Jerry Chetty - Myth About Data Investigation
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This document discusses fraud investigations in industries that handle large amounts of data. It notes that fraudsters use big data to conceal fraud and that data-driven investigations can uncover more fraud than traditional methods. The document describes how one insurance company used data analysis to uncover over $1 million in fraudulent claims from an individual and department that were not discovered through traditional investigations. It advocates for combining investigative skills with data analysis skills and having access to industry data sets to more effectively investigate fraud in data-heavy industries.
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Jerry Chetty - Myth About Data Investigation
- 1. THE WORLD WE LIVE IN Speaker 3 of 17 Jerry Chetty @4JerryC Myths About Data Investigation Followed by Gary Hope
- 2. Facts about fraud • Fraudsters do not discriminate • No organisation is immune from fraud • It’s not about if, but rather when • Fraudsters love big data – the more, the merrier! They use big data to camouflage their fraud!!!!
- 3. Investigations in data heavy industries INDUSTRIES WHO CARRY AND PROCESS BIG DATA The following are some examples: • Banks • Telecommunications • Retailers • Insurers • Government departments
- 4. Cost of insurance fraud NO ACCURATE MEASURE OF INSURANCE FRAUD The following are some of the calculations/estimates: • Internationally insurance fraud = 7-15% of gross written premiums • 2011 UK insurance fraud = 1billion pound, ABI (2012) • UK – fraudulent claim exposed every hour LOCALLY: • SAIA says 10% of claims amount contains an element of fraud = R2-3billion
- 5. Insurance process flow chart: Structured & Unstructured Data (250 million lines of data) 4. CLAIMS PROCESS SOS INTER-MEDIARY FALSE CLAIMS INFLATED CHANGING CIRCUMSTANCES OF CLAIMS BACKDATING OF COVER SUBMIT FALSE CLAIMS ON CLIENTS POLICY 2. ISSUE POLICY 3. PAY PREMIUM DEBIT ORDER (D/ O) INTER-MEDIARY THEFT OF PREMIUMS CONTRAVENTION OF S45 of STI 1. SELL COVER CONTAC T CENTRE SANTAM MANDA-TED INTER-MEDIARY PREVIOUS CLAIMS SECURITY REQUIREMENTS UNDERWRITING FRAUD FRAUD MATERIAL AFFECTS FACTS PREMIUM UNDERWRITING FRAUD 5. ASSESOR INTERNAL EXTERNAL 6. SERVICE PROVIDER CORRUPTION FALSE INVOICES INFLATED REPAIR COSTS (FALSE CLAIMS) INFERIOR REPAIRS SUPPLIER FRONTING
- 6. Imagine doing an investigation here
- 7. Who would you employ?
- 8. Sherlock Holmes VS. Data mentalist
- 9. Life is all about how we see things
- 10. Physical evidence VS. Evidence in data
- 12. Insurance process flow chart 4. CLAIMS PROCESS SOS INTER-MEDIARY FALSE CLAIMS INFLATED CHANGING CIRCUMSTANCES OF CLAIMS BACKDATING OF COVER SUBMIT FALSE CLAIMS ON CLIENTS POLICY 2. ISSUE POLICY 3. PAY PREMIUM DEBIT ORDER (D/ O) INTER-MEDIARY THEFT OF PREMIUMS CONTRAVENTION OF S45 of STI 1. SELL COVER CONTAC T CENTRE SANTAM MANDA-TED INTER-MEDIARY PREVIOUS CLAIMS SECURITY REQUIREMENTS UNDERWRITING FRAUD FRAUD MATERIAL AFFECTS FACTS PREMIUM UNDERWRITING FRAUD 5. ASSESOR INTERNAL EXTERNAL 6. SERVICE PROVIDER CORRUPTION FALSE INVOICES INFLATED REPAIR COSTS (FALSE CLAIMS) INFERIOR REPAIRS SUPPLIER FRONTING
- 13. Our case study – Investigating in numbers ELECTRONIC FUNDS TRANSFER FRAUD • R22 000 only one incident • Sufficient evidence to prove this • Great case solved! • Or is it? • Enter Santam Sherlock Holmes and Data Mentalist • Extract claims data processed by alleged fraudster = 20 000 lines (Overwhelming) • Traditional analysis = Investigation = zero results (Frustration) • Profile existing fraudulent transaction and alleged fraudster • Refine analysis = Investigation = What’s in a surname? = R1.4m DOES LIGHTNING STRIKE IN THE SAME PLACE TWICE? • Extract claims data for entire department = 60 000 lines • Analysis = Investigation = R1.2m fraud
- 14. Learning's • Huge opportunity for using data in investigations - Uncover more fraud - Provides most accurate financial impact of fraud incident - Develop detective and proactive anti fraud strategies • Results from any form of data analysis does not prove FRAUD • Still need hard-core investigations • Having an inventory of data sets • Need the skill of both an investigator and the data mentalist – collaborative effort • Using one person to execute both functions is NOT a collaborative effort • Data heavy is the way of the future – need to embrace its usefulness FRAUDSTERS DO – THEY UNDERSTAND THE USEFULNESS OF BIG DATA AS A MEANS OF CONCEALMENT FOR THEIR ACTIVITIES!
- 15. Insurance process flow chart 4. CLAIMS PROCESS SOS INTER-MEDIARY FALSE CLAIMS INFLATED CHANGING CIRCUMSTANCES OF CLAIMS BACKDATING OF COVER SUBMIT FALSE CLAIMS ON CLIENTS POLICY 2. ISSUE POLICY 3. PAY PREMIUM DEBIT ORDER (D/ O) INTER-MEDIARY THEFT OF PREMIUMS CONTRAVENTION OF S45 of STI 1. SELL COVER CONTAC T CENTRE SANTAM MANDA-TED INTER-MEDIARY PREVIOUS CLAIMS SECURITY REQUIREMENTS UNDERWRITING FRAUD FRAUD MATERIAL AFFECTS FACTS PREMIUM UNDERWRITING FRAUD 5. ASSESOR INTERNAL EXTERNAL 6. SERVICE PROVIDER CORRUPTION FALSE INVOICES INFLATED REPAIR COSTS (FALSE CLAIMS) INFERIOR REPAIRS SUPPLIER FRONTING
- 16. Hiding within those mounds of data is knowledge that could change the life of a patient, or change the world.” Atul Butte, Stanford School of Medicine “Without big data, you are blind and deaf in the middle of a freeway” Geoffrey Moore, management consultant and theorist “Information is the oil of the 21st century, and analytics is the combustion engine.” Peter Sondergaard, Gartner Research