freedom 2.0—claims automation and mitchell’s intelligent
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Freedom 2.0—Claims Automation and Mitchell’s Intelligent Open Platform
Olivier BaudouxSVP, Product & Artificial Intelligence
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Mitchell’s Approach to Serving the Industry
Strategic PillarsAuto Physical Damage Claims Processing is rapidlychanging as a result of changes in consumerbehavior and advancements in technology. To assistour customers to keep up with changes, Mitchell’sClaim Solution strategy is focused on 4 pillars.
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Gartner Says AI Technologies Will Be in Almost Every New Software Product by 2020
Today, 60% of insurers are investing in AI to improve operational processesINSURANCE | Digital Transformation Remaking an Industry, Accenture
"AI offers exciting possibilities, but unfortunately, most vendors are focused on the goal of simply building and marketing an AI-based product rather than first identifying needs, potential uses and the business value to customers."
Jim Hare, research vice president at Gartner
4 out of 5 companies are actively pursuing investments in AI, with 41% having already deployed the technology.
Artificial Intelligence has become a Must-Have
McKenzie | The Time to Act is Now
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Machine Learning | AI timelineClaims
AutomationSince an early flush of optimism in the 1950s, smaller subsets of artificial intelligence –first machine learning, then deep learning – have created even larger disruptions.
Artificial Intelligence
Machine Learning
Deep Learning
1950s 1960s 1970s 1980s 2000s 2010 2015 2018 CURRENT
Early artificial intelligence stirs excitement.
Machine learning begins to flourish.
Deep learning breakthroughs drive AI boom.
1990s
Source: @Google
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What can machine learning do?
Machine Learning uses data to create models that:
Can adapt to a changing environmentExample: Vehicles never seen before
Classify new data, or make predictionsExample: Image Classification, optimal parts prediction
Provide concise summaries and insightsExample: Cluster estimates, discover accuracy opportunities
Source: @UCSD
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What AI is not? The Magic Pill to Touchless Claims
Mobile First Notice of Loss
Consumer Uploads Photos
Estimate is automatically generated from submitted photos
Consumer receives estimate
Consumer selects repair facilities
Once repair is complete, the repair facility is automatically paid
Telematics Identifies Car Accident
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Our Journey towards Claim Automation
Develop Vehicle Damage Detection
(VDD) AI model
Leverage Computer Vision & Neural
Networks to recognize damage areas through
claim photos
AI-driven Assisted Review
Review parts and labor recommendations based
on computer vision output
Mitchell Intelligent Estimating
Leverage AI solutions to partially or fully
automate the creation of estimates
AI-Driven Smart Solutions
Expand to other capabilities to solve for
other business problems.
e.g. Smart Triage
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Vehicle Damage Detection (VDD)IN
PUTS
Car/No Car
Completed Models
Core Mitchell IP
Mitchell Intelligent Estimating
Panel Detect Damage Detect Operation Parts & Labor
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Strategic Partnership with Google
Mitchell - Google VDD AI Model• Enhance MVDD model to maintain competitive edge• Continuous training to extend model knowledge and
classifiers leveraging Google’s expertise• Expose VDD in new global markets
Google Cloud Platform• Optimization for Google Cloud Platform• Surfaced on Google Marketplace
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Vehicle Damage Detection (VDD)IN
PUTS
Car/No Car
Completed Models
Under-Development
Core Mitchell IP
Panel Detect
Damage Detect
Damage Type
Damage Severity Operation Parts &
Labor
Mitchell Intelligent Estimating
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The Foundations are Rapidly StrengtheningPanels/Components Model Progression over the last 12-months
Front Bumper
Front BumperFront Upper BumperFront Lower Bumper
Right Headlamps Left Headlamps
GrilleUpper Grille
Grille EmblemFront Bumper
Front Upper BumperFront Lower Bumper
Front Reinforcement Bar
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Assisted Review through Computer Vision
Confidence indicated with icon
Desk Reviewers will have the option to “Agree” or “Disagree” with the photo analysis
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Assisted Review – Efficiency & AccuracyUtilize AI to review claim photos and estimate details to flag cases with potential inaccuracies
Efficiency Accuracy
Drive focus towards claims with highest potential opportunities
Ensure the right amount is paid on each claim
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Assisted Review Objectives & Benefits
Maximize Reviewer ThroughputMetric: Show where the final approved estimates aligned with Assisted Review results
Metric: Gauge efficiency gains by Assisted Review categorizing the images and estimate lines by panel for the reviewer
Performance ManagementMetric: Results by estimating resource/shop to identify performance issues and training opportunities
Selecting the Right Estimates to ReviewMetric: Validate results where original version estimates showed Assisted Review exceptions
Identify Estimate InaccuraciesMetric: Measure repair/replace operation exceptions compared to final decision
Measure: Identify additional damage opportunities