation and disruption, as demonstrated by the rise in InsurTech companies and investments by venture capitalists in this space. For Talent professionals, it’s essential to be one step ahead and to predict future skills requirements. InsurTechs are challenging traditional incumbents, forcing them to respond to the changing market. To compete effectively, these incumbents must reinvent and modernize how they use new data sources and invest in their workforce to employ innovative toolkits for analysis.

Underwriters are being challenged to move from hindsight, where their decisions are evaluated after the fact, to foresight. Active portfolio management and ongoing monitoring allow underwriters to understand the impact of risks added to their books in real-time. It’s a significant industry shift and a big ask for those who are not trained data analysts.  

Active monitoring can mean insurers can more accurately predict issues and work towards outperformance. Having solid data skills such as handling data securely and safely, using data to identify critical risks, and communicating data-driven recommendations and decisions to others means underwriters can accurately and efficiently perform deep dives into data, predict issues, and work towards outperformance more accurately. Take Cyber Insurance, where threat actors constantly evolve their tools and techniques, making hindsight underwriting less reliable. Insurers are making inroads with open insurance data-sharing models. Although much more can be done across the industry, there is no doubt that the ability to perform quantitative analysis confidently supports better forecasting and risk management. 

Data-driven principles and techniques allow insurance companies to streamline their existing processes and are meant to complement their current workflow. Human judgment and expertise will always be required to accurately price risk in line with a company’s business strategy. However, in addition to that expertise, there is a broad range of cutting-edge Data Analytics tools that Cyber Insurance can employ to help the Underwriter to develop adequate pricing and risk management models, as well as derive meaning and insights from large historical datasets. 

Meanwhile, the customer’s world is becoming more digital, and the widespread availability of alternative and predictive data is increasing. 77% of insurers say improving customer experience significantly motivates their Digital Transformation efforts (Celent). 

The reliance on underwriting expertise diminishes as risk selection becomes increasingly competitive and facilitates more rapid adjustments to underwriting strategies. With these changes and the increased adoption of new tools and emerging technologies, insurance professionals are often concerned that their employers will use these technologies to replace them, resulting in fears about job security and the thought that robots will eventually take precedence. For many, the rise of automation in the workplace sounds alarm bells. 

We recognise that the insurance industry is experiencing disruption through automation and increased digitisation, and the role of the Underwriter is evolving as a result. However, automation is a steady process, and instead of replacing entire roles, the majority of jobs will only experience a replacement of certain tasks.  

Accenture predicts that 8% of an underwriter’s tasks will be automated by 2025. While it’s true that the roles of underwriters are likely to change due to new data and technology, the buck will still stop at the Underwriter’s desk. You can never underestimate the power of an informed/educated human interpretation of data, and there are significant opportunities for underwriters, supported by their L&D teams and business leaders, to develop new skills that will future-proof their careers and unlock new possibilities for their organisations. 

Business-critical data skills can be the difference between extracting value from the massive amounts of data that insurance firms hold and letting it go to waste. Equally, appropriate data analysis skills can be the difference between securing the future success of your underwriting function and losing your competitive edge. 

Rather than being displaced by automation, underwriters can ensure job security and enhance their value by gaining new, sought-after skills. Ultimately, underwriting requires human judgement; combining this with the needs of the 21st century gives you a competitive edge.  

As machine learning, virtual reality, and other digital advances increasingly automate the underwriting function, more successful underwriters can take advantage of technology and newly developed skill sets to become more valuable to both their clients and employers. Leveraging real-time data, industry insights, and market-sensing capabilities, they could be better equipped to help customers manage risk and provide insight on how to avoid and prevent exposures. 

Success in the transformation journey and underwriting modernisation is likely to hinge on upgrading four major areas in tandem: 

• Data and analytics 
• Strategy and governance 
• Technology 
• Culture and talent 

Having worked at LV= GI for over ten years, Craig Dunne explains how big data has changed the sector. “When I started working in insurance, there was limited data. We only had access to one-way data, such as sales figures and claims. Over the years, that has been transformed by the availability of data enrichments from third parties. My interest in data science has grown with that evolution.”  

LV= work with Corndel to grow their data talent, launching the first Level 4 Data Analytics programme in January 2020. This data skills development supports LV=’s desire to keep pace with data innovation, a crucial part of their business success.