Combating Debit Card Fraud Ron Mazursky Director of Debit Advisory Services Mercator Advisory Group Brian Fisher Card Services Product Manager Elan ATM & Debit Services Troy Cullen President Strictly Private & Confidential Emerging Trends in Debit Cards & Debit Fraud Ron Mazursky Director of Debit Advisory Services Mercator Advisory Group Troy Cullen President Strictly Private & Confidential | Debit Card Market Share represents the largest share of dollar volume spent by US consumers at 28% Share of U.S. Consumer Payment Value by Type (%), EsKmated, 2012 ACH 15% Debit 28% Checks 20% Prepaid Card 2% Cash 16% Credit 19% Source: Mercator Advisory Group, Consumers and Cash: A Love Story, January 2013 ©2013 Elan Financial Services & Mercator Advisory Group 3 | 78% 76% Debit Card Performance Stats 2011-2012 77% 76% 35 74% 72% 30 70% 25 68% 68% 66% 66% 64% 2012 2011 20 19.418.3 15 10 62% 60% $37 $38 40 5 Penetration Rate Activation rate 0 Avg # Trans/Mo. Avg Tkt Size Source: 2011-2012 Pulse Debit Card Study ©2013 Elan Financial Services & Mercator Advisory Group 4 | Consumer Ownership of Checking and Savings Accounts Survey Ques6on: Which of the following types of accounts do you have at banks or credit unions? (Base = All respondents) Checking Account Holders Age: 97% of seniors, 90% of 35–64 year olds, 84% of 25–34, but 76% of 18–24 have checking accounts Race: 92% of Whites, 80% of Asians and Hispanics, 78% of Blacks have checking accounts Income: 94% of $100K+ earners, 92% of $50K–99K earners, 85% of <$50K earners Gender: 92% of women, 86% of men 89% 93% 95% 94% Checking* 71% 77% 79% 77% Savings* 59% 61% Credit card 29% Mortgage* Unbanked (Have No Accounts With Banks) Age: 13% of 18–24 year olds, 9% of 25–34, 6% of 35–64, 2% of respondents aged 65+ Other Income: 10% of <$50K, 4% of 50K+ Race: 15% of Blacks, 11% of Hispanics, 9% Asians, 5% Whites None of these* EducaKon: 10% less, 3% college+ *StaKsKcally significant difference 2012–2013 at the 95% level. 40% 45% 44% 77% 72% 2013 2012 2011 2010 13% 11% 19% 17% 7% 5% 3% 4% Source: Mercator Advisory Group CustomerMonitor Survey Series, Payments, 2010, 2011, 2012, 2013, QuesKon S4 ©2013 Elan Financial Services & Mercator Advisory Group 5 | Household Debit Card use is shrinking, after having peaked in 2011 – on par with credit now Household Payment Type in Current Use (Base = All Respondents) 74% 68% 66% 64% 63% 62% 60% 63% 60% 59% 2009 2010 2011 34% 34% 33% 30% 12% 11% 11% 9% 10% 7% 3% 4% 4% 5% Debit card PL revolving store card* 2013 42% 39% 41% GP credit card 2012 7% 6% 4% 6% 0% GP monthly GP reloadable ATM only card charge card prepaid* 11% 8% 9% 10% 6% 5% N/A PayPal in store N/A PayPal None of the previous cards Household Card Ownership *StaKsKcally significant difference 2012–2013 at 95% level. Source: Mercator Advisory Group CustomerMonitor Survey Series 2009, 2010, 2011, 2012, 2013, QuesKon 29 ©2013 Elan Financial Services & Mercator Advisory Group 6 | • • • • Challenges in Debit Debit is finding a new norm, side by side with credit. Its torrid growth over the last several years has stalled Prepaid and other alternative financial services will meet the needs of the underserved Debit’s profitability is being challenged by regulatory issues Fraud is a big threat on the horizon and EMV is only a partial solution (need PIN v. signature; and CNP transactions are threatening). ©2013 Elan Financial Services & Mercator Advisory Group 7 | • Major points of compromise for payment card information lead to merchant, acquirer and Issuer/Network fraud Payment card data is most often compromised in data breaches at issuers, merchants and processors – Stolen card data to commit large-scale fraudulent transactions; mostly virtual (card not present), but also counterfeit • Skimming is second largest method of compromise – Magstripe data is copied at POS or ATM – Counterfeit cards are created from skimmed data ©2013 Elan Financial Services & Mercator Advisory Group 8 | Fraud Rates on U.S.