Customer Experience Management in the Insurance P&C Industry

Attensity Webinar Series

With James Purchase, Senior Director of Industry Solutions, Attensity

#AttensityWebinar

Introduction to Attensity

Insurance P&C - High Loss Ratio Challenge

Insurance P&C - Benefits of Unstructured Claims Analytics

Use Cases:

Detection of Fraudulent Claims

Accurate Identification of Subrogation

Enhanced Claims Analysis

Survey Verbatim Analysis

Member/Non-Member Review Analysis

External vs. Internal Review Analysis

Social Media Buzz & Sentiment

Insurance P&C Solution Deliverables – Summary & Conclusions

Q&A

Agenda

10+ years of experience in Text Analytics/CEM

7 patents in natural language processing

500+ installations worldwide

World’s largest NLP development group

Help the world’s leading brands leverage

customer conversations as a business asset. No matter where they take place: social media • blogs • surveys • call center notes • review sites • emails • more

About Attensity

We Work with the World’s Leading Brands

Customer Service

BI Text Analytics VOC

SCRM

Attensity Social Analytics and Engagement Suite

Real-time annotated social media data feed: 75+ million social and online sources

ATTENSITY COMMAND CENTER

ATTENSITY PIPELINE

ATTENSITY ANALYZE Deep sentiment, root cause analysis and trending

ATTENSITY RESPOND Social customer engagement solution

Enriches and tags the data Extracts people, places, things, events

Plus internal sources: emails, surveys, CRM notes, etc

Includes out of the box:

Industry specific Dashboards, Reports, Categories, Topics

Patented semantic analysis for extracting detailed insights from text

Sentiment and root cause analysis

Trend analysis

Continuously updated social media feed & market intelligence

Point and click wizard for creating custom reports & dashboards

Built on Attensity Analyze: First Text Analytics Solution Designed for Business Users One of a series of industry solutions

Insurance Industry Solution

Most property and casualty (P&C) insurers ended 2011 with dismal financial results, with many insurers experiencing year-over-year deterioration.

Carriers are looking for ways to correct the High Loss Ratio!

P&C Industry - High Loss Ratio Challenge

80% of all claims data is unstructured, which makes spreadsheet analysis of standard data ineffective.

Claims analysis of unstructured data can drive major financial improvements in areas such as:

Fraud

Subrogation

Provider Network Management

Insurance P&C - Benefits of Unstructured Claims Analytics

Source:

Use Case: Improving Detection of Fraudulent Claims

UK National Fraud Authority estimates £2 billion in fraud annually.

10% of all US P&C claims are fraudulent – representing over $40 Billion of cost to the industry

Industry best practice finds fraud in 1 to 3% of claims

The Claim Adjuster workforce is aging: 70% is over 45 years old – knowledge and experience is leaving the industry

Average claim settlement times are too long, driving loss and adjustment expense higher

Use Case: Improving Detection of Fraudulent Claims

Appropriate Claim Examiner

SIU

Supervisor

Other

Intelligent Workflow All data is

fused together

All claims are analyzed

Claims are assigned to 1

of 4 tiers

Workers Compensation General Liability Auto

Claims Administration Straight through processing

Claims Database Text Sources Social Media Email

Dictionaries

Use Case: Improving Detection of Fraudulent Claims

Score

Tier 4

Tier 3

Tier 2

Tier 1

Actionable Claims

No Suspicion

High Suspicion

Tier 1 claims in this tier show no suspicion and should be fast tracked

Tier 2 claims in this tier show minimal signs of suspicion and may require analysis

Tier 3 claims in this tier show stronger signs of suspicion and should be analyzed

Tier 4 claims in this tier are highly suspicious and should be referred to SIU

Tiered Claims

Fused claim records:

Claims enter the funnel using filtering options to identify claims to be processed

Use Case: Improving Detection of Fraudulent Claims

Reduced costs Addressing fraudulent claims earlier in the process reduces the overall claims cost.

Training Text analysis uncovers inconsistent use of red flags across claim examiners and identifies training opportunities.

Improved regulatory compliance

Analysis of text identifies suspicious claims not reported to state agencies.

Knowledge capture Allows for the capture of fraud intelligence and the consistent application across claims. Provides a hedge against loss of knowledge .

Use Case: Improving Detection of Fraudulent Claims

Provides a cumulative view of claims. In this example over 50% of claims are characterized as : Neck, Back, Shoulder, Arm & Knee injuries!

