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Vertafore Introduces RiskMatch Retention Prediction to Help Independent Agencies Improve Client Retention Rates

Ask Kodiak and Vertafore Announce Partnership

Industry-first analytics tool uses data modeling & adaptive machine learning to surface at-risk polices, equipping agents for proactive client engagement

Vertafore today announced RiskMatch® Retention Prediction, a groundbreaking tool to give agencies insights to increase client retention by identifying policies at risk for cancelation or non-renewal. As an integrated part of Vertafore’s award-winning RiskMatch platform, this latest feature is part of Vertafore’s strategy to help agencies modernize with analytics that support data-driven business decisions and increase profitability.

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Agents work hard to build relationships with their clients and continuing those relationships is essential for an independent agency’s success. But the aggregated data from 3,700 agencies in RiskMatch shows an average client retention rate of just 83% across the industry — meaning independent agencies must replace nearly a fifth of their clients each year just to maintain business at the same level.

Reducing client turnover — sometimes referred to as client “churn” — can substantially influence an agency’s profitability for the better. Even modest, consistent improvements in retention can have a dramatic impact. For example, with just a consistent 3% increase in retention, agency revenue could be up to 15% higher after five years. RiskMatch Retention Prediction can help agencies spot potential issues and take proactive steps to retain business — setting the stage higher retention rates and better year-over-year growth.

“We’re focused on delivering data and analytics tools that help our customers modernize, grow and support the most essential needs of their business,” said Chad Hawkinson, Vertafore’s chief product and data officer. “Putting this predictive tool into the hands of independent agencies empowers them with the right insights to build stronger, more loyal and more profitable customer relationships.”

Without an automated data analytics tool, agencies can spend excessive effort tracking and reporting on their client retention rate, and they can’t identify at-risk policies and clients. RiskMatch Retention Prediction both analyzes historical retention trends and looks ahead at upcoming renewals, enabling agencies to:

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  • See upcoming renewals ranked by retention risk on scale of high, moderate, low, to prioritize customers for churn management initiatives.
  • Focus their retention efforts on customers with the highest savable value to maximize resource utilization and business growth.
  • View client retention trends by carrier, product, geography, industry sector and even office location or agency rep to identify opportunities for client outreach, training or other solutions.
  • Benchmark retention rates across multiple variables to measure the effectiveness of churn management solutions and drive continuous improvement.

Built on Vertafore’s unique open platform, Titan™ technology, RiskMatch Retention Prediction uses Vertafore’s industry-exclusive machine learning capabilities to examine 250+ internal and external factors across market, client, and agency data. The dynamic solution not only benchmarks historical data but also adapts to current market and industry factors to deliver more accurate future-looking insights — such as how major events like a global pandemic might impact future retention.

In addition to analyzing an agency’s own client and policy data, the retention risk tool also benchmarks agency performance against the overall market, leveraging the largest database in the industry with over $135 billion in in-force premium across 150+ million policies to deliver dependable, proven predictive insights.

Agency managers can view RiskMatch’s retention analysis in an intuitive, user-friendly dashboard and drill down into specifics to quickly formulate a churn management strategy. The tool is available now to all RiskMatch customers and works across multiple management system.

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