SAS Fraud Framework for Banking

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "SAS Fraud Framework for Banking"

Transcription

1 SAS Fraud Framework for Banking Including Social Network Analysis John C. Brocklebank, Ph.D. Vice President, SAS Solutions OnDemand Advanced Analytics Lab

2 SAS Fraud Framework for Banking Agenda Introduction to SAS Fraud Framework SAS Fraud Framework Demo Preliminary Results 2

3 Starting with the SAS Fraud Framework Increasing Fraud: The Business Problem Fraudsters Far more sophisticated organized crime, patient, sharing of rules Engaging insiders to understand detection environment High velocity of attacks disappear after 2-3 transactions Hitting multiple channels and industries at the same time Continuously evolving fraud strategies Current Fraud Systems Systems are silo d by line of business Current systems act on transaction or customer Rules and predictive models have limitations No sharing of data Rely on 3 rd party systems No real proactive steps taken to combat 1 st Party Fraud Evidence insufficient to act upon 3

4 SAS Fraud Framework Innovation in Detection Driven by Industry Robust and Flexible Framework Capabilities Support for real-time, intra-day, batch execution Ability to use existing data infrastructure Ability to use existing fraud alert output from any LOB / 3 rd party Business intelligence for all levels of users Support for Business Functions Provide strategic insight into threats, trends, risks Enterprise view of fraudulent behavior Rapidly test, simulate, and deploy models/rules without dependence on IT Ability to provide single view for investigators Phased Approach to Support Tactical and Strategic Initiatives 4

5 SAS Fraud / Social Network Analysis Vision Banking Insurance Health Care Government 1 st / 3 rd Party Fraud Warranty Medical Fraud Medicare / Medicaid (DME) Fraud Telco Account Fraud Internal Fraud Auto and Auto P&C Fraud Dental / Vision Fraud Social Social Services Fraud Contagious Social Services Churn Card (Credit & Debit) Worker s Comp Fraud Prescription Drug Fraud Tax Evasion Householding/ Campaign Marketing Credit Risk Life Insurance Fraud Program Evasion AML Policy Pricing / Premium Evasion Law Enforcement Detection and Alert Generation Fraud Framework Alert Management Social Network Analysis Case Management Business Analytics Framework Business Intelligence Data Integration Analytics Storage 5

6 SAS Fraud Framework Using a Hybrid Approach for Fraud Detection Operational Data Sources Suitable for known patterns Suitable for unknown patterns Suitable for complex patterns Suitable for associative link patterns Customer Account Rules Anomaly Detection Predictive Models Social Network Analysis Transaction Applications Rules to filter fraudulent transactions and behaviors Examples: Detect individual and aggregated abnormal patterns Example: Predictive assessment against known fraud cases Example: Knowledge discovery through associative link analysis Example: Employee 3 rd Party Flags Internal Bad Lists Call Center Logs Txns in different time zones within short period of time 1 st Txn outside US Cash cycling event Wire transactions on account exceed norm # unsecured loans on network exceed norm Accounts per address exceed norm Like wire transaction patterns Like account opening & closure patterns Like network growth rate (velocity) Association to known fraud Identity manipulation Transactions to suspicious counterparties Hybrid Approach Proactively applies combination of all 4 approaches at account, customer, and network levels 6

7 Analytic Engine Analytic Approach: Unsupervised Methods Use when no target exists Examine current behavior to identify outliers and abnormal transactions that are somewhat different from ordinary transactions Include univariate and multivariate outlier detection techniques, such as peer group comparison, clustering, trend analysis, and so on 7

8 Analytic Engine Analytic Approach: Supervised Methods Use when a known target (fraud) is available Use historical behavioral information of known fraud to identify suspicious behaviors similar to previous fraud patterns Include parametric and nonparametric predictive models, such as generalized linear model, tree, neural networks, and so on Fraud Scores Incomes Predicted Fraud Scores # of previous investigations 8

9 Analytic Engine Predictive Analytics 9

10 Analytic Engine Analytic Approach: Text Mining Text Mining (e.g., call center logs or investigator notes) 10

11 Why Social Network Analysis? Rules, Predictive Models, Anomaly Detection on Linked Data More fraud / actionable cases identified Including both previously undetected networks and extensions to already identified cases Reduction in false positive rates SNA reduces false positives by up to 10+ times over traditional rulesbased approaches Improved analyst / investigation efficiency Each referral takes 1/2 1/3 the time to investigate using SAS fraud network visualization on aggregated data Significant increase in ROI per analyst / investigator Can be leveraged for credit risk, marketing, householding, AML 11

12 SAS Fraud Framework Analytics Network scoring SAS Social Network Analysis Rule and analytic-based Analytic measures of association help users know where to look in network Net-CHAID for local area of interest (node) in the network Density, Beta-Index (network) Risk ranking with hypergeometric distribution, degree, closeness, betweenness, eigenvector, clustering coefficients (node) 12

13 SAS Fraud Framework Process Flow Operational Data Sources Exploratory Data Analysis & Transformation Fraud Data Staging Business Rules Alert Generation Process SNA Server Administration Social Network Analysis ARC RTS Analytics Anomaly Detection Predictive Modeling Network Rules Network Analytics IRIS WC Claims Intelligent Fraud Repository Learn and Improve Cycle Alert Management & BI / Reporting Case Management 13

14 Demo 14

15 Status Update 15

16 SAS Fraud Framework History Built on SAS Foundational Components SAS Business Analytics Framework in production since October 2002 Alert Generation Process in production since 2003 Social Network Analysis using OR macros, NVW since1999 SAS Fraud Framework / Alert Management UI First production release in January 2008 (thick NVW client) Release 1.0 with thin Flex client September 2008 Installed v2.0 (field release of thin client used for pilots across industries) SAS Fraud Framework V2.1 First production release with thin client interface Available now for implementation (in use by current customers) General availability 15Dec09 16

17 17 Copyright 2009, 2008, SAS Institute Inc. All rights reserved.

