Staffing crunch forcing commercial insurance industry to embrace technology

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The COVID-19 pandemic shone the spotlight on growing labor shortages throughout the U.S. economy. While most of the attention to find entry and mid-level workers has focused on retailers, restaurants, and other service industries, the reality is that the staff shortage is affecting Wall Street banks, construction, manufacturing, trucking, and more. The pandemic has exacerbated long-standing staffing issues for commercial insurance brokers and carriers and is driving more companies to look to technology to bridge the gaps.  

Many common dynamics are driving the overall labor shortage. As the pandemic rose and fell, more Americans reassessed which types of jobs they wanted and at what pay. The rising acceptance of remote work, elimination of the daily commute, lack of access to childcare, desire and opportunity to start a business, and simply workers choosing to leave the workforce altogether are driving the staffing gap. Experts believe the staffing challenge is not a temporary issue but, in fact, the new normal.

Commercial insurers face challenges beyond the pandemic. Attracting younger workers has long been a problem for brokers and carriers. Understaffing of key roles within the industry is a long-standing issue. It’s already common for high-level staff to spend time on administrative tasks instead of focusing on their chief responsibility -- managing risk. And with nearly 25 percent of senior insurance professionals who are ready to retire or have already done so, the staff and knowledge gap within the industry could explode, severely limiting the ability of insurers to respond to claims and assess risk.


Staff shortages particularly impact commercial insurers because they suffer from data overload. Evaluating submission documents is perhaps the most critical aspect of underwriting, with commercial insurers processing nearly 100 million submissions every year. Every submission requires staff to process what is likely to be hundreds of pages and thousands of lines of text. Today, nearly all that underwriting data is collected and analyzed by people. Even fully staffed, the placement process is drawn-out and costly, often taking 45, 60, even 90 days to complete. Brokers and carriers have limited resources and struggle to monitor the massive amount of incoming data – creating unnecessary, costly bottlenecks. Staff shortages mean more delays, less efficiency, less revenue, and fewer projects approved.

Many factors contribute to staffing shortages within each industry, but the most common pitfall is the failure to embrace new technologies. Commercial insurance has been particularly slow to innovate and transform. New technologies like scalable artificial intelligence (AI) and machine learning can revolutionize the industry by automating and streamlining inefficient, manual processes, dramatically increasing efficiency and driving more revenue.

Insurance is a data industry, and data presents itself in thousands of ways. Traditional processes, which execute a list of pre-programmed instructions, have not kept up with the broad scope of material leverage to determine risk. Doing things "the old way" already costs brokers and carriers $55 billion annually. Automating data extraction and recognition from unstructured or semi-structured sources, such as free-form text fields, spreadsheets, and PDFs improves model inputs, enables insurers to dramatically improve accuracy and drive better decisions.

AI learns and adapts to the information as it is processed, allowing businesses to quickly identify data patterns, improve predictions, and initiate data-driven decisions more rapidly and efficiently. It delivers production-ready data from insurance applications, loss runs, emails, policy forms, exposure schedules, and other document types at scale, creating scalable and repeatable processes that review reams of unstructured or semi-structured submission data and create actionable ready-to-use data.

These solutions are finally advanced enough to unlock the deeper and valuable insights within information previously trapped in unstructured submissions, quickly converting emails, applications, loss runs, and exposure schedules into enriched structured data used for underwriting, pre-fill, and analytics. Data libraries fill in gaps to advance risk management and shorten the quote-time process from potentially weeks to mere hours. Brokers and carriers receive complete, enhanced data sets, helping them respond more quickly to the market and boosting productivity and profits.

Today’s labor shortage is likely not a simple short-term problem. Commercial insurers must innovate now to prepare for the future. Current market forces and uncertain pandemic realities require the industry to accelerate adoption of new digital and AI solutions to reduce the impact of the talent crunch, fast-track revenue, drive better risk selection, improve time-to-quote, and provide more complete and usable data.

Jeff Mason is the CEO of Groundspeed Analytics, a leading provider of SaaS-delivered submission and placement technology to the commercial P&C industry. Groundspeed's smart ML-enabled platform automates document processing workflows and intelligently integrates and delegates to human-in-the-loop for last mile validation. By uniquely combining AI with Human-in-the-loop, Groundspeed provides the most advanced solution to ingest, enrich and analyze data from unstructured commercial insurance documents to help insurance carriers and brokers transact smarter and faster. Groundspeed's comprehensive solutions are available via API. For more information, visit

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