Insurance Underwriting
Use AI-Powered Underwriting to evaluate 100% of claims data, align prices with risk, and drive higher profits while lowering operating costs.
Daisy’s AI-Powered Underwriting solution uses both application data and relevant historical claims experience to better align underwriting decisions with risk, lowering operating costs through automation to improve loss ratio.

Increase profitability with precision pricing
Daisy’s Theory of Risk™ will:
- Use optimal control dynamics to identify anomalies in application data.
- Use identity and network resolution to evaluate all historical claims and underwriting data to build peer groupings and link underwriting applications.
- Refine risk levels and differentiate pricing using detailed claims history.

Automate your underwriting process to reflect market dynamics
Daisy’s Insurance Underwriting solution will:
- Eliminate the need to manage a continuously increasing set of underwriting rules.
- Streamline your underwriting process to do more with fewer underwriters.
Automate your underwriting process to reflect market dynamics
Daisy’s Insurance Underwriting solution will:
- Eliminate the need to manage a continuously increasing set of underwriting rules.
- Streamline your underwriting process to do more with fewer underwriters.

Establish results
Revenue increase of 1-3% with stable or improved loss ratios
Daisy will recommend price changes on more than 10% of your applications, resulting in millions of dollars in incremental revenue.
Explore Our Other Insurance Solutions

Insurance Assessment
From fraud avoidance to increasing straight through processing, Daisy’s Insurance Assessment identifies previously uncovered value and business opportunities for your company.

Fraud Detection
Use real-time data to detect and resolve suspicious claims, and dramatically lower false-positive rates.

Claims Automation
Identify high-value fraud investigation and segment claims for automation.

Loss Ratio Optimization
Find the optimal combination of pricing, underwriting, fraud avoidance, and claim processing decisions to determine the desired loss ratio.
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