Using Analytics to detect and prevent Healthcare fraud. Copyright 2010 SAS Institute Inc. All rights reserved.

Using Analytics to detect and prevent Healthcare fraud. Copyright 2010 SAS Institute Inc. All rights reserved. Using Analytics to detect and prevent Healthcare fraud Copyright 2010 SAS Institute Inc. All rights reserved. Agenda Introductions International Fraud Trends Overview of the use of Analytics in Healthcare

More information

9K: How Technology Can Address Current and Emerging Fraud Risks

9K: How Technology Can Address Current and Emerging Fraud Risks 9K: How Technology Can Address Current and Emerging Fraud Risks Session Level: Intermediate Tuesday, June 14-1:40-3:00 p.m. This session will explore how organizations are addressing the operational and

More information

SAS Fraud Framework for Health Care Evolution and Learnings

SAS Fraud Framework for Health Care Evolution and Learnings SAS Fraud Framework for Health Care Evolution and Learnings Julie Malida, Principal for Health Care Fraud, SAS Jay King, Manager, Advanced Analytics Lab, SAS Copyright 2009, SAS Institute Inc. All rights

More information

Closing session. Session 11 Coördinators: Basie von Solms & Leon Strous

Closing session. Session 11 Coördinators: Basie von Solms & Leon Strous The 22nd IFIP World Computer Congress 24 26 September 2012 Amsterdam the Netherlands Towards an innovative, secure and sustainable information society Closing session Session 11 Coördinators: Basie von

More information

Smarter Analytics Leadership Summit Content Review

Smarter Analytics Leadership Summit Content Review Smarter Analytics Leadership Summit Content Review Agenda Fraud Point of View IBM Claims Fraud Solution Overview Infinity Insurance: Combating Fraud with IBM Claims Fraud Solution Building the Business

More information

Mastering Big Data. Steve Hoskin, VP and Chief Architect INFORMATICA MDM. October 2015

Mastering Big Data. Steve Hoskin, VP and Chief Architect INFORMATICA MDM. October 2015 Mastering Big Data Steve Hoskin, VP and Chief Architect INFORMATICA MDM October 2015 Agenda About Big Data MDM and Big Data The Importance of Relationships Big Data Use Cases About Big Data Big Data is

More information

The State of Insurance Fraud Technology. A study of insurer use, strategies and plans for anti-fraud technology

The State of Insurance Fraud Technology. A study of insurer use, strategies and plans for anti-fraud technology The State of Insurance Fraud Technology A study of insurer use, strategies and plans for anti-fraud technology September 2014 The State of Insurance Fraud Technology A study of insurer use, strategies

More information

Solve Your Toughest Challenges with Data Mining

Solve Your Toughest Challenges with Data Mining IBM Software Business Analytics IBM SPSS Modeler Solve Your Toughest Challenges with Data Mining Use predictive intelligence to make good decisions faster Solve Your Toughest Challenges with Data Mining

More information

Solve your toughest challenges with data mining

Solve your toughest challenges with data mining IBM Software IBM SPSS Modeler Solve your toughest challenges with data mining Use predictive intelligence to make good decisions faster Solve your toughest challenges with data mining Imagine if you could

More information

IBM's Fraud and Abuse, Analytics and Management Solution

IBM's Fraud and Abuse, Analytics and Management Solution Government Efficiency through Innovative Reform IBM's Fraud and Abuse, Analytics and Management Solution Service Definition Copyright IBM Corporation 2014 Table of Contents Overview... 1 Major differentiators...

More information

SAS. Fraud Management. Overview. Real-time scoring of all transactions for fast, accurate fraud detection. Challenges PRODUCT BRIEF

SAS. Fraud Management. Overview. Real-time scoring of all transactions for fast, accurate fraud detection. Challenges PRODUCT BRIEF PRODUCT BRIEF SAS Fraud Management Real-time scoring of all transactions for fast, accurate fraud detection Overview Organizations around the globe lose approximately 5 percent of annual revenues to fraud,

More information

FRAUD & SECURITY INTELLIGENCE

FRAUD & SECURITY INTELLIGENCE FRAUD & SECURITY INTELLIGENCE STU BRADLEY, SR. DIRECTOR SECURITY INTELLIGENCE PRACTICE APRIL 16, 2015 2015 TRENDS MOBILE IS HERE TO STAY 2015 TRENDS INTERNET OF THINGS CREATING VULNERABILITIES 2015 TRENDS

More information

Solve your toughest challenges with data mining

Solve your toughest challenges with data mining IBM Software Business Analytics IBM SPSS Modeler Solve your toughest challenges with data mining Use predictive intelligence to make good decisions faster 2 Solve your toughest challenges with data mining