Claims Details provides additional information such as Gender, Age, Health Profile…

Many Red Flag Indicators are publically known but many are specific to a product/carrier and others continue to emerge! This shows a breakout of the highest occurring flag indicators.

The presence of multiple Red Flag Indicators can lead to Fraud “Tiers”. The more indicators present the more suspicious the claim!

Drilling into this claim which is a Tier 3 we see the presence of 4 indicators!

Given that this is a Tier 3 claim we can update the status as “Sent to SIU”

Subrogation is the process whereby one insurance company, whose customer was not at fault, recoups paid claims from the company of the individual responsible for the accident.

Each individual state has unique rules and regulations around what constitutes “fault.”!

For most insurance organizations, subrogation is something less than a science.

Goal to quickly ascertain high priority to low priority of successful subrogation

Use Case: Accurate Identification of Subrogation

Use Case: Accurate Identification of Subrogation Attensity extracts Entities like BODY_PART, CLAIM_ROLE & INJURY but what about relationships in text?

Attensity also gets to Subrogation and Root Cause: “insured vehicle : broadside : other vehicle” “burn from airbag”

Use Case: Enhance Claims Analytics

Claims Supervisors can glean intelligence about time-intensive steps and consider ways of improving claims processing efficiency

Use Case: Enhanced Claims Analytics

Older claims may involve multiple Adjusters. Individual Claims Adjusters can review chronological order of claims

Members can provide feedback on themes such as Service, Attrition, Product, Brand

Indirectly there may be feedback on “Service Provider Networks” including

Body Shops

Auto Repair Facilities

Vehicle Rentals

Legal Services

Medical Providers.

Use Case: Survey Verbatim Analysis

Use Case: Survey Verbatim Analysis

Relatively higher Negative sentiment towards Property Claims process versus Auto Claims process

Poor communication/Follow-Up is common to both lines of business

Negative feedback on Property claims centered on “Policy Coverage complaints”, “Poor Explanations” “Claim Process Slow”

Auto Claim complaints are more centered around “Appraisals/Estimates Inaccurate” “High Or Increased Rates”

Common Positive Sentiment towards both lines of business includes: “Performed Job Well” “Helpful, Responsive”

Can review surveys for feedback on Service Network Providers. Based on quantity of feedback, there may be opportunities for expanding networks…

Within most industries Member/Non-Member reviews are an increasingly important component of “Word of Mouth” marketing

Review sites controlled or facilitated by a carrier may tend to be more positive in nature!

Use Case: Member/Non-Member Review Analysis

Reviews of USAA insurance products and services were analyzed by 3 lines of business: Auto, Home and Rental.

Use Case: Member/Non-Member Review Analysis

Reviews for Home insurance is significantly more Negative than Auto or Rental

Lots of Negativity towards “premium”

Use Case: Member/Non-Member Review Analysis

Drilling down into Auto Reviews we actually see some Churn Threats!

These reviews can be routed and responded to via Attensity Respond!

Use Case: External vs. Internal Review Analysis

Specifically members/non-members are complaining more about Service issues

Carriers that have a Social Media Engagement strategy are better placed to engage with members!

External reviews show more negativity

Use Case: Social Media Buzz & Sentiment

This report tracks Share of Voice across Carriers

Despite a lot of Negativity towards Marketing (commercials), YTD there is more positivity

This tag cloud track overall specific complaints across industry.

This report tracks overall Sentiment across carriers…

Use Case: Social Media Buzz & Sentiment

These reports provide a high level and detailed view of Sentiment across the entire industry!

Use Case: Social Media Buzz & Sentiment

Through the use of Hotspots, Attensity can track new Product Launches, Marketing Campaigns , Customer Service and many other themes

Use Case: Social Media Buzz & Sentiment

Distribution of Social Media Content Type By Carrier!

Use Case: Social Media Buzz & Sentiment

Sentiment by Social Media Channel!

Packaged Insurance P&C Dictionaries, Topics, Categories, Reports & Dashboards

Tiered-Fraud approach – tiering of claims based on years of human intelligence versus statistical and probability-based scoring

Higher degree of accuracy – industry leading Text Analytics engine enables a scoring approach that significantly reduces false positives and negatives

Easily configurable dashboards

Over 100 OOB dashboard reports across Fortune 500 Carriers

Daily extractions of all Social Media data (real-time available if needed)

Insurance P&C Solution – Summary & Conclusions