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CCC Uses a Single Photo to Usher in New Era of Smart Claims

Artificial Intelligence (AI) Comes to Life in CCC Smart Total Loss™ Solution, Improving Accuracy, Expediency for Total vs. Repair Decision

 (PRNewsfoto/CCC Information Services Inc.)

News provided by

CCC Information Services Inc.

Oct 16, 2017, 09:00 ET

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CHICAGO, Oct. 16, 2017 /PRNewswire/ -- CCC Information Services Inc. (CCC) introduced today its CCC Smart Total Loss™ solution, an AI-powered claims solution that uses and analyzes a single photo to help auto insurers predict a vehicle total loss in seconds, with superior accuracy, and without human intervention. CCC Smart Total Loss uses deep learning algorithms to help predict the most effective appraisal method for insurers, which improves triage decisions that can reduce related expenses and reduce the disruption caused by total loss vehicles at repair shops. CCC, the automotive claims leader who first went into production with machine learning capabilities in 2011, is now in market trials with carriers testing the first integrated solution that combines digital technology with powerful AI to bring decision-making precision and a streamlined experience to claims processing.

"Claims that require little-to-no human intervention are an ambitious goal and one that needs to be approached intelligently and with the betterment of the industry, its participants, and consumers in mind," said Barrett Callaghan, GM and SVP, Insurance Services Group, CCC. "The introduction of CCC Smart Total Loss is the first tangible step on a journey toward truly intelligent claims. CCC has processed more than 180 million automotive claims, and our work in AI and deep- and machine-learning has been persistent and ongoing for nearly a decade. Not every claim can be fast-tracked, but through technology expertise, and deep claims insight, we can achieve a greater level of efficiency, quality, and service experience that is demanded in today's digital and consumer-centric environment."

CCC Smart Total Loss will be available for deployment in standalone mobile apps or integrated into insurers' mobile experiences.  Users upload their photo - as instructed by their insurer - and have that photo analyzed by CCC's powerful AI engine. Smart Total Loss instantly analyzes damage against like photos, matching in make, model, year, and damage-type, returning a real-time response. Smart Total Loss is part of CCC Smart Claims™, a rapidly growing suite of intelligent claims management solutions.  Smart Total Loss is powered by the CCC ONE® platform and is designed to be integrated into the workflow of the more than 350 carriers and 24,000 shops that use the platform today.

Learn more about the CCC Smart Total Loss solution.  

About CCC
CCC, together with its affiliates, combines strategic foresight, dynamic partnerships, and smart technology to power its customers forward. Founded in 1980, CCC is a leading provider of innovative cloud, mobile, telematics, hyperscale technologies and apps for the automotive, insurance, and collision repair industries.  CCC's solutions and big data insights are delivered through the powerful CCC ONE™ platform, which connects a vast network of 350+ insurance companies, 24,000+ repair facilities, OEMS, hundreds of parts suppliers, and dozens of third-party data and service providers.  In addition, CCC provides access to car-related services to millions of consumers via carwise.com, and Auto Injury Solutions Inc., a CCC company, provides customizable, end-to-end, casualty solutions to auto insurers for the handling of first and third-party claims. The collective set of CCC's smart, flexible, and intuitive solutions make connected car, vehicle, and accident data actionable, informing decision-making, enhancing productivity, and helping customers deliver faster and better experiences for end consumers.  Learn more about CCC at cccis.com.

CCC and the CCC logo are registered trademarks, and CCC ONE is a trademark, of CCC Information Services Inc.

SOURCE CCC Information Services Inc.

Related Links

http://www.cccis.com

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