More information

Agenda. Agenda. SAS Predictive Claims Processing. Detecting Fraud, Increasing Recovery and Optimizing Workflow through Analytics

Agenda. Agenda. SAS Predictive Claims Processing. Detecting Fraud, Increasing Recovery and Optimizing Workflow through Analytics SAS Predictive s Processing Detecting Fraud, Increasing Recovery and Optimizing Workflow through Analytics Stephen W Swenson, MBA SAS Insurance Development Executive Copyright 2006, 2008 SAS Institute

More information

Fraud Solution for Financial Services

Fraud Solution for Financial Services Fraud Solution for Financial Services Transforming Fraud Detection and Prevention in Banks and Financial Services In the digital age, the implications of financial crime against banks and other financial

More information

Program Integrity in Government Transforming Data to Useful Information: Using Analytics to Detect and Prevent Improper Payments May 2013

Program Integrity in Government Transforming Data to Useful Information: Using Analytics to Detect and Prevent Improper Payments May 2013 Program Integrity in Government Transforming Data to Useful Information: Using Analytics to Detect and Prevent Improper Payments May 2013 Ed Rounds Smarter Analytics Executive, Fraud, Waste and Abuse Government,

More information

Data Mining + Business Intelligence. Integration, Design and Implementation

Data Mining + Business Intelligence. Integration, Design and Implementation Data Mining + Business Intelligence Integration, Design and Implementation ABOUT ME Vijay Kotu Data, Business, Technology, Statistics BUSINESS INTELLIGENCE - Result Making data accessible Wider distribution

More information

OPERA SOLUTIONS CAPABILITIES. ACH and Wire Fraud: advanced anomaly detection to find and stop costly attacks

OPERA SOLUTIONS CAPABILITIES. ACH and Wire Fraud: advanced anomaly detection to find and stop costly attacks OPERA SOLUTIONS CAPABILITIES ACH and Wire Fraud: advanced anomaly detection to find and stop costly attacks 2 The information you need to fight fraud does exist You just have to know it when you see it

More information

NEEDLE STACKS & BIG DATA: USING EVENT STREAM PROCESSING FOR RISK, SURVEILLANCE & SECURITY ANALYTICS IN CAPITAL MARKETS

NEEDLE STACKS & BIG DATA: USING EVENT STREAM PROCESSING FOR RISK, SURVEILLANCE & SECURITY ANALYTICS IN CAPITAL MARKETS NEEDLE STACKS & BIG DATA: USING PROCESSING FOR RISK, SURVEILLANCE & SECURITY ANALYTICS IN CAPITAL MARKETS JERRY BAULIER, DIRECTOR, PROCESSING DAVID M. WALLACE, GLOBAL FINANCIAL SERVICES MARKETING MANAGER

More information

Product. AML Risk Manager for Life Insurance Complete End-to-End AML Coverage for Life Insurance

Product. AML Risk Manager for Life Insurance Complete End-to-End AML Coverage for Life Insurance Product AML Risk Manager for Life Insurance Complete End-to-End AML Coverage for Life Insurance A Comprehensive Solution for AML Detection, Investigation, Case Management and Reporting Illegal money laundering

More information

Statement of. Mark Nelsen. Senior Vice President, Risk Products and Business Intelligence. Visa Inc. House Ways & Means Subcommittee.

Statement of. Mark Nelsen. Senior Vice President, Risk Products and Business Intelligence. Visa Inc. House Ways & Means Subcommittee. Statement of Mark Nelsen Senior Vice President, Risk Products and Business Intelligence Visa Inc. House Ways & Means Subcommittee on Oversight Hearing on The Use of Data to Stop Medicare Fraud March 24,

More information

Master Data Management: More than a single view of the enterprise? Tony Fisher President and CEO

Master Data Management: More than a single view of the enterprise? Tony Fisher President and CEO Master Data Management: More than a single view of the enterprise? Tony Fisher President and CEO Agenda Why MDM? Why CDI? Business Drivers for MDM Are You Ready for MDM? What is Master Data Management?

More information

2nd Global Summit Healthcare Fraud: Prevention is better than cure. 25-26 October 2012 Beaumont Estate, Old Windsor, UK

2nd Global Summit Healthcare Fraud: Prevention is better than cure. 25-26 October 2012 Beaumont Estate, Old Windsor, UK 2nd Global Summit Healthcare Fraud: Prevention is better than cure 25-26 October 2012 Beaumont Estate, Old Windsor, UK Combating Fraud, Waste and Abuse With Predictive Analytics Global Summit Healthcare

More information

Predictive Analytics: Turn Information into Insights

Predictive Analytics: Turn Information into Insights Predictive Analytics: Turn Information into Insights Pallav Nuwal Business Manager; Predictive Analytics, India-South Asia pallav.nuwal@in.ibm.com +91.9820330224 Agenda IBM Predictive Analytics portfolio

More information

Introduction to BPM. Dr. Setrag Khoshafian. Chief Evangelist & VP of BPM Technology

Introduction to BPM. Dr. Setrag Khoshafian. Chief Evangelist & VP of BPM Technology Introduction to BPM Dr. Setrag Khoshafian Chief Evangelist & VP of BPM Technology Agenda: Business Transformation Through BPM Suite The Vision: Realizing the Adaptive Enterprise What is a BPM Suite? How

More information

Introduction to Predictive Analytics: SPSS Modeler

Introduction to Predictive Analytics: SPSS Modeler Introduction to Predictive Analytics: SPSS Modeler John Antonucci, Sr. BDM Katrina Adams Ph.D. Welcome! The Webinar will begin at 12:00 pm EST LPA Events Calendar Upcoming Webinars Today - Introduction

More information

The Convergence of Data and Analytics in the Corporate World

The Convergence of Data and Analytics in the Corporate World The Convergence of Data and Analytics in the Corporate World Is it possible to draw parallels between commercial experience and tax applications? Jack Noonan President & Chief Executive Officer SPSS Inc.

