Pandemic staffing crunch creates commercial insurance hurdles
Current market forces and pandemic realities require faster adoption of new digital and AI solutions.
The COVID-19 pandemic labor crisis continues to be one of the top stories of 2021. While the bulk of attention has focused on retail, restaurant and service sectors, the shortage is impacting industries across the board, from Wall Street banks to construction or trucking; this staffing crunch appears to be more than a short-term blip.
According to former U.S. Bureau of Labor Statistics Commissioner Erica Groshen, the current environment is less a labor shortage than a structural change in our economy. The pandemic has accelerated key sectors and simultaneously shifted the labor market. E-commerce and telemedicine, for example, took giant leaps forward, while other segments rapidly receded. In addition, demographic shifts over the coming decades are poised to hasten staff shortages as more senior talent retires and fewer young professionals are available to replace them.
It is a complex, daunting challenge.
The commercial insurance industry is no exception, and the situation is compounding the industry’s already existing “talent gap.” One recent report estimated almost a quarter of insurance professionals have or are about to retire. Meanwhile, millennials are largely being drawn to newer and more high-tech industries. Exacerbated by the pandemic, this ongoing challenge could severely impact the industry by further delaying the time-consuming, meticulous underwriting process, reducing efficiency, and extending the period between a quote request and policy delivery.
Mission-critical
Today, evaluating submission documents is one of the most critical aspects of the underwriting process. Commercial insurers process nearly 100 million submissions every year, and each submission requires staff to pour over hundreds of pages and thousands of lines of data manually. Fully staffed, the placement process is drawn-out and costly, often taking 45, 60, even 90 days to complete. Furthermore, brokers and carriers have limited resources and struggle to monitor the sheer volume of incoming data, which creates unnecessary costly bottlenecks.
The current labor shortage threatens to create even greater delays to this painstaking process. It is already common for high-level staff to spend time on these administrative tasks instead of focusing on their main responsibility: evaluating risk.
Unfortunately, commercial insurance has been slower to innovate and transform to new technologies. According to Deloitte, the reluctance to embrace solutions such as machine learning and scalable artificial intelligence (AI) is limiting commercial carriers’ and brokers’ productivity. It is critical that the industry transform data extraction and recognition from unstructured sources, such as free-form text fields, improve model inputs, and enhance accuracy to drive better and quicker decisions. Underwriters using traditional legacy technology are handcuffed with unproductive tasks, such as manually analyzing and recording information from disparate sources and multiple systems, which leads to reduced productivity, efficiency and profits, costing carriers and brokers an estimated $55 billion annually. Even with that effort and cost, large data gaps remain.
Insurance is a data industry
Data presents itself in thousands of ways in insurance, and traditional processes have not kept up with the broad scope of material leverage to determine risk. Unlike traditional technology, which executes a list of pre-programmed instructions, AI learns and adapts to the information as it is processed, allowing businesses to identify information patterns and make better predictions and data-driven decisions more quickly and efficiently.
For commercial carriers and brokers, an effective AI platform can deliver production-ready data from insurance applications, loss runs, emails, policy forms, exposure schedules and other document types at scale. To be a true service to insurers, an AI platform must possess deep domain experience that understands the building blocks of effective automation, creates scalable and repeatable processes that can handle the full scope of submission data, and be able to take a broad set of unstructured or semi-structured documents and transform them into actionable, enriched data sets that are ready to use.
Rapidly evolving InsurTech solutions are now advanced enough to unlock deep, valuable insights from the information previously trapped in unstructured submissions. These solutions convert commercial insurance documents such as emails, applications, loss runs and exposure schedules into enriched structured data used for underwriting, pre-fill and analytics. Enormous repositories of data can now serve to fill in data gaps accurately to advance risk management. These solutions can shorten the quote-time process from potentially weeks to hours and provide brokers and carriers complete and enhanced data to respond more quickly to the market, increasing win rates and premiums.
The next generation of AI
AI, which has been under development for more than a decade, can rapidly advance the commercial insurance industry. One method InsurTech can use to build greater belief and trust in the technology is to ensure solutions maintain real oversight from real people. It requires a genuine human-machine partnership, one that continuously monitors data and digitization and checks for incongruencies and anomalies. This ensures greater accuracy and paves the way for greater trust and adoption of this transformative technology.
The ongoing labor shortage rippling through the world economy may be much greater than a short-term problem, so commercial insurers must act now to build for the future. Current market forces and pandemic realities require faster adoption of new digital and AI solutions to not only reduce the growing impact of the talent crunch, but help fast-track revenue, drive better risk selection, improve time-to-quote, and provide more complete and production-ready data.
Transformative AI technology provides the key for brokers and carriers to tame talent and data challenges, compete better, and be profitable in a rapidly evolving environment.
Jeff Mason (jeff.mason@groundspeed.com) 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 www.groundspeed.com.
These opinions are the author’s own.
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