CLHIA Claims and Anti Fraud Conference 2026

Innovation meets impact: See Shift Technology at CLHIA 2026 

Fraud, waste, and abuse don't stand a chance when the industry works together. At Shift, we’re dedicated to fueling CLHIA 2026 with collaborative AI solutions that simplify detection and amplify results.

Heading to the Claims and Anti-Fraud Conference? We’d love to show you how our latest innovations can transform your detection and prevention workflows. Visit us to see why leading insurers trust Shift to drive their FWA strategy forward. Let’s build a more secure future, together.

Meet the Shift Team 

Stop by the Shift exhibit to connect with our experts and explore how we are redefining Healthcare FWA Detection. See real-world success stories of how our cross-industry intelligence is helping Canadian insurers navigate their most complex FWA challenges. 

• Advanced, Insurance-Grade AI: Purpose-built for health insurance, our AI combines agents, machine learning, generative AI, and hundreds of external data sources to deliver fast, accurate, and explainable results—right when you need them.
• Real ROI, Proven Impact: Shift solutions deliver 5–10x ROI by pinpointing suspected fraud, waste and abuse, identifying savings and recovery opportunities, and accelerating claims processing.
• Deep Industry Expertise: With 200+ data scientists focused solely on insurance and a proven track record with 115+ insurers in 30+ countries, we understand the industry trends and nuances of Canadian insurance and deliver with confidence.
• Global Recognition: From Celent’s 2024 Luminary Award to inclusion in CNBC’s World’s Top InsurTech Companies, Shift continues to be recognized as a leader in insurance AI innovation.

Shift on Stage

Wednesday, June 10, 12:45 - 1:05 PM

Spotlight Session: The AI Remedy: Detecting Fraud, Waste & Abuse in Health Plans

Jason Yan, Senior Data Scientist

Learn how AI is changing the fight against fraud, waste and abuse (FWA) in health plans. This session explores practical AI applications: agents, automated document analysis, anomaly and network detection across claims and clinical data, and AI‑assisted investigator workflows that prioritize high‑risk cases. See real examples of how combining internal records with external datasets improves signal quality, speeds investigations and reduces false positives. Join us to understand how AI can strengthen plan integrity while meeting privacy and regulatory expectations.