Many life insurers are considering entering or expanding their presence in the middle market where the time and costs associated with traditional underwriting methods are difficult to justify. A primary concern that carriers face is how their sales force will act when the rigors of a fully underwritten program are removed and whether they have the ability to effectively manage agent behavior. Yet if a company has the right set of tools backing up a simplified issue program, it can minimize these issues and take advantage of enormous opportunities in the middle market.
Adverse selection – the attraction of a disproportionate number of high-risk lives to a product offering – is a concern for all life insurers, especially for companies in the non-medically underwritten market. While the risk of adverse selection can be factored into the pricing of these products, it is still one of the main challenges facing companies in the simplified issue market.
Analyzing the results of simplified-issue programs, it is common to see a small subset of agents who attempt to take advantage of weaknesses in the system and submit anti-selective business. Companies most often discover this years after the behavior occurred when analyzing paid claims data to discover why their actual to expected ratios on a product are not working out as desired. Insurers are then left to contemplate how much additional business the offending agent has placed in the interim and grimace at the impact this could have on results for years to come.
Velogica®, our automated underwriting engine for small face amount life products, has a unique capability that aids in identifying potential anti-selective behavior. This allows companies to deal with issues early and correct problems when the costs can be minimized. While Velogica clients are usually drawn by the speed and sophistication of our underwriting decision algorithm, many come to believe that the agent analysis capability is one of Velogica’s most valuable features.
Identifying anti-selective behavior is extremely difficult to accomplish by looking at individual applications. Velogica instead captures and analyzes data using a statistically driven warning system that flags unusual patterns in an agent’s portfolio of cases. The analysis draws upon several factors: the number of applications submitted, the age distribution, the level of admitted information on the applications, and the amount of times non-admitted information has been discovered elsewhere.
The process compares the performance of individual agents against the portfolio as a whole and highlight agents who are extreme outliers of normal metrics. The actuarial math behind this approach capitalizes on our years of experience underwriting business using Velogica and as a reinsurer. Our understanding of simplified business allows us to establish accurate probabilities specific to a client portfolio and successfully indicate which agents exhibit behavior well outside what would be expected.
There will always be applicant misrepresentation in this business. However, when the math says that the business from an agent has only a 0.2 percent likelihood to have been achieved randomly, a carrier needs to consider what the agent is doing to remove the randomness from the process.
Two categories of warning flags alert us to possible suspicious behavior: The “Smoking Gun” and the Inferred Misrepresentation. “Smoking Guns” occur when subsequent investigation by tools such as electronic databases definitively tells us that information was omitted or incorrect on an application.
Inferred instances of possible misrepresentation can be identified by analyzing the pattern of answers on applications from a particular agent. While this may not seem as convincing as the “Smoking Gun” proof, our sophisticated algorithm provides the statistical probability that the pattern of information on applications occurred randomly. Our experience shows that all of our clients have at least a few agents with a probability rating approaching zero percent, meaning that the pattern of responses on their submitted applications has close to no chance of occurring randomly, and many achieve concerning scores on multiple flags.
The Sentinel Effect
While more difficult to quantify, we also believe that carriers gain significant benefits from the sentinel effect produced using this tool. When word spreads that a carrier has a tool to identify application misrepresentation, some level of anti-selection can be stopped before it even begins.
In addition to being useful for individual agents, the tool can also be used for any identifiable sub-group that a Velogica client can identify within their portfolio. This can allow analysis of the business from a particular office, region, wholesaling group, etc.
Anyone who writes simplified issue business is interested in controlling anti-selection, and likely has a program in place to monitor their distribution force. Our process allows clients to focus those efforts where they will do the most good – on the few agents whose business can be statistically measured as anti-selective. By helping companies manage behavior down to the agent level, our Velogica solution can influence better adherence to practices and contribute to an improved quality of business.