More information

Smarter Analytics. Barbara Cain. Driving Value from Big Data

Smarter Analytics. Barbara Cain. Driving Value from Big Data Smarter Analytics Driving Value from Big Data Barbara Cain Vice President Product Management - Business Intelligence and Advanced Analytics Business Analytics IBM Software Group 1 Agenda for today 1 Big

More information

RSA Adaptive Authentication For ecommerce

RSA Adaptive Authentication For ecommerce RSA Adaptive Authentication For ecommerce Risk-based 3D Secure for Credit Card Issuers SOLUTION BRIEF RSA FRAUD & RISK INTELLIGENCE The Threat of ecommerce Fraud ecommerce fraud is a threat to both issuers

More information

A New Era Of Analytic

A New Era Of Analytic Penang egovernment Seminar 2014 A New Era Of Analytic Megat Anuar Idris Head, Project Delivery, Business Analytics & Big Data Agenda Overview of Big Data Case Studies on Big Data Big Data Technology Readiness

More information

PREDICTIVE MARKETING, DIGITAL ATTRIBUTION, OPTIMIZATION, AND DATA-DRIVEN PERSONALIZATION

PREDICTIVE MARKETING, DIGITAL ATTRIBUTION, OPTIMIZATION, AND DATA-DRIVEN PERSONALIZATION PREDICTIVE MARKETING, DIGITAL ATTRIBUTION, OPTIMIZATION, AND DATA-DRIVEN PERSONALIZATION A m a r t y a B h a t t a c h a r j y & S u n e e l G r o v e r P r i n c i p a l S o l u t i o n A r c h i t e

More information

April 2016 JPoint Moscow, Russia. How to Apply Big Data Analytics and Machine Learning to Real Time Processing. Kai Wähner. kwaehner@tibco.

April 2016 JPoint Moscow, Russia. How to Apply Big Data Analytics and Machine Learning to Real Time Processing. Kai Wähner. kwaehner@tibco. April 2016 JPoint Moscow, Russia How to Apply Big Data Analytics and Machine Learning to Real Time Processing Kai Wähner kwaehner@tibco.com @KaiWaehner www.kai-waehner.de LinkedIn / Xing Please connect!

More information

CoolaData Predictive Analytics

CoolaData Predictive Analytics CoolaData Predictive Analytics 9 3 6 About CoolaData CoolaData empowers online companies to become proactive and predictive without having to develop, store, manage or monitor data themselves. It is an

More information

Data Warehousing and Data Mining in Business Applications

Data Warehousing and Data Mining in Business Applications 133 Data Warehousing and Data Mining in Business Applications Eesha Goel CSE Deptt. GZS-PTU Campus, Bathinda. Abstract Information technology is now required in all aspect of our lives that helps in business

More information

How Organisations Are Using Data Mining Techniques To Gain a Competitive Advantage John Spooner SAS UK

How Organisations Are Using Data Mining Techniques To Gain a Competitive Advantage John Spooner SAS UK How Organisations Are Using Data Mining Techniques To Gain a Competitive Advantage John Spooner SAS UK Agenda Analytics why now? The process around data and text mining Case Studies The Value of Information

More information

Fraud Alert Management The Power of an Integrated Approach. Eric Kraus, Sr. Director Fraud Product Management

Fraud Alert Management The Power of an Integrated Approach. Eric Kraus, Sr. Director Fraud Product Management Fraud Alert Management The Power of an Integrated Approach Eric Kraus, Sr. Director Fraud Product Management FIS Fraud Management Who We Are FIS Fraud Management 7,600+ financial institutions served 47

More information

Niara Security Analytics. Overview. Automatically detect attacks on the inside using machine learning

Niara Security Analytics. Overview. Automatically detect attacks on the inside using machine learning Niara Security Analytics Automatically detect attacks on the inside using machine learning Automatically detect attacks on the inside Supercharge analysts capabilities Enhance existing security investments

More information

Introducing SAP Fraud Management. Jérôme Pugnet

Introducing SAP Fraud Management. Jérôme Pugnet Introducing SAP Fraud Management Jérôme Pugnet LEARNING POINTS Impacts and Challenges of Fraud How Big is the Problem? Fraud is Typically Found Without Technology: an Undetected Potential! What are the

More information

An effective approach to preventing application fraud. Experian Fraud Analytics

An effective approach to preventing application fraud. Experian Fraud Analytics An effective approach to preventing application fraud Experian Fraud Analytics The growing threat of application fraud Fraud attacks are increasing across the world Application fraud is a rapidly growing

More information

Making critical connections: predictive analytics in government

Making critical connections: predictive analytics in government Making critical connections: predictive analytics in government Improve strategic and tactical decision-making Highlights: Support data-driven decisions using IBM SPSS Modeler Reduce fraud, waste and abuse

