In the world of self-driving cars, smart houses, and the Internet of Things, it is not surprising that in my weekly reading of National Insurance trade journals (great bedtime reading!) I see news about predictive modeling algorithms designed to direct care and patient safety, as well as large-scale artificial intelligence-driven medical professional liability underwriting systems.
These underwriting methods are designed to replace or supplement the work of underwriters. Self-driving malpractice insurance policies seem to be in the works.
An example of predictive modeling is rating auto accident and liability insurance premiums based on such seemingly irrelevant factors as the density of deer population in and around the city centre. Environmental pricing factors such as Department of Motor Vehicle records, restaurant reviews on Yelp, and deer density are just one of the increasingly popular sources of analytics that inform liability insurance pricing and increase the efficiency of premium development.
These days, underwriting is sometimes art and fledgling science, and other times outdated to the point of almost being useless. In fact, without technology improvements, underwriting can be a manual and highly experiential process.
Most Medical Professional Liability Insurance carriers use hard-learned lessons and claims history to create their policies. These tools can be homemade and not helpful enough to provide any guidance or useful data to assist in the quick review and pricing required of each underwriter and each application.Submissions are presented by brokers, and underwriters rely entirely on external factors known to them through their companies, as well as this personalized information included in the application submitted by the broker.Just as the future of healthcare is changing, so too are underwriting tools. This will reduce time and expense. There will be more models, and less manual processing. The goal is automated real-time use of advanced data and analytics to drive the underwriting workflow.
Environmental factors and online data building pricing algorithms
Healthcare organizations almost always market their services through their websites. These websites can be primary sources used to aggregate data. They’re becoming more easily available with reliable and fast computer systems. This forward-looking philosophy relies more on the present environmental dynamics of exposure rather than solely looking at loss history, education and medical specialty.
By reviewing websites and looking at the individuals who own and direct healthcare organizations, we're forming a picture of the medical profession that can support and rationalize much lower premiums in many cases. These premiums are lower than the old historical annual cost-of-living increase premiums associated with various specialties and facilities.
Revenue, number of consultations, demographic data and the connectivity of the public to the innovative health technology firm can provide the necessary pricing data that contributes to artificial intelligence base programs and can help underwriters come to quicker decisions. In health care specifically, contributing to the lower cost of medical service is a noble and overarching consequence of these automated intelligent predictive underwriting models.
If you can take the cost of underwriting each account from $5,000 down to $1,000 by applying underwriting algorithms gleaned from mining the wealth of resources available on the internet, then the role of underwriting will change forever. Less menial work and more critical thinking will result not necessarily in reductions in premium, but rather price stability! Ten years of national professional liability loss history supports the idea that there is pressure to pay more claims and to pay more experts and attorneys to defend.
These pricing models can assist the professional liability niche for years to come. Just as cars will soon self-drive, the pricing of medical malpractice insurance policies will self-underwrite. As data gets better and the software is tested, decisions will be almost exclusively data driven.Human judgment is still important because emotional decisions have an important place in the underwriting process. The insurance industry will change just as the healthcare industry has, and the cost of underwriting will go down after the important investment in technology to gather data from a variety of resources. Building pricing algorithms will stabilize prices in spite of fluctuations in losses.When our insurance carrier suddenly and without precedent reduces premiums to attract new business by over 50% of historical pricing levels, there are red flags that should at least give us pause and encourage us to look further at the numbers.Recently, an orthopedic surgery group canceled to go with a carrier that recently has posted huge losses. A look at their finances shows that acquisitions have drained surplus. This carrier is charging 30% of historical pricing trends based on same size same specialty pricing comparisons.A decision like this to change the professional liability in a high-risk specialty like orthopedic surgery can put assets at risk. It’s important to work with insurance carriers and brokers to study and understand pricing methodologies with the goal of stability rather than unreasonable prices.