IBM Counter Fraud Signature Solutions

Transcription

1 IBM Counter Fraud Signature Solutions November 5th, 2013 Athens Carmen Ene, VP IBM Global Business Services, Europe Leader Counter Fraud & Financial Crimes

2 Provider ID Theft o Claim for routine services is submitted by Dorsey Med Group located at 2625 Piedmont Road Northeast, Suite o The provider is listed as Dr. Harry Dorsey, a licensed internist in the State of Georgia o Dorsey is a respected physician with 39 years of experience. o However 2

3 Provider ID Theft o 2625 Piedmont Road Northeast, Suite is a UPS Store mail box o Dr. Harry Dorsey s practice in Albany Georgia miles away o The business was incorporated by Olga Teplukhina who also applied for the NPI o When contacted, Dr. Dorsey did not have any knowledge of Dorsey Med Group 3

4 Excessive Units o Provider submits a claim for a patient suffering for post surgical nausea consisting of 200 units of Tigan (HCPCS J3250) o One "unit" of Tigan is 200mg o The maximum daily dosage is 800mg per day (4 units) o This could be a mistake that happens as the result of confusion over the dosage (200mg) versus units o Typical dosage cost is less than $10 o However 4

5 Excessive Units o One provider was identified as an outlier that billed every instance at 200 units o In most cases, the provider is paid approximately $900 per dose (versus $10 per dose, which is normal) o Some patients had multiple visits - as many as 70 in one quarter o Over a period of 10 months, the provider received approximately $2,000,000 related to the alleged administration of Tigan Member DOS HCPCS Description Units Paid J3250 Trimethobenzamide 200 $900 5

6 Geospatial and Cluster Analysis o We uncovered abnormal billing related to HCPCS code E0172 (Seat lift mechanism placed over or on top of toilet) o The behaviors we identified were material, distinct, and by definition, anomalous o Total disbursements for this device exceed $230,000 for the period of January-July 2011 o Payments were highly concentrated for a large number of patients in a remote regional in Texas o The listed addresses were highly suspect and consisted of a video store, a deserted home, and an empty strip mall 6

7 IBM is seeing an increase in fraud that is expected to continue. We anticipate greater focus on fraud as a potential compromise in closing budget gaps 1. Crime rings are increasingly turning to fraud Fraud is low risk and relatively easy to conduct Medical claims are path to revenue for fraudsters 2. Economic downturns lead to greater fraud and abuse Individuals and businesses seek new ways to make ends meet 3. Market conditions pressuring our public and private bottom line Need to find new sources of savings 4. Advances in analytics are make finding and preventing fraud both possible & economical We can now do what we previously couldn t Survey participants estimated that the typical organization loses 5% of its revenues to occupational fraud each year The median loss caused by the occupational fraud cases in our study was $140,000 20% of the cases were greater than 1M The frauds reported to us lasted a median of 18 months before being detected 7

8 This new era is reshaping the IT landscape and creating new market dynamics The new era is driving the IBM Counter Fraud strategy Cloud Mobile Social Internet of Things 8 SEPTEMBER, 2013

9 Helping our customers become a Hard Target Predict and Protect Disrupt and Defeat Prosecute and Recover Learn and Apply 9

10 Fraud (aka Improper Payment or Program Integrity) is a deliberate misrepresentation or deception intended to result in financial gain. Fraud is a criminal act. Abuse refers to similar actions not proven to be criminal. Financial Crimes includes Anti-money laundering and cyber-risk primarily for banking Organized rings conducting sophisticated attacks against corporations for producing financial gains Staged Events Money Laundering Improper Billing Improper Payments Providers taking advantage of public and private institutions for the purpose of improper financial gain Organized Opportunistic Individuals seeking improper payments by taking advantage of private and public institutions Slip Fall Arson Tax Fraud Medical Fraud Procurement Financial Statement Expense Employees creating fraudulent transactions, records, and claims to receive improper payments from Employers 10

11 Anatomy of a Complex fraud 11

12 IBM s Counter Fraud solution reduces improper payments using a layered best of breed approach to disrupt the intentions of both organized and opportunistic fraudsters Detect in real time if a medical bill or other transaction is fraudulent by applying models and rules in real time to determine the propensity for fraud Apply the results of Detection to stop processing known fraud, or encourage fraudsters to abandon their objective by showing more is known than they think should be known Predict & Protect Detect Detect fraud within a business process Prevent Take action in real time when it matters Disrupt & Defeat Prosecute & Recover Investigate Confirm fraud for prosecution, recovery, rules and watch lists Fraudster Discover Find fraud within the data Learn & Apply 12 Gather data about DETECTED or DISCOVERED fraud; build cases for prosecution, recoveries, or denial of payments. Provide feedback to DETECTION and/or DISCOVERY Discover fraud retrospectively by reviewing past data and looking for patterns and anomalies that may indicate an individual or organization is potentially fraudulent