More information

Warranty Fraud Detection & Prevention

Warranty Fraud Detection & Prevention Warranty Fraud Detection & Prevention Venky Rao North American Predictive Analytics Segment Leader Agenda IBM SPSS Predictive Analytics for Warranties: Case Studies Why address the Warranties process:

More information

The Predictive Fraud and Abuse Analytic and Risk Management System

The Predictive Fraud and Abuse Analytic and Risk Management System The Predictive Fraud and Abuse Analytic and Risk Management System Empowering healthcare payers and stakeholders in preventing and recovering fraudulent healthcare payments IkaIntegrity : Your real-time

More information

FICO Falcon Fraud Manager for Retail Banking

FICO Falcon Fraud Manager for Retail Banking FICO Falcon Fraud Manager for Retail Banking What can you do to protect the current account against fraud attacks? Martin Warwick Principal Consultant Fraud Solutions FICO May 2010 1 2010 Fair Isaac Corporation.

More information

BIG DATA What it is and how to use?

BIG DATA What it is and how to use? BIG DATA What it is and how to use? Lauri Ilison, PhD Data Scientist 21.11.2014 Big Data definition? There is no clear definition for BIG DATA BIG DATA is more of a concept than precise term 1 21.11.14

More information

Big Data Developments in Transaction Analytics

Big Data Developments in Transaction Analytics Big Data Developments in Transaction Analytics Scott M Zoldi, PhD Vice President FICO Credit Scoring and Credit Control XIII August 28-30, 2013 This presentation is provided for the recipient only and

More information

DRIVING THE CHANGE ENABLING TECHNOLOGY FOR FINANCE 15 TH FINANCE TECH FORUM SOFIA, BULGARIA APRIL 25 2013

DRIVING THE CHANGE ENABLING TECHNOLOGY FOR FINANCE 15 TH FINANCE TECH FORUM SOFIA, BULGARIA APRIL 25 2013 DRIVING THE CHANGE ENABLING TECHNOLOGY FOR FINANCE 15 TH FINANCE TECH FORUM SOFIA, BULGARIA APRIL 25 2013 BRAD HATHAWAY REGIONAL LEADER FOR INFORMATION MANAGEMENT AGENDA Major Technology Trends Focus on

More information

ACI Response to FFIEC Guidance

ACI Response to FFIEC Guidance ACI Response to FFIEC Guidance Version 1 July 2011 Table of contents Introduction 3 FFIEC Supervisory Expectations 4 ACI Online Banking Fraud Management 8 Online Banking Fraud Detection and Prevention

More information

III JORNADAS DE DATA MINING

III JORNADAS DE DATA MINING III JORNADAS DE DATA MINING EN EL MARCO DE LA MAESTRÍA EN DATA MINING DE LA UNIVERSIDAD AUSTRAL PRESENTACIÓN TECNOLÓGICA IBM Alan Schcolnik, Cognos Technical Sales Team Leader, IBM Software Group. IAE

More information

Predictive Modeling in Workers Compensation 2008 CAS Ratemaking Seminar

Predictive Modeling in Workers Compensation 2008 CAS Ratemaking Seminar Predictive Modeling in Workers Compensation 2008 CAS Ratemaking Seminar Prepared by Louise Francis, FCAS, MAAA Francis Analytics and Actuarial Data Mining, Inc. www.data-mines.com Louise.francis@data-mines.cm

More information

Gladiator NetTeller Enterprise Security Monitoring Online Fraud Detection INFORMATION SECURITY & RISK MANAGEMENT

Gladiator NetTeller Enterprise Security Monitoring Online Fraud Detection INFORMATION SECURITY & RISK MANAGEMENT Gladiator NetTeller Enterprise Security Monitoring Online Fraud Detection INFORMATION SECURITY & RISK MANAGEMENT Gladiator NetTeller Enterprise Security Monitoring Online Fraud Detection Foreword The consumerization

More information

An Oracle White Paper October 2009. An Integrated Approach to Fighting Financial Crime: Leveraging Investments in AML and Fraud Solutions

An Oracle White Paper October 2009. An Integrated Approach to Fighting Financial Crime: Leveraging Investments in AML and Fraud Solutions An Oracle White Paper October 2009 An Integrated Approach to Fighting Financial Crime: Leveraging Investments in AML and Fraud Solutions Executive Overview Today s complex financial crime schemes pose

More information

Combating Insurance Claims Fraud

Combating Insurance Claims Fraud Combating Insurance Claims Fraud How to Recognize and Reduce Opportunistic and Organized Claims Fraud WHITE PAPER SAS White Paper Table of Contents Executive Summary....1 Introduction....1 The Many Faces

More information

2015 Analyst and Advisor Summit. Advanced Data Analytics Dr. Rod Fontecilla Vice President, Application Services, Chief Data Scientist

2015 Analyst and Advisor Summit. Advanced Data Analytics Dr. Rod Fontecilla Vice President, Application Services, Chief Data Scientist 2015 Analyst and Advisor Summit Advanced Data Analytics Dr. Rod Fontecilla Vice President, Application Services, Chief Data Scientist Agenda Key Facts Offerings and Capabilities Case Studies When to Engage

More information

Are You Ready for Big Data?

