COMPARATIVE STUDY OF SAS FRAUD MANAGEMENT & MONITOR PLUS ACF

Agenda

Introduction SAS Fraud Management SAS Functionality Fraud Framework Technical aspects of SAS Monitor Plus ACF ACF Functionality Fraud framework ACF Technical Aspects Comparison of SAS and Monitor Plus

Introduction

Banks need to have enterprise-wide fraud management system

Fraud detection, Alert, Case management should be managed as a whole

Customer behavior needs to be studied across all channels and products

Equal emphasis should be given on non-financial transaction

SAS Fraud Management

Proactive approach Focuses more on fraud prevention than fraud

detection Wide coverage of transactions

Purchase Payments Non-monetary

Monitors real time transactions Multiple accounts monitoring for same

cardholder

Functionality

Integrated End to End Fraud management approach

Functionality

Analyzes customer behavior Scores transactions on demand for risks In built fraud models available System updates itself after every

fraudulent transaction Separate Case Management provided

Fraud Framework

Data analysis and alert generation The ability to assimilate data from multiple sources and

apply predictive analytics to accurately assess transactions, activities and customer state in real time.

Alert management The mechanism for accepting, prioritizing and distributing

alerts from the various fraud detection and money laundering tools used across the enterprise.

Social network analysis An analysis and visualization tool for uncovering

previously unknown relationships among accounts or entities.

Case management A structured environment in which to manage

investigation workflows, attach documentation and record exposure and losses, while using advanced dashboards for management oversight and analytical reporting to track financial crimes operational performance.

Technical Aspects

Zero foot print technology End users need not install any software

Use of neural network Ability to learn Ability to generalize

Client configurable API Can be customized as per client’s need

Customer state vectors Flexible Architecture

Monitor Plus ACF

Reactive Approach Transaction Screening, monitoring

Covers real time, near real time, batch mode

Scope of transactions Cash Advance, Purchases Internet & electronic channels Non financial transactions

Users can customize pre-define parameters

Functionality

• AI Techniques• Unusual TRx• Fraud

Sequences

• Generate Alerts

• Pre defined actions

• Investigation Work Flows

• Confirm• Discard• Fraud

Learning Analyze

ActionConclusion

Functionality

4 stage analysis process ACF analyzes operations on following criteria

Issuer Acquirer Processor Switch

Comprehensive Fraud pattern analysis Automated alerts and actions Uses AI Techniques for analysis

Business rules Case base reasoning Risk factor analysis Transaction risk scoring

Framework

Alert & Presentation Layer

Reports

Analysis Layer

Risk Factors

Data Access Layer

Real time, Near real time, Batch

Framework

Data Access layer Access data from transaction from any kind of source

i.e. real time, near real time, batch mode and screens transactions for fraudulent processes

Analysis Layer Performs analysis based on adaptive business rules,

neural n/w, risk factor scoring, fraud patterns Alert & Presentation layer

Generates alerts such as email, SMS, call to customer service as well as customer himself, Audit etc.

Performs pre defined actions given by users such as block card, deny access, freeze an account etc.

Technical Aspect

Use of neural network Ability to learn Ability to generalize

Customizable system parameters Integrative and flexible system Included case management Point of compromise management

Face to FaceParameters SAS Fraud Management Monitor Plus ACF

Approach Proactive Reactive

Transaction Coverage Real Time Real Time, Near Real Time, Batch Mode

Functionality

Customer Behavior Present uses customer state vectors

Present uses fraud pattern analysis

Transaction Scoring Present Present based on risk factors

Built in fraud Models Present Present

Case Management Need to buy separately Present

Technical Aspects

Zero foot print technique Present Absent

Neural network Present Present

Customizable API Present Present

Customer state vectors Present Absent

AI Techniques Absent Present

Alert management Present Present