AI-Powered
Claims Optimization
Predict risks early, prevent escalation, and protect portfolio profitability.
Overview
Pinpoint’s AI-driven claims solutions detect high-impact scenarios at the earliest moment, whether at quote, FNOL, or during early handling. By surfacing key indicators like litigation potential, fraud propensity, and large-loss risk, carriers can act before costs escalate.
Seamlessly integrated into existing workflows, our models empower claims teams to allocate resources strategically, resolve cases faster, and deliver stronger policyholder experiences, while maintaining compliance and accuracy.
Reduce Severity
Improving Closure Rates,
and Protecting
Portfolio Profitability.
With Pinpoint, claims teams shift from reactive handling to strategic management.
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Anticipate Legal Involvement Before It Happens
Our Attorney Rep Propensity model enables carriers to predict attorney involvement in claims at or immediately after first notice of loss – often before legal representation is confirmed. Using advanced attorney rep prediction analytics, the model highlights claims with elevated claim legal representation risk, allowing adjusters to take proactive action. Carriers can adjust communication strategies, assign the right resources, and implement handling approaches that discourage unnecessary litigation.
- Identify likely represented claimants early in the lifecycle
- Adjust communication strategy and resource allocation
- Improve claim outcomes by tailoring handling approach
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Predict and Reduce Claims Litigation
Our Litigation Propensity model uses advanced litigation risk scoring to identify claims with potential for legal escalation early in the claims lifecycle. By leveraging claims litigation prediction, carriers can take proactive steps: involving legal counsel, adjusting reserves, or modifying settlement strategies, to reduce claim litigation severity and improve closure rates. Claims teams can prioritize these high-risk claims for closer monitoring, allocate resources effectively, and implement handling strategies that limit exposure to costly outcomes.
- Detect claims likely to escalate to litigation before it occurs
- Enable earlier legal intervention or reserve adjustments
- Improve closure rates and reduce severity
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Detect and Prevent Fraud Early
Our Fraud Propensity model provides advanced insurance fraud prediction to flag suspicious activity across the policy and claims lifecycle. Using a fraud scoring model, carriers can detect potential fraud at quote, First Notice of Loss (FNOL), or any point during claims handling. By analyzing claimant and applicant-level attributes, the model enhances claim fraud detection software capabilities and supplements existing rules-based or vendor tools.
- Score for fraud risk at quote, FNOL, or during claims handling
- Strengthen underwriting decisions with early fraud signals
- Improve SIU targeting and investigation efficiency
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Spot High-Exposure Claims Early
Our Large Loss Identifiers model enables carriers to predict large loss claims and detect high-exposure cases at or shortly after FNOL. Using advanced loss reserve accuracy analytics, the model flags claims with significant development potential, allowing claims teams to assign specialized adjusters, implement enhanced monitoring, and make more informed reserving decisions. Early identification of high-risk claims reduces adverse development, streamlines triage, and improves overall portfolio performance.
- Spot large-loss potential before it develops
- Assign specialized adjusters to high-exposure cases
- Reduce adverse development through early oversight
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Detect Risk by Loss Type
Our Cause of Loss Identifiers use advanced loss cause analytics and claimant risk attribute models to detect heightened risk for specific causes of loss – such as asbestos exposure, trip-and-fall, or habitability issues. By analyzing claimant-level attributes, the model provides early insight into potential loss types, supporting both claims handling and underwriting decisions.
Insights inform reserving, triage, and risk segmentation, improving operational efficiency and reducing exposure to adverse outcomes.
- Detect individuals with elevated risk for specific loss types
- Enable targeted claims handling by loss cause
- Support underwriting with pre-claim risk insights
Key Claims Benefits
Early Risk Detection
Identify litigation, fraud, and large-loss claims before costs escalate.
Proactive Management
Allocate resources strategically to improve closure rates and outcomes.
Portfolio Protection
Reduce severity, control costs, and safeguard profitability.
Case Studies
Predictive Power at Work
Auto Case Study: Loss Cost Model to Optimize Marketing Spend
Pinpoint helped reduce Loss Ratio by 4 points on personal auto Client: National Auto Carrier Line of Business: Auto Insurance Number of Policies: 714,577 Average Premium: $2,495 Use Case Focus: Customer Acquisition Challenges for Auto Insurers: The combined ratio for personal auto has worsened from 92.5% in 2020 (the best result in 25 years) to [...]
Auto Case Study: Claims Severity Predictions
Pinpoint helped reduce Loss Ratio by 3 points with Claims Severity Predictions Client: National Auto Carrier Line of Business: Auto Insurance Number of Policies: 714,577 Average Premium: $2,495 Challenge for Auto Insurer: A national auto insurance carrier looked to augment their modeling and solve the problem of balancing business against increasing claim payouts, increasing costs [...]