Are You Ready for Big Data? Are You Ready for Big Data? Jim Gallo National Director, Business Analytics February 11, 2013 Agenda What is Big Data? How do you leverage Big Data in your company? How do you prepare for a Big Data initiative?

More information

WebFOCUS RStat. RStat. Predict the Future and Make Effective Decisions Today. WebFOCUS RStat

WebFOCUS RStat. RStat. Predict the Future and Make Effective Decisions Today. WebFOCUS RStat Information Builders enables agile information solutions with business intelligence (BI) and integration technologies. WebFOCUS the most widely utilized business intelligence platform connects to any enterprise

More information

Stopping the Flow of Health Care Fraud with Technology, Data and Analytics

Stopping the Flow of Health Care Fraud with Technology, Data and Analytics White Paper and New Ways to Fight It Stopping the Flow of Health Care Fraud with Technology, Data and Analytics January 2014 Health care costs are rising and everyone is being affected, including patients,

More information

CA Arcot RiskFort. Overview. Benefits

CA Arcot RiskFort. Overview. Benefits PRODUCT SHEET: CA Arcot RiskFort CA Arcot RiskFort CA Arcot RiskFort provides real-time protection against identity theft and online fraud via risk based, adaptive authentication. It evaluates the fraud

More information

Endeca Introduction to Big Data Analytics

Endeca Introduction to Big Data Analytics Endeca Introduction to Big Data Analytics Overview May 8, 2013 1 Agenda Introduction Overview Analytics for Big Data Overview Endeca Information Discovery Q & A 2 Introduction Business vs. IT Big Data

More information

Customer Information Management. Amanda McIntyre, Vice President, Product Manager Glenn Sonsalla, Vice President, Enterprise Strategy & Governance

Customer Information Management. Amanda McIntyre, Vice President, Product Manager Glenn Sonsalla, Vice President, Enterprise Strategy & Governance Customer Information Management Amanda McIntyre, Vice President, Product Manager Glenn Sonsalla, Vice President, Enterprise Strategy & Governance Session Objectives Defining Customer Information Management

More information

Signal Hub for Wealth Management

Signal Hub for Wealth Management Signal Hub for Wealth Management Overview of Design and Background The Signal Hub for Wealth Management, which Opera Solutions has deployed to the wealth management industry, has required combining a variety

More information

Busting Financial Crime with TIBCO

Busting Financial Crime with TIBCO Busting Financial Crime with TIBCO Ana Costa e Silva, PhD Senior Data Scientist, TIBCO Software What if you could use just one financial crime fighting solution that would empower your business users to

More information

THE USE OF PREDICTIVE MODELLING TO BOOST DEBT COLLECTION EFFICIENCY

THE USE OF PREDICTIVE MODELLING TO BOOST DEBT COLLECTION EFFICIENCY CREDIT SCORING AND CREDIT CONTROL XIII EDINBURGH 28-30 AUGUST 2013 THE USE OF PREDICTIVE MODELLING TO BOOST DEBT COLLECTION EFFICIENCY MARCIN NADOLNY SAS INSTITUTE POLAND Many executives fear that the

More information

PREDICTIVE ANALYTICS IN FRAUD

PREDICTIVE ANALYTICS IN FRAUD PREDICTIVE ANALYTICS IN FRAUD Click Scott to White edit Master subtitle style Business Development Manager Why predict? Organizations that use predictive business performance metrics will increase their

More information

How Financial Services Firms Can Benefit From Streaming Analytics

How Financial Services Firms Can Benefit From Streaming Analytics How Financial Services Firms Can Benefit From Streaming Analytics > 2 VITRIA TECHNOLOGY, INC. > How Financial Services Firms Can Benefit From Streaming Analytics Streaming Analytics: Why It s Important

More information

IBM Analytical Decision Management

IBM Analytical Decision Management IBM Analytical Decision Management Deliver better outcomes in real time, every time Highlights Organizations of all types can maximize outcomes with IBM Analytical Decision Management, which enables you

More information

Fighting Identity Fraud with Data Mining. Groundbreaking means to prevent fraud in identity management solutions

Fighting Identity Fraud with Data Mining. Groundbreaking means to prevent fraud in identity management solutions Fighting Identity Fraud with Data Mining Groundbreaking means to prevent fraud in identity management solutions Contents Executive summary Executive summary 3 The impact of identity fraud? 4 The forgery

More information

INSURANCE INFORMATION AND MONITORING CENTER

INSURANCE INFORMATION AND MONITORING CENTER INSURANCE INFORMATION AND MONITORING CENTER AYDIN SATICI Managing Director April 2015 Sigorta Bilgi ve Gözetim Merkezi 1. 2. Mobile Accident Report Application 3. Fraud Management System and Social Network

More information

CHANNEL OPTIMIZATION THROUGH PERSONALIZATION

CHANNEL OPTIMIZATION THROUGH PERSONALIZATION CHANNEL OPTIMIZATION THROUGH PERSONALIZATION 1 Introductions Zimm Zimmermann Vice President, Personalization Platform Marketer Competencies Platform Data Consumer Privacy & Compliance Audience Management

More information

Bottomline Healthcare. Privacy and Data Security

Bottomline Healthcare. Privacy and Data Security Bottomline Healthcare Privacy and Data Security Start Page 2 Table of Contents 03 The Patient Privacy Challenge 05 Bottomline Healthcare Privacy and Data Security 07 How it Works Features Data Capture

More information

Data Mining with SAS. Mathias Lanner mathias.lanner@swe.sas.com. Copyright 2010 SAS Institute Inc. All rights reserved.

