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