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Data-Driven Claims Decisions
Streamline Claims Business Decisions using Predictive Analytics and Big Data Sources
Calvin T Strong, AVPMetLife
AGENDA
Historical Perspective Data Sources / Big Data The Opportunity within Claims Mechanics / How to Start a Program Examples of Success Q&A
3
Data Driven Decisions – History
19th Century Frederick W Taylor Henry Ford
20th Century
Today
DEGREES
OF
INTELLIGENCE
COMPETITIVE ADVANTAGE
BusinessIntelligence
Level of Analytics What’s Possible
Optimization What is the best that can happen?
Predictive Modeling What will happen next?
Forecasting What if it continues?
Statistical Analysis Why is this happening?
Alerts What actions are needed?
Query or Drill Down Where exactly is the problem?
Ad hoc Reports How many, how often, where?
Standard Reports What happened?
Data Degrees of Intelligence
Data Sources - Claims
• Internal Financial Systems
• Internal Quality Programs
• Internal Customer Service Scores
• Internal Claims Management Systems
Big Data Sources
• Vendor Data
• Data Aggregators
• Personal Identifiable Information (PII) Data Providers
• Social Media
Claim Triage Exposure Recognition
Straight Through Processing
The Opportunity
How to Get Started• Identify Pain Points
• Determine Best Approach for Building Your Model
‐In House Data Scientist‐Consultant‐Vendor Solution / Support‐Hybrid
• Establish a Prioritization Governance and Plan
• Establish a Data Extraction Plan
How to Get Started
• Build Your Model
‐Blackboard Characteristics that Drive Results‐Study Relationships between Characteristics‐Determine Top Characteristics to Drive the Model
• Establish a Model Implementation Plan
‐I.T. Resources ‐Pilot Phase‐Full Implementation Phase‐Monitor, Measure, Review and Revise Phase
• Support Culture Change
Success Stories – PIP Straight Through Processing
BusinessRules
Model
Automatically Processed for Payment
Incoming Medical Bills
Incoming Medical Bills
Success Stories – PIP Straight Through Processing
Benefits:
• Bill Payment Cycle Time Reduction of 16 Calendar Days
• Reduced Adjuster Processing Time by 44 Business Days
• Created Capacity for Adjusters to Improve Medical Management
– Increased IME Activity
– Increased EUO Activity
• Supports Growth as the Program Expands
Success Stories – Fraud Recognition
Success Stories – Fraud Recognition
Success Stories – Fraud RecognitionBenefits:
• Industry Leading Referral Ratio ‐ 2.3%
• Industry Leading Impact Ratio ‐ 61%
• Industry Leading Cycle Times – 54 Average Days to Close
• Major Case Unit
– Civil Litigation & Pursuit of Restitution
– NICB Medical Fraud Task Forces
– Law Enforcement Assistance Program
• Strategic Partnerships
– Pre‐Loss Foreclosure Investigations & Premium Fraud
Success Stories – BI Exposure Recognition
Director
Manager
Supervisor
Management Intervention Program Model
Alerts
Unstructured Data
Success Stories – BI Exposure RecognitionBenefits:
• Large Loss Reserve Recognition Improvement of 250 days
• Reduced Long‐Term Prior Year Reserve Development
• Reduction of 40% in Pending Extra‐Contractual Claims
• Partnership with the Reserving Actuarial Department
Other Initiatives in Progress
• Total Loss Recognition @ FNOL
• IME Recognition
• Litigation Optimization
• Quality Boost Camp
Conclusion
Q & A