hicfg 4 th november 2011 paul yelland consultant id & fraud

1 © 2009 Experian plc. All rights reserved.

Confidential

HICFG4th November 2011

Paul YellandConsultantID & Fraud

Presenter’s name

Experian’s proposed PMI Counter Fraud Solution & Data Pilot

© 2010 Experian Limited. All rights reserved. 2

Sales: $3.9 billion

Profits: $910 million

Market cap: £6.7 billion

In top 50 of FTSE-100

Net Debt: $1.6 billion

Employees: c. 15,000

Offices in 40 countries

Largest markets: UK, US, Brazil

Corporate headquarters: Dublin

Main offices: London, Costa Mesa (US), Nottingham (UK), Sao Paolo (Brazil)

Our businessExperian – a snapshot


Our businessGlobal reach

Experian operates in 40 countries and supports Clients in over 90 countries


Insurance Fraud 2009 - 2010

% of policies / claims processed marked to fraud

Xmas activity peakXmas activity peak

Xmas activity peakXmas activity peak


Up to Date Fraud Statistics


Tools applied at different stages of the insurance process

Customer acquisition MTA Claims Renewal

CUEInsurance investigator

• Fraud investigation

• Single input

• Links addresses

• Bridges databases

• Red/green/amber

Hunter II• Fraud Networks

• Identifies known fraudsters

• Highlights fraud rings

• Fraud case management tool

Market Underwriting Quote accept Cross sell

Change

coverClaim Fraud Trace Renew

1 2 3 4 5 6 7 8 9

• Confirms claims history

• High lights multiple claims

• Meets CRU legislation

• CUE PI e-messaging

Authentication• Verifies Name

• Verifies Address

• Covers Sanctions

7 © Experian Limited 2007. All rights reserved.Confidential and proprietary.

Fraud and Identity SolutionsHelping you answer key questions

Identity

Does this person exist?

Is this person who they say they are?

Is the person a fraudster?

Are they lying to me?

Has the any of the information provided been used to defraud me or anyone else before?

Fraud

Is the information they have provided correct?Are they old

enough?

Are they a risk?

AuthenticationIdentity

Questions

CUE

Hunter

UK Only Product

International Product

UK & US Only Product

* Experian also has a Detect system in Italy

Investigator

© 2009 Experian Limited. All rights reserved.8

Matching to known / suspected fraudsters or fraud intelligence

Fraud profiling

Network Link Analysis

Retrospective matching

Methods of detecting and preventing fraud

Validation of supplied data within application

Checking supplied details for Matches, Inconsistencies & Anomalies against trusted data sources


FSA / SRA Alerts

FSA / SRA Alerts

Client Suspect Files

Client Suspect Files

Insurance Hunter

Insurance Hunter

CCJsCCJs

Victims of FraudVictims of Fraud

Consumer Bank Accounts

Consumer Bank Accounts

Sanctions & PEPS

Sanctions & PEPS

Mail Redirections / NCOA

Mail Redirections / NCOA

Telephone SubscribersTelephone

Subscribers

Suspicious Activity Score

Suspicious Activity Score

Address LinksAddress Links

Consumer Credit Accounts

Consumer Credit Accounts

Previous Credit Applications

Previous Credit Applications

Data assets used for fraud prevention

Mortality RecordsMortality Records

Credit SearchesCredit Searches

National HunterNational Hunter

Electoral Roll Electoral Roll CIFASCIFAS

Mail Drop / Accommodation

Addresses

Mail Drop / Accommodation

Addresses

AVS / CCV2 Check

AVS / CCV2 Check


Hunter II

Most widely used antifraud system in UK Insurance & Banking sectors covering……….. Motor insurance

Household insurance

Pet insurance

Travel insurance

Creditor insurance

12.5m policies and claims processed p.a.

Contains over 65m policies and claims

32,000 known insurance frauds

350,000 known finance frauds


Confidential

Insurance Clients


Confidential

Experian largest UK Financial Service

Provider

Financial Service Clients


Confidential

Experian’s ID & Fraud management solutionWhat is it and what does it do ?

Application Fraud prevention system for Insurance

Fraud protection at

Policy application stage

Claims application stage

(also mid-term policy changes)

Screens for & highlights potentially fraudulent activity

By the insured party / claimant

By service provider

By broker


Confidential

Experian’s ID & Fraud management solutionWhat it will help to find

Types of suspicious / fraudulent activity

Fake & multiple claims Un-bundling of treatments

Multiple policies Up-Coding of treatments

Witheld personal information

Pre-existing conditions Previous claims

Extended treatments

Physio Hospital stay

Fake service providers Extended billing (eg. after death)

Membership fraud (Identity theft) Equipment / medicines not provided *

Tiered billing Collusion between brokers & members

Fraud Rings Providing treatments without accreditation *

Money Laundering High risk territories & groups

eg. Nigeria (Lebanese) eg. Kenya (Indian providers)


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Experian’s ID & Fraud management solutionHow do we know ?