Data Mining with SAS. Mathias Lanner mathias.lanner@swe.sas.com. Copyright 2010 SAS Institute Inc. All rights reserved. Data Mining with SAS Mathias Lanner mathias.lanner@swe.sas.com Copyright 2010 SAS Institute Inc. All rights reserved. Agenda Data mining Introduction Data mining applications Data mining techniques SEMMA

More information

Making Critical Connections: Predictive Analytics in Government

Making Critical Connections: Predictive Analytics in Government Making Critical Connections: Predictive Analytics in Improve strategic and tactical decision-making Highlights: Support data-driven decisions. Reduce fraud, waste and abuse. Allocate resources more effectively.

More information

MDaudit Compliance made easy. MDaudit software automates and streamlines the auditing process to improve productivity and reduce compliance risk.

MDaudit Compliance made easy. MDaudit software automates and streamlines the auditing process to improve productivity and reduce compliance risk. MDaudit Compliance made easy MDaudit software automates and streamlines the auditing process to improve productivity and reduce compliance risk. MDaudit As healthcare compliance, auditing and coding professionals,

More information

An Enterprise Framework for Business Intelligence

An Enterprise Framework for Business Intelligence An Enterprise Framework for Business Intelligence Colin White BI Research May 2009 Sponsored by Oracle Corporation TABLE OF CONTENTS AN ENTERPRISE FRAMEWORK FOR BUSINESS INTELLIGENCE 1 THE BI PROCESSING

More information

IBM Counter Fraud Signature Solutions

IBM Counter Fraud Signature Solutions IBM Counter Fraud Signature Solutions November 5th, 2013 Athens Carmen Ene, VP IBM Global Business Services, Europe Leader Counter Fraud & Financial Crimes Provider ID Theft o Claim for routine services

More information

4.4 Human Services, Medicaid Payments, Fraud Prevention, Detection, and Program Integrity

4.4 Human Services, Medicaid Payments, Fraud Prevention, Detection, and Program Integrity 4.4 Human Services, Medicaid Payments, Fraud Prevention, Detection, and Program Integrity SAS is focused on fraud and leading the industry in fraud detection A. A description of relevant experience specific

More information

Complete Financial Crime and Compliance Management

Complete Financial Crime and Compliance Management Complete Financial Crime and Management With Oracle Financial Services Financial Crime and Management applications, financial institutions can manage compliance risk and investigate appropriate information

More information

Anti-fraud management solution. Torsten Zube October 2012

Anti-fraud management solution. Torsten Zube October 2012 Anti-fraud management solution Torsten Zube October 2012 Legal Disclaimer This presentation is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any

More information

SAP Predictive Analysis: Strategy, Value Proposition

SAP Predictive Analysis: Strategy, Value Proposition September 10-13, 2012 Orlando, Florida SAP Predictive Analysis: Strategy, Value Proposition Charles Gadalla, Solution Management, SAP Business Intelligence Manavendra Misra, Chief Knowledge Officer, Cognilytics

More information

Application of Data Visualization

Application of Data Visualization Application of Data Visualization Lunteren Conference Landelijk Netwerk Mathematische Besliskunde (LNMB) January 15 2015, Lunteren dr.ir. Danny Holten Lead Visualization Scientist & Co-Founder danny.holten@synerscope.com

More information

Copyright 2009 SAS Institute Inc. All rights reserved. Success With Business Analytics in the New Pharmaceutical Commercial Model.

Copyright 2009 SAS Institute Inc. All rights reserved. Success With Business Analytics in the New Pharmaceutical Commercial Model. Copyright 2009 SAS Institute Inc. All rights reserved. Success With Business Analytics in the New Pharmaceutical Commercial Model. Emerging Commercial Models: Rethinking Analytics Deloitte Consulting LLP

More information

Leverage big data to fight claims fraud

Leverage big data to fight claims fraud Leverage big data to fight claims fraud How big data supports smarter approaches to addressing claims fraud Highlights Identify patterns and trends across emerging information to pinpoint fraudsters quickly

More information

Three proven methods to achieve a higher ROI from data mining

Three proven methods to achieve a higher ROI from data mining IBM SPSS Modeler Three proven methods to achieve a higher ROI from data mining Take your business results to the next level Highlights: Incorporate additional types of data in your predictive models By

More information

Advanced Case Management in Government: The Roadmap for Effectiveness and Efficiency

Advanced Case Management in Government: The Roadmap for Effectiveness and Efficiency Advanced Case Management in Government: The Roadmap for Effectiveness and Efficiency Campbell Robertson Program Director, Public Sector IBM Software Group/Industry Solutions/ECM cir@ca.ibm.com Twitter:

More information

Life Insurance & Big Data Analytics: Enterprise Architecture

Life Insurance & Big Data Analytics: Enterprise Architecture Life Insurance & Big Data Analytics: Enterprise Architecture Author: Sudhir Patavardhan Vice President Engineering Feb 2013 Saxon Global Inc. 1320 Greenway Drive, Irving, TX 75038 Contents Contents...1

