Shift’s Solutions Recognized for Sophistication and
Breadth of Technology and Leading Market Presence
BOSTON and PARIS, Sept. 10, 2024 /PRNewswire/ — Shift Technologya provider of AI-powered decision optimization solutions for the global insurance industry, today announced that Shift Claims Fraud Detection and Shift Improper Payment Detection/FraudWaste and Abuse Detection achieved Luminary status in Celent’s recently published Insurance Fraud-Detection Solutions: Property and Casualty Insurance, 2024 Edition and Insurance Fraud-Detection Solutions: Health Insurance, 2024 Edition respectively. Celent defines a Luminary as a technology that excels in solution capabilities and demonstrates a leading market presence.
According to the Coalition Against Insurance Fraud, $45 billion in insurance losses recorded by P&C insurers annually are attributed to fraudwith an estimated 10 percent of claims showing evidence of fraudulent activity. Further, It is estimated that fraudwaste, and abuse (FWA) is equivalent to 10% of total healthcare spending per year, or more than $400 billion annually in the US alone. As evidenced by Celent’s recognition, Shift’s fraud detection solutions meet the challenges of insurance fraud head on.
Since its founding in 2014, the company has been harnessing the power of artificial intelligence (AI) to help insurers detect more fraudinvestigate suspicious claims or suspected incidents of fraudwaste and abuse (FWA) more effectively, and settle claims as quickly, accurately and fairly as possible. Beginning in 2020, the company has been at the forefront of using Large Language Models (LLMs) and Generative AI (GenAI) to bring even greater efficiency and accuracy to the fraud detection process. In both reports, Shift’s capabilities in these areas are highlighted as market leading, including support for AI and GenAI powered detection and case management.
“We are pleased to recognize Shift Technology’s ‘Shift Claims Fraud Detection’ and ‘Shift FraudWaste, and Abuse Detection/Improper Payment Detection as Luminary solutions in our Insurance Fraud Detection reports for P&C and Health insurance, respectively,” said Fabio Sarricoanalyst, Research and Advisory, Celent. “Being designated as a Luminary solution signifies that both of Shift Technology’s solutions excel in terms of functionality and technology in Celent’s evaluation, making them a compelling choice for insurers seeking a fraud detection solution in the market.”
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The Celent Insurance Fraud-Detection Solutions: Property and Casualty Insurance, 2024 Edition and Insurance Fraud-Detection Solutions: Health Insurance, 2024 Edition reports provide insurers with an overview of participating vendors’ functionality, customer base, technology, SaaS capabilities, implementation, pricing, and support. Each report also includes the Technical Capability Matrix which places each solution into one of five categories based on the sophistication and breadth of its technology and functionality with Luminary being the highest possible placement.
“Being named a Celent Luminary demonstrates to the insurance industry that Shift possesses the right combination of technical excellence, solution functionality, and the experience and expertise required to help insurers and health plans implement and execute incredibly effective fraud and FWA detection strategies,” stated Jeremy JawishCEO and co-founder, Shift Technology. “The ability to effectively mitigate the impact of fraud on the bottom line is truly a game changer.”
About Shift Technology
Shift Technology delivers AI-powered decisioning solutions to benefit the global insurance industry and its customers. Our products enable the world’s leading insurers to improve combined ratios by optimizing and automating critical decisions across the policy lifecycle. Shift solutions help mitigate fraud and risk, increase operational efficiency, and deliver superior customer experiences. Learn more at www.shift-technology.com.
Contacts:
Rob Morton
Corporate Communications
Shift Technology
+1.617.416.9216
[email protected]
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SOURCE Shift Technology
