1 / 22

HICFG 4 th November 2011 Paul Yelland Consultant ID & Fraud

Experian’s proposed PMI Counter Fraud Solution & Data Pilot. HICFG 4 th November 2011 Paul Yelland Consultant ID & Fraud. Presenter’s name. Our business Experian – a snapshot. Sales: $3.9 billion Profits: $910 million Market cap: £6.7 billion In top 50 of FTSE-100 Net Debt: $1.6 billion

amma
Download Presentation

HICFG 4 th November 2011 Paul Yelland Consultant ID & Fraud

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Experian’s proposed PMI Counter Fraud Solution & Data Pilot HICFG4th November 2011Paul YellandConsultantID & Fraud Presenter’s name

  2. Our businessExperian – a snapshot • 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)

  3. Our businessGlobal reach Experian operates in 40 countries and supports Clients in over 90 countries • Argentina • Australia • Austria • Belgium • Brazil • Bulgaria • Canada • Chile • China • Costa Rica • Czech Republic • Denmark • Estonia • Finland • France • Germany • Greece • Hong Kong • India • Ireland • Italy • Japan • Malaysia • Mexico • Monaco • Morocco • Netherlands • New Zealand • Norway • Poland • Russia • Singapore • South Africa • South Korea • Spain • Sweden • Taiwan • Turkey • United Kingdom • United States

  4. Insurance Fraud 2009 - 2010 • % of policies / claims processed marked to fraud Xmas activity peak Xmas activity peak

  5. Up to Date Fraud Statistics

  6. Renewal Claims Customer acquisition MTA Insurance 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 Tools applied at different stages of the insurance process 1 2 3 4 5 6 7 8 9 Market Underwriting Quote accept Cross sell Change cover Claim Fraud Trace Renew • Authentication • Verifies Name • Verifies Address • Covers Sanctions • Confirms claims history • High lights multiple claims • Meets CRU legislation • CUE PI e-messaging CUE

  7. UK Only Product International Product Fraud and Identity SolutionsHelping you answer key questions UK & US Only Product Fraud Identity Does this person exist? Is the information they have provided correct? 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? Are they a risk? Are they old enough? Authentication Identity Questions CUE Hunter Investigator * Experian also has a Detect system in Italy

  8. Matching to known / suspected fraudsters or fraud intelligence Fraud profiling Network Link Analysis Retrospective matching Methods of detecting and preventing fraud Scoring Own / Group / Consortia • Validation of supplied data within application • Checking supplied details for Matches, Inconsistencies & Anomalies against trusted data sources

  9. Data assets used for fraud prevention Credit Searches Electoral Roll AVS / CCV2 Check CIFAS Mail Drop / Accommodation Addresses Previous Credit Applications Mortality Records National Hunter Consumer Credit Accounts Telephone Subscribers Consumer Bank Accounts Insurance Hunter Address Links Victims of Fraud Client Suspect Files Mail Redirections / NCOA Suspicious Activity Score Sanctions & PEPS CCJs FSA / SRA Alerts

  10. 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 insurancefrauds • 350,000 known finance frauds

  11. Insurance Clients

  12. Daily News Experian largest UK Financial Service Provider Financial Service Clients

  13. 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

  14. Experian’s ID & Fraud management solutionWhat it will help to find Types of suspicious / fraudulent activity

  15. 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

  16. Data sharing to find fraud in other sectors Over 350,000 Known Frauds 40,000 Known Frauds Insurance Hunter National Hunter CIFAS CIFAS CIFAS CIFAS Frauds Frauds Frauds Frauds Applications Applications Applications Applications Cards / Loans Mortgage Asset Finance Applications Processed: 12,000,000 30,000,000 1,700,000 1,300,000 8 clients 42 clients 39 clients 10 clients Contributors:

  17. 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

  18. Experian’s ID & Fraud management solution New Policies Insurance Hunter • > 5m Policies & Claims • > 30k known Frauds Experian’s Data • >47m Voters Roll • > 200m CAPS • >136m A&A • >330m Address • >95m Detect • + MORE + New Claims (+ Repeat treatments & episodes) Insurer’s Policy Admin system XML Data Extract CUE Referrals & case management Online Results(optional) High Risk Data Underwriters Authentication scores Fraud networks Authenticate Questions Record frauds & suspicions • Verify • Validate Investigators Experian ID & Fraud Management Solution Prev. Policies & Claims (From Insurer’s own & PMI Community) Referral policy rules Fraud risk Scores National Hunter? CIFAS? Fully hosted solution

  19. 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 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

  20. 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

  21. Key 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

  22. Paul YellandConsultantIdentity & Fraudpaul.yelland@uk.experian.com07973 799 448

More Related