More information

Application Fraud and Account Monitoring

Application Fraud and Account Monitoring Application Fraud and Account Monitoring A Holistic Approach to First Party Fraud First Party Fraud The attempt by an individual, or group of individuals, to establish facilities with a bank and acquire

More information

The CRM that Defines Innovation. Bill Armistead, Product Sales Specialist CONNECTIONS

The CRM that Defines Innovation. Bill Armistead, Product Sales Specialist CONNECTIONS The CRM that Defines Innovation Bill Armistead, Product Sales Specialist CONNECTIONS The CRM that Defines Innovation What is CONNECTIONS? CRM (Customer Relationship Management) Enterprise-wide, web-based,

More information

Using Predictive Analytics to Detect Contract Fraud, Waste, and Abuse Case Study from U.S. Postal Service OIG

Using Predictive Analytics to Detect Contract Fraud, Waste, and Abuse Case Study from U.S. Postal Service OIG Using Predictive Analytics to Detect Contract Fraud, Waste, and Abuse Case Study from U.S. Postal Service OIG MACPA Government & Non Profit Conference April 26, 2013 Isaiah Goodall, Director of Business

More information

Are You Ready for Big Data?

Are You Ready for Big Data? Are You Ready for Big Data? Jim Gallo National Director, Business Analytics April 10, 2013 Agenda What is Big Data? How do you leverage Big Data in your company? How do you prepare for a Big Data initiative?

More information

Data: To BI or not to BI?

Data: To BI or not to BI? NATIONAL CONFERENCE ON BMS, 30 MAY 2013, HILTON HOTEL Challenges in building a BI and Big data analytics system Data: To BI or not to BI? Iva Valerieva, 1 Marketing & Business Development Manager Who Are

More information

Solution Brief Efficient ecommerce Fraud Management for Acquirers

Solution Brief Efficient ecommerce Fraud Management for Acquirers Solution Brief Efficient ecommerce Fraud Management for Acquirers Table of Contents Introduction Sophisticated Fraud Detection and Chargeback Reduction Improved Compliance Posture Transparent User Experience

More information

Recognize the many faces of fraud

Recognize the many faces of fraud Recognize the many faces of fraud Detect and prevent fraud by finding subtle patterns and associations in your data Contents: 1 Introduction 2 The many faces of fraud 3 Detect healthcare fraud easily and

More information

BUSINESS ANALYTICS SUPPORTING FRAUD DETECTION AND PREVENTION DAVID HARTLEY DIRECTOR FRAUD AND FINANCIAL CRIMES PRACTICE

BUSINESS ANALYTICS SUPPORTING FRAUD DETECTION AND PREVENTION DAVID HARTLEY DIRECTOR FRAUD AND FINANCIAL CRIMES PRACTICE BUSINESS ANALYTICS SUPPORTING FRAUD DETECTION AND PREVENTION DAVID HARTLEY DIRECTOR FRAUD AND FINANCIAL CRIMES PRACTICE AGENDA Understanding Business Analytics Business Cases How Business Analytics can

More information

Data Integration Alternatives & Best Practices

Data Integration Alternatives & Best Practices CAS 2006 March 13, 2006, 2:00 3:30 Data 2: Information Stored, Mined & Utilized/2 Data Integration Alternatives & Best Practices Patricia Saporito, CPCU Insurance Industry Practice Director Information

More information

Predictive Analytics at the Speed of Business

Predictive Analytics at the Speed of Business Predictive Analytics at the Speed of Business How decision management and a real-time infrastructure get predictive analytics where and when you need them 2012 Decision Management Solutions 1 Your presenters

More information

Data Science Transforming Security Operations

Data Science Transforming Security Operations SESSION ID: STR-W03 Data Science Transforming Security Operations Alon Kaufman Ph.D. Director Data Science & Innovation RSA Agenda Transforming Security Operations with Data Science The Vision: Where we

More information

A Multitier Fraud Analytics and Detection Approach

A Multitier Fraud Analytics and Detection Approach A Multitier Fraud Analytics and Detection Approach Jay Schindler, PhD MPH DISCLAIMER: The views and opinions expressed in this presentation are those of the author and do not necessarily represent official

More information

BIG SHIFTS WHAT S NEXT IN AML

BIG SHIFTS WHAT S NEXT IN AML Commercial Solutions Financial Crimes Commercial Solutions BIG SHIFTS WHAT S NEXT IN AML The next big shift in the fight against financial crime and money laundering is advanced machine learning and sophisticated

More information

The Data Mining Process

The Data Mining Process Sequence for Determining Necessary Data. Wrong: Catalog everything you have, and decide what data is important. Right: Work backward from the solution, define the problem explicitly, and map out the data

More information

SAP Predictive Analytics: An Overview and Roadmap. Charles Gadalla, SAP @cgadalla SESSION CODE: 603

SAP Predictive Analytics: An Overview and Roadmap. Charles Gadalla, SAP @cgadalla SESSION CODE: 603 SAP Predictive Analytics: An Overview and Roadmap Charles Gadalla, SAP @cgadalla SESSION CODE: 603 Advanced Analytics SAP Vision Embed Smart Agile Analytics into Decision Processes to Deliver Business

More information

Augmented Search for Software Testing

Augmented Search for Software Testing Augmented Search for Software Testing For Testers, Developers, and QA Managers New frontier in big log data analysis and application intelligence Business white paper May 2015 During software testing cycles,

More information