fico® application fraud solution
TRANSCRIPT
© 2015 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.© 2015 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.
FICO® Application Fraud Manager
Cindy WhiteSenior Director Product [email protected]
www.fico.com/enterprisefraud
© 2015 Fair Isaac Corporation. Confidential. 2
Fraud and Financial Crime Trends
535 million consumers acrossthe globe will make a purchase
via mobile this year.1
Account Takeover now attributes for
40% of eCommerce Fraud.2
The FBI pursuing Russian hacker who
amassed a trove of 1.2 billion stolen online
credentials, plus payment card data and Social Security numbers
Every two seconds,there is a new identity
fraud victim in the U.S.3
1Goldman Sachs2Forrester Research: eCommerce Fraud Management Solutions 2014 3 2015 Identity Fraud Study by Javelin Strategy & Research
© 2015 Fair Isaac Corporation. Confidential. 3
The Impact of Fraud Goes Beyond Fraud Loss and Operational Costs
Source: ISMB Faces of Fraud Survey, 2013 and 2014, CEB analysis
Customers Are Less LoyalAfter Fraud Incident
0.3%1.3%
2.1%2.3%2.4%
2.8%2.9%3.0%3.0%
3.6%3.6%
4.1%4.2%
5.9%6.1%6.2%Pharmaceutical
FinancialHealthcare
ServicesTechnology
CommunicationsIndustrial
TransportationConsumerHospitality
EnergyEducationResearch
MediaRetailPublic
Abnormal Churn Rates Due to Fraud, by IndustryPercent of Abnormal Customer Churn, 2014
Source: Ponemon Institute
Banks Lack Confidence in Preventionof Account Takeover Fraud
36%
50%
26%
40%
Confidence Versus Frequency of Account TakeoverPercentage of Respondents, 2013–2014
ReportedFrequency
Confidence inAbility to Prevent
20132014
© 2015 Fair Isaac Corporation. Confidential. 4
Risk Officers Take on Diverse Challenges
Reduce customer
impact and include
consumers as an extra layer of
defense
CustomerExperience
Help me to be more compliant
and reduce brand risk
Compliance and Reputational
RiskReduce my operating expenses through
automation, shared
capabilities and self service
Operational Efficiency
Protect my organization and
my customers from financial crimes while allowing my
business to grow
FraudRisk
Management
© 2015 Fair Isaac Corporation. Confidential. 5
The cost of fraudulent applications
Source: 1Goldman Sachs 2Forrester Research: eCommerce Fraud Management Solutions 2014, Aite Group 2015
is expected to rise to
$28.6 billion by 20161
© 2015 Fair Isaac Corporation. Confidential. 5
© 2015 Fair Isaac Corporation. Confidential. 6
Explosion of new productsand channels How to monitor all of these, in real-time?
Risk management complexities: fraud and compliance monitoringHow to get a complete view of customer with limited information?
Originations Dynamics: Growing Need for Application Fraud Monitoring
Rising costof fraud and compliance monitoring How to improve a company’s ability to prevent bad people from entering the books and to know when a good customer goes bad?
© 2015 Fair Isaac Corporation. Confidential. 6
© 2015 Fair Isaac Corporation. Confidential. 7
Application Fraud Defined
An attempted or actual misrepresentation or manipulation of customer demographic (employment, residency, financial, etc.) in order to obtain a product or service that would otherwise not have been granted. This may be performed by the actual applicant,or by someone falsely representing themselves as the applicant.
© 2015 Fair Isaac Corporation. Confidential. 8
Existing,Re-size
Applicant
New,Not Seen
New,Solicited
Existing,Extension
Existing,Solicited
New,Existing
Connection
Types of Applicant and Potential Fraud Risk
SocialEngineering
FalseIncome
Declaration
Early LifeDefaults
© 2015 Fair Isaac Corporation. Confidential. 9
Existing,Re-size
Applicant
New,Not Seen
New,Solicited
Existing,Extension
Existing,Solicited
New,Existing
Connection
SocialEngineering
FalseIncome
Declaration
Early LifeDefaults
Types of Applicant and Potential Fraud Risk
Online
Online Mobile
In Branch
Online Social
© 2015 Fair Isaac Corporation. Confidential. 10
Application Fraud Typologies
First-party fraud in credit cards worldwidecost $18.5BN in 2012 andwill rise to $28.6BNby 2016
Fraudulent obtaining of credit (often by falsifying information) without intending to pay it back
FIRST PARTY
Involves identity theft – Refers to fraud that is committed without the knowledge of a person whose identity is used to commit the fraud
THIRD PARTY
© 2015 Fair Isaac Corporation. Confidential. 11
Addressing the Full Spectrum of Application Fraud
Existing, solicitedNew, not seen New, solicited New, existing connection Existing, extensionExisting, re-size
Early life defaults Bust out Identity theft False Income Declaration Social Engineering
ThirdParty
THREAT BUSINESS
FirstParty
Channel
Product
SourceSegme
nt
ActionAutomation
Investigation
DATA
© 2015 Fair Isaac Corporation. Confidential. 12
FICO® Application Fraud Manager Product Overview
© 2015 Fair Isaac Corporation. Confidential. 13
FICO® Application Fraud ManagerIdentify Both First and Third Party Application Fraud
Capability Benefit
Decisioning Service