13 Counter-Fraud solutions must provide a layered approach by leveraging multiple analytical techniques Entity Analytics Predictive Analytics Forensic Analysis Content Analytics Retrospective Analysis 13

14 IBM Fraud Solution Framework Operational Systems Advanced Industry Libraries: Data Models, Predictive Models, Rules, Reports, Process, External Fraud Data and so on Real Time / In line Prevention Detection Back Office Analytics Discovery Investigation Reporting Integration Action Guidance Rules Predictive Analytics Rules Decision Management Selection Evaluation Anomalies Identification Case Management Relationship Visualization Investigative Analytics Operational Reporting Dashboards Feedback Observation Space Information Domains Internal Sources External Sources Evolving Unstructured Sources Fraud Use Case Libraries 14

15 IBM Technology Operational Systems Advanced Industry Libraries: Data Models, Predictive Models, Rules, Reports, Process, External Fraud Data etc. Real Time / In line Prevention Detection Back Office Analytics Discovery Investigation Reporting Integration Action Guidance Rules Predictive Analytics Rules Decision Management Selection Evaluation Anomalies Identification Case Management Relationship Visualization Investigative Analytics Operational Reporting Dashboards Feedback Observation Space Information Domains Internal Sources External Sources Evolving Unstructured Sources Fraud Use Case Libraries 15

16 IBM Counter Fraud Solution Form, Bill, Claim Application, and so on Entity Analytics Detection Discovery Applicant Business Rules Predictive Model Claimant Entity Analytics Optimize Fraud Decisions Anomaly Detection 9,500 model library Selection Evaluation Identification Real Time Alert Provider New Investigation Observation Space Case Management Intelligent Investigation Intelligent Fraud Dashboards 16

17 Public story: Fraud detection at Alameda County Social Services Challenge: Case workers were confronted with: Applicants applying for public assistance who were not adequately screened prior to enrollment Applicants receiving benefits that were noncompliant for several months to year Administrative caseload burdens of per worker, reducing their ability to spend time with clients Solution: Alameda County implemented a new Social Services Integrated Reporting System (SSIRS) powered by IBM InfoSphere Identity Insight, IBM BI Data Warehouse and Cognos Reporting,Charting, and Dashboarding Services were provided by IBM 200 Concurrent Users interact with SSIRS through web enabled interfaces Business Benefits: ROI: 631%, Payback 2 months, $24M annual benefit Bring together data on child welfare system clients from multiple payment and case management systems Decrease false positives and negatives and reduce investigation time for increased fraud ROI - Investigators now receive high ROI case alerts - Workers are alerted to child and adult endangerment, double dipping, and fraudulent representation - Investigators receive relationship information immediately

18 Banking story: Preventing fraud at MoneyGram MoneyGram Since the tool launched in May 2010 as part of MoneyGram s efforts to enhance its global consumer anti-fraud program, MoneyGram has prevented thousands of fraudulent transactions, saving its customers about $22.5 million. Business Wire 03/09/11 18

19 Insurance story: Claim fraud detection at Santam Insurance in South Africa South Africa s largest short-term insurance company uses predictive analytics to uncover a major insurance fraud syndicate, save millions on fraudulent claims and resolve legitimate claims 70 times faster than before. Solution Business Opportunity Like most insurers around the world, Santam was losing millions of dollars paying out fraudulent claims every year. Expenses were being passed on to the customer in the form of higher premiums and longer waits to settle legitimate claims. To improve its bottom line and enhance customer satisfaction, the company needed to detect and stop insurance fraud early in the claims process. It also needed to find a way to isolate risky, fraudulent claims so that claims managers could more quickly process lower-risk claims. Gained the ability to spot fraud early with an advanced analytics solution that captures data from incoming claims, assesses each claim against identified risk factors and segments claims to five risk categories, separating higher-risk cases from low-risk claims. Plans to use propensity modeling to enhance and refine segmentation process as more data becomes available Results Identified a major fraud ring in less than 30 days after implementation. Saved more than $2.5M in payouts to fraudulent customers, and nearly $5M in total repudiations. Reduced claims processing time on low-risk claims by nearly 90%. Cut operating costs by reducing the number of mobile claims investigations.

20 IBM Counter-Fraud and Financial Crime Signature Solution An unparalleled combination of integrated capabilities, delivery experience, and business expertise with a proven ability to deliver business outcomes Learn and Apply Prosecute and Recover Disrupt and Defeat Predict and Protect 20

21 Predictive Police 21

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