The case for Data Sharing – Proven to work

FACT - Clear evidence that data sharing delivers significant gains for detection of

Higher volumes of fraud

Greater variety of fraud types, trends & patterns

The more data shared (group, national, international) – the more effective it gets

FACT - Insurers targeted by same individuals / criminals / gangs

Share the same data & discrepencies

FACT - Experian’s solution has been industry standard since 2000

Processes > 13m claims / yr

Used most widely in Home & Motor

Equally applicable to Medical Insurance


Confidential

National Hunter

Applications Applications

Frauds Frauds

Cards / Loans Mortgage

Applications

Frauds

Asset Finance

CIFAS CIFAS CIFAS

Data sharing to find fraud in other sectors

Over 350,000 Known Frauds

1,700,00030,000,000 1,300,000

42 clients 39 clients 10 clients

Applications Processed:

Contributors:

Insurance

Hunter

Applications

Frauds

CIFAS

8 clients

12,000,000

40,000 Known Frauds


Confidential

Experian’s ID & Fraud management solutionHow it works

The devil is in the detail – historical evidence

Solution invoked at time of New Policy application or Claim (fully automatic)

Search against all historical policy & claim records (internal & external) & “watchlists” for any connections which may be deemed “suspicious” or “fraudulent”

Checks for Data Inconsistencies & Data Matches which may indicate

Provision of mis-information (eg age)

Witholding of information (eg claims, pre-existing conditions)

Hidden adverse information / other historical conflicts

Fraud Scoring prioritises identified cases (according to % fraudulence)

Enables investigators to review cases

Make judgements ….. Take actions (approve / decline / don’t pay)

Record findings / results / actions …… And to SHARE this information onwards

Prev. Policies & Claims

(From Insurer’s own

& PMI Community)

Experian’s ID & Fraud management solution

Fully hosted solution

High Risk

Data

ID & Fraud Management Solution

Referral

policy rules

Fraud risk Scores

Referrals &case management

Record frauds &suspicions

Fraud networks

Experian’s Data

• >47m Voters Roll• > 200m CAPS • >136m A&A• >330m Address• >95m Detect• + MORE +

Experian’s Data

• >47m Voters Roll• > 200m CAPS • >136m A&A• >330m Address• >95m Detect• + MORE +

Insurance Hunter

• > 5m Policies & Claims

• > 30k known Frauds

Insurer’s Policy Admin

systemOnline Results

(optional)

XML Data Extract

New

Po

licies

New

Claim

s(+

Repeat treatm

ents &

episodes)

CUE

Underwriters

Investigators

Authenticate

Questions• Verify• Validate

Authentication scores

Experian

National Hunter?

CIFAS?


Confidential

Flexible Rules – define your fraud business strategy

Define to the system What we are looking for How to treat Cases

Experian – expertise in rules management consulting Rules Management Service (RMS) Clear data as well as known fraud / suspect

Varied rules palette Inconsistencies

Across databases, claims, personal / corporate / medical details

Anomalies & Data Matches

Trends, patterns & exceptions Patterns indicative of fraud Known frauds & suspects Fraud rings

Fraud scoring prioritises cases

Rules (100’s) Suspect member

Individual / Company

Suspect provider

Suspect broker

Non Disclosure of personal data

Fictitious / falsified parties

Variance to policy / geographical cover

Treatment codes

Abnormal costs

Pre-existing conditions

Multiple / false claims

Multiple policies

Same phone

Same bank details

Fraud rings

Known fraud Intelligence

Suspect / fraudster

Rules (100’s) Suspect member

Individual / Company

Suspect provider

Suspect broker

Non Disclosure of personal data

Fictitious / falsified parties

Variance to policy / geographical cover

Treatment codes

Abnormal costs

Pre-existing conditions

Multiple / false claims

Multiple policies

Same phone

Same bank details

Fraud rings

Known fraud Intelligence

Suspect / fraudster

Key Features

Data Services - Automated Cross-Matching

Own data

Historic insurance policy and claims (Insurer’s own)

PMI community shared data

Historic Insurance policy and claims (other PMI’s data)

High Risk database – Private User Group

Historic “watchlist” database of known suspicious / fraudulent health insurance policies and claims

Insurance Hunter

Insurance frauds (non Health)

Historic insurance policy and claims (non Health)

National Hunter

UK banking and retail National Frauds

CUE

Motor and Home historic claims data

Referrals / Case Management

Automated Referral Management

Full Match Information

For all instances of data inconsistency, anomaly or presence on a “watch-list”

Fraud Investigation Platform

Full referral management using intelligent workflow

Policy rules & scoring determine prioritisation of cases to investigations team

Tailored to Insurer’s requirements & operational set-up

Industry leading workbench functionality

User screens & dedicated functionality

Notes making facilities

Automatic updates (own & external databases)

Perpetuates data-sharing cycle

Fraud ring analysis (using I2)

Numbers of apparently valid claims which have suspicious connections


Confidential

Key benefitsKey benefits

Significant reduction in losses due to unethical / criminal / fraudulent activity

• Consequential uplift in profitability

• Improve competitive stance from a premium perspective

Improve levels of customer service, risk management and control over policy

Ensure SI unit are focussed on the cases most likely to be fraud

Additional recording & sharing of data improves effectiveness YoY

Typical ROI to Insurance Clients

Product Data sharing Own data only

Overall 22:1 12:1


Confidential

Paul Yelland

Consultant

Identity & Fraud

[email protected]

07973 799 448

hicfg 4 th november 2011 paul yelland consultant id & fraud

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