Auto Case Study: Litigation Risk Scores
Pinpoint Helped Identify an Additional 6% of Claimants Likely to Seek Attorney Representation Client: National Auto Insurance Insurer Line of Business: Auto Insurance Model Trained: 130,000 Claimants Use Case Focus: Claims and Litigation A national insurance carrier partnered with Pinpoint to receive Risk Scores identifying the likelihood of Third-party Claimants to seek Attorney Representation. With [...]
Home Case Study: Claims Frequency Prediction to Optimize Growth
Pinpoint helped reduce Loss Ratio by 3 points to optimize profitable growth Client: National Home Insurance Carrier Line of Business: Home Insurance Number of Policies: ~300,000 Average Individual Premium: $2,900 A national home insurance carrier partnered with Pinpoint to receive Loss Predictions at the top of the funnel (before the customer journey begins). Their current [...]
Home Case Study: Loss Cost Prediction to Reduce Non-Weather Water Losses
Pinpoint helped reduce Loss Ratio by 4 points during pre-application Client: National Home Insurance Carrier Line of Business: Home Insurance Number of Policies: ~150,000 Average Individual Premium: $1,291 A national home insurance carrier partnered with Pinpoint to receive Loss Cost Predictions at the top of the funnel (before the customer journey begins). Their current models [...]
Auto Case Study: Loss Cost Prediction to Optimize Growth
Pinpoint helped reduce Loss Ratio by 4.6 points by focusing on Individual Drivers Client: National Auto Carrier Line of Business: Auto Insurance Number of Policies: 80,000 Average Premium: $1,500 Challenges for Auto Insurer: A national auto insurer partnered with Pinpoint on generating Loss Cost predictions to better understand the profitability on individual drivers and identify [...]
Home Case Study: Claims Frequency Predictions for Book Acquisition
Pinpoint helped reduce Loss Ratio by 7 points by focusing on Book Acquisition Strategy Client: National Home Insurance Carrier Line of Business: Home Insurance Number of Policies: 200,000 Average Premium: $2,813 Use Case Focus: Book Roll A national home insurance carrier used Pinpoint's platform to generate Loss Predictions. Their existing models were only available after the [...]
Frequently Asked
Questions
How does Pinpoint’s claims optimization help carriers improve outcomes?
What types of risks can Pinpoint’s claims models identify?
Do the claims models require historical claims data to work?
How do these solutions integrate with existing claims workflows?
What benefits can carriers expect from AI-powered claims optimization?
From Our Partners
Michael Lorion
CEO
“Pinpoint’s explainable visualizations reveal what drives human behavior, and also the interesting reasons why conventional data have missed the signal on this important issue. We see this as an important step forward in predicting behavior and ultimately reducing frictional costs and premiums.”
Vern Kirchhoff
SVP of Data Analytics
“Pinpoint’s automated platform unlocked 7 points of Loss Ratio improvement for our homeowners book for a 1-year implementation and, over the longer term, a larger bottom-line benefit as more of the book takes on the selected risk contours. The new signal we validated represents one of the largest boosts in predictive performance I’ve seen in the industry in 30 years.”
Michael Pauletti
Senior VP & Chief Pricing and Actuarial Officer
“Pinpoint’s deep-learning platform allowed us to predict non-cat homeowners’ losses at the beginning of the customer journey for the first time. Moreover, this score adds a remarkable new incremental lift above and beyond our rating model; it’s one of the most predictive factors we’ve seen.”
Analytics Team
“Pinpoint has provided game-changing new data to drive markedly improved loss ratios through better risk selection and claims handling.”
Rick Carter
Vice President, Analytics
“Above and beyond our latest pricing models, Pinpoint’s scores show material predictive lift for personal auto pure premiums. These are impressive results relative to other emerging vendor data offerings.”
Chad Combs
VP of Personal Lines, Underwriting
“Pinpoint provided significant predictive advancement in the identification of a highly important loss exposure. This enables Ohio Mutual to better identify premium leakage and loss mitigation opportunities in our Homeowners book.”
Chris Strohl
Vice President, Underwriting
“We’re excited to partner with Pinpoint as we look at the opportunity to get deeper insights into our customers and understand risks based on individual behaviors. Pinpoint’s deep learning capabilities are a game changer for us to better serve our customers and agents.”
Alice Robinson
Chief Actuary
“After just a few weeks of evaluating Pinpoint’s custom loss scores, we saw a significant improvement in loss ratio, and in predictive performance in our non-pay cancel model. In addition, the explainability of lift in predictive power yielded valuable insights. The Pinpoint team is helpful, knowledgeable, and easy to work with.”
Greg Godshall
President and CEO
“Pinpoint’s actuarial loss predictions will enable us to orchestrate the best experiences for agents and our customers, reducing friction and creating the ability to micro-segment leads like never before”
Fast-Track
Profitable Growth
Data Science That Delivers Business Impact
Pinpoint is an AI company purpose-built for insurers. We combine deep actuarial expertise with modern data science to solve real-world problems across underwriting, marketing, and distribution. Our mission is simple: make insurance more precise and more profitable—one model at a time.