Bitesize Impact 25: Pharm3r
September 19, 2019 Chris Sandilands
Pharm3r is a healthcare analytics platform and Oxbow Partners InsurTech Impact 25 Member.
Pharm3r uses proprietary AI and Machine Learning algorithms to collect, clean and aggregate pharma-related data (e.g. unstructured web data on clinical trial results). This data is then used to generate insight about pharma exposures, allowing insurers to make better risk selection, pricing and portfolio management decisions.
The primary insurance use case is to quickly detect, predict and price litigation risk. For example, an underwriter can see the trends and types of adverse events reported for a particular active ingredient or compare the nature of reported product defects for a type of medical device.
Pharm3r has a number of tools to help underwriters in risk assessment, pricing and portfolio management. Its PandoraPlus software application provides comprehensive profiles, comparing and aggregating risk at the product, class and manufacturer levels. Its built-in portfolio manager allows underwriters to track metrics such as risk, premium and exposure on insured manufacturers and to view portfolio trends. Since the release of the InsurTech Impact 25 2019 report, the PandoraPlus product has been “significantly expanded and deepened” according to Libbe Englander, Founder and CEO, with new data sources incorporated and new functionality added (e.g. analysis of claims data using proprietary NLP algorithms to further develop the understanding of a risk).
The team comprises biology and computer sciences expertise and its offices in Nova Scotia and New York City.
The Oxbow Partners view
Industrial insurers sometimes argue that their segment of the market is relatively immune to change. For example, many D&O underwriters have long argued that there are too few claims to model risk, and continue to price largely on market trends and gut instinct supported by some analysis of historic claims. (Describe Data, who we covered last week, is using advanced statistical analysis to address this particular issue.)
But industry databases and analytics companies are a game-changer for underwriters. In short, they allow underwriters to move away from using experience metrics (i.e. claims and near misses) as the primary source of rating to an informed and quantified view of exposure.
Consider a high layer medical device manufacturer’s liability policy. The broker may be pushing for below-average ROL pricing due to the manufacturer’s good claims history, but data could tell an underwriter that there has been a recent sharp increase in the number and severity of product problems related to a specific device. This insight could be the difference between a profitable and highly unprofitable book of business.
