The highly complex inland marine insurance sector is finding a shortage of qualified practitioners, according to a new report by
With expected increases in business volume within some of its sub-sectors and the pending retirement of its baby boomers, this niche market’s need to train a sufficiently large next generation of inland marine underwriters is well recognized in the industry, notes Conning. While some in the industry are taking steps to reverse the trend, many still face obstacles such as how to “bridge the generational divide to combine the best of the “old school” approaches to the inland marine craft with the tools of the current generation,” notes the report.
Another obstacle relates to the diverse products that comprise the insurers’ portfolios. Insurers must train new underwriters based on these statutory inland marine insurance lines, which are grouped on the basis of satisfying criteria specified in the Nationwide Marine Definition, and are currently in a state of flux.
Of those products, the largest groups, measured by aggregate premium, is construction-related and includes builder’s risk, contractor’s equipment, and installation floaters. Although construction is currently down from an economic standpoint, the boom of 2000-2006 brought many insurers to the table that then had to deal with the ramifications of the economic downslide in 2008-2010, causing them to fight for each premium dollar.
Both commercial and personal lines; fine arts and yacht, are two more inland marine segments that have taken a beating due to the economic crisis, creating extreme competition among insurers.
The inland marine motor cargo carrier’s liability insurance represents the segment’s second-largest product area, also affected by the economic landscape. Among this group, the use of data is rapidly being used to both modernize the inland marine transportation world, and create a competitive advantage among its insurers.
Although some inland marine insurers seeking rating plans are leveraging data associated with sufficiently large numbers of risks that have functionally homogeneous characteristics, overall, the notable difficult, complex nature of its many products creates further obstacles for data analytics development and deployment, and this plays forward to difficulties within the training function itself.
“It is inevitable that the progressive development of quantitative tools will improve the handling of even the most complex accounts, but it is hard to avoid the conclusion that there will continue be a need for specialized expertise,” notes conning.
