Federato's platform leverages advanced Al to identify the highest-appetite, most-winnable accounts
Most traditional winnability tools use "type 1" insurance data, like account size and risk details, to anticipate if an account is likely to bind. But this data is often not sufficient to make an accurate prediction, and as a result some underwriters spend up to 40% of their time working unwinnable deals.
Federato's winnability scores leverage both "type 1" data and "type 2" interaction data unique to your business, including past interactions with individual brokers and accounts, to predict the likelihood that an account will bind. With this additional context, Federato's winnability scores offer 10x the predictive power of traditional scores.
What [Federato] were showing us was winnability scores and appetite scores to help us triage our risk so we could work on the highest win ability and highest opportunity risk first, which helps our overall bind efficiency and gives us up to a 30 to 50% lift in our ability to write more good premium.”
Incoming submissions are scored by appetite and likelihood to bind, and assigned a place in the winnability matrix: Quadrant 1 (high appetite and high winnability), Quadrant 2 (high appetite and low winnability), Quadrant 3 (low appetite and high winnability), and Quadrant 4 (low appetite and low winnability).
Underwriters can focus their first attention on submissions from quadrants 1 and 2, and spend more time working these promising deals. With less time wasted on unwinnable or low-appetite business, underwriters can send out more and better quotes, for a 15% increase in hit ratio.
When an underwriter selects a submission to examine, they're able to take a deep dive from the same interface to understand why the submission received the score that it did. From there, the underwriter can apply their expertise to analyze the risk and decide if they ultimately want to offer a quote.
The winnability algorithm takes the underwriters' decisions into account, and applies machine learning to continually improve its suggestions. Underwriters get up-to-date guidance on the most winnable, in-appetite deals, leading to up to 3.7x more high appetite bound accounts.
"We set a goal that by noon each day, each underwriter should have quoted the best three or four deals on their desk. To do that, they have to focus on what's in-appetite and winnable, rather than which brokers are most vocally calling for a quote. That puts the power in their hands to be more selective and write the best business quickly, and to spend more time on the deals and relationships where their particular skills can come into play."