• Single system for multiple channels and product lines• Matching engine / consortium-driven decisioning• Compares current application to other applications, fraud file, and credit
bureau records• Multiple-model execution• Real-time or batch
Analytics and Rules
• Leverage FICO-brand premium analytics and subject matter expertise that provide rapid deployment
• Modify and deploy rules in real-time for up-to-minute decisioning and fraud detection
Case Management
• Unique design helps analysts to zero in on specific areas• Investigative analysis, reporting, queue management• Integration with IRE for Link analysis with graphical view of systemic fraud
problems
Data Acquisition
Analytics
Decisioning
Case Management
Link Analysis
© 2015 Fair Isaac Corporation. Confidential. 14
AFM System Components
Orchestration • The system employs an orchestration layer to coordinate data flow
between services• Can be configured to orchestrate data import from multiple sources• Configurable sequencing of analytics and rules
Decisioning• Based on Blaze Advisor system• Web-based configurable Rules Management Administration (RMA)• Develop, test and deploy rules using business-friendly environment
Case Management• Provides flexibility and adaptation to specific application types and
business processes• Standard web services interface permits utilization of alternate
system if desired• Link Analysis• Identifies potential linkages between current application entities and
other applications• Provides graphical investigation “discovery”
System Services
OrchestrationAnalytics
LinkAnalysis
Data
Rules
CaseMgmt.
Applications +Bureau Data Cases
Consortium
© 2015 Fair Isaac Corporation. Confidential. 15
Application Fraud Analytics
1st and 3rd Party
3rd Party
CreditLine
PersonalLoans
AutoLoans
Mortgage
MobilePhone
InsurancePolicy
1st Party
Credit Card / Revolving
Credit
Consumer Loans
Insurance Policy
Mobile Phone
Auto Loans
Credit Card / Revolving
Credit
Consumer Loans
Insurance Policy
Mobile Phone
Auto Loans
Fraud Tags no Type Definition OR
Insufficient data
Tagged Fraud Data with Type Distinctions OR
Agreed Fraud Definition
Application Segmentsby Product andLine of Business
© 2015 Fair Isaac Corporation. Confidential. 16
Models
PerformanceData
Historic Data forObservation Data
Key Elements to Building a Fraud Model
Application • Age, gender, address, contact info• Occupation
Applicant • Business, consumer, self employed
Bureau • Time at address, time at employer• Payments, delinquency
Product • Cards, loans, mortgages, vehicle financing• Retail/checking/current accounts
Authentication • ID type and number• Documentation
Customer • Time with bank• Other accounts and payment history
Industry Files • Industry negative files
Third Party Data • Deceased register, sanction list, phone number lookups, address changes
© 2015 Fair Isaac Corporation. Confidential. 17
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 1000
0
5
10
15
20
25
30 Fraud to Non-fraud Score Separation
Better Fraud Predictions Yield Better Business ResultsOperationalize Scores on Every Transaction
While minimizingthe false-positives
Advanced Analytics
increases the concentration
of fraud relative to
good transactions at high score
thresholdsWhile
minimizingthe false-negatives
Advanced Analytics
decreases the concentration
of fraud relative to
good transactions
at lower score thresholds
%
% Goods% Bads
Score Cut Off
© 2015 Fair Isaac Corporation. Confidential. 18
Business Rules – Matching
• Matching rules are used to search the applications in the underlying application database for ones that contains fields that match one or more fields on the current application
• Types of matchinclude:─ Exact─ Fuzzy─ Wildcard─ Range
© 2015 Fair Isaac Corporation. Confidential. 19
Value Proposition: AFM + IRE + Global ExpertiseFICO’s Application Fraud Solution can detect more fraud, more efficiently at the point of application before losses are incurred and customers are impacted
DetectionFind More Fraud
Fraud RingsDetect Collusion using SNA
AccuracyDecrease
False Positives
Customer Experience
Say “Yes” More
EfficiencyPrioritize Work
FutureExpansion
Expand Geographically,Horizontal and Vertical
Integration
© 2015 Fair Isaac Corporation. Confidential. 20
FICO Application Fraud Solution Differentiators
Superior Analytics
FICO Models, SNA, Rules and Fuzzy Logic Detect
More Fraud with Lower False Positives
ModularDesign
Designed to Meet theUnique Needs of
Each Market
Pre-andPost-BookProvides Pre- and
Post-Book Detection and Investigative Tools
Social Network Analysis
FICO Provides SNAScoring of Applications
in Real-Time
Global Fraud Expertise
Industry-leading IP, GlobalFraud Expertise, Consulting
and Deployment
Flexibleand Scalable
FICO Provides Superior Decisioning, Flexibility
and Scalability
© 2015 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.
Thank You
Cindy White
© 2015 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.
Senior Director Product [email protected]
www.fico.com/enterprisefraud