-Issued Debit Cards have increased dramatically through 2011, then falling in 2012 0.09 0.075 0.08 0.07 0.075 0.06 0.054 0.047 0.05 0.04 0.081 0.054 0.052 2006 Data Not Collected 0.042 Debit Fraud losses have been on an upward trend for both Signature and PIN debit from 2004 to 2011. 2012 saw a drop in both PIN and Signature debit fraud rates. 0.03 0.02 0.01 0.013 0.006 0.011 0.010 0.010 0.007 0.003 0.008 0 200420052006200720082009201020112012 PIN Debit Fraud Rates Signature Debit Fraud Rates Source: Pulse Debit Issuer Study 2005, 2007, 2008, 2009, 2010, 2011, 2012, 2013 ©2013 Elan Financial Services & Mercator Advisory Group 9 | Debit Card Fraud per Transaction: Signature Debit Fraud Dwarfs PIN Debit Fraud Fraud losses per Transaction Source: 2013 Pulse Debit Issuer Study ©2013 Elan Financial Services & Mercator Advisory Group 10 | Exempt financial institutions earn significantly more than regulated financial institutions on interchange $/Year $120.00 $104.76 $100.00 $80.00 $60.00 $72.17 $53.54 $53.54 $40.00 $20.00 PIN $0.70 $4.66 $0.23 $4.66 Signature $- Source: Mercator Advisory Group, 2013 Pulse Debit Issuer Study ©2013 Elan Financial Services & Mercator Advisory Group 11 | Strategies for Reducing Fraud The Federal Reserve Bank of Minneapolis found that 62% of financial institutions reported a reduction in their fraud losses in 2011 by implementing changes to their risk management practices. • • In 2011, 46% of the respondents had experienced an increase in fraud losses over the previous year. 93% of respondents to this study had total assets under $1 billion. The rest were under $10 billion in assets. Areas of Change % Financial Institutions Enhanced fraud monitoring system 69% Staff training and education 63% Enhanced internal controls and procedures 38% Adopted/increased use of risk management tools offered by the financial institution or its financial service provider 38% Enhanced method to authenticate customer and/or validate customer account 13% Source: 2012 Payments Fraud Survey Summary (Federal Reserve Bank of Minneapolis) ©2013 Elan Financial Services & Mercator Advisory Group 12 | • • • The Future Fraud will not innately slow down. Perpetrators will jump from one channel to another. EMV implementation will slow down, but will not stop. Card Not Present (CNP) Fraud continues to grow quickly online – Path of least resistance for the fraudster – Global growth of EMV chip cards will continue – eCommerce is fastest growing sales channel for merchants • North America E-commerce industry standard = 1% of total online revenue in 2011 (Cybersource) ©2013 Elan Financial Services & Mercator Advisory Group 13 Detecting and Blocking Debit Fraud Brian Fisher Card Services Product Manager Elan ATM & Debit Services Troy Cullen President Strictly Private & Confidential | Card Fraud – now American’s biggest fear Study: Card fraud Americans' biggest fear - It 'out-fears' war, terror, hacking and deadly epidemics 1 out of every 5 debit card holders in the U.S. has experienced fraud on their card in the last five years. That is the fourth highest rate among 17 countries surveyed – only Mexico, China and India have greater rates of debit card fraud. ©2013 Elan Financial Services & Mercator Advisory Group 15 | • • • • Identify Theft Card Not Present (CNP) Not Received Issue (NRI) Stolen Cards • Counterfeit Cards ©2013 Elan Financial Services & Mercator Advisory Group Many Forms of Debit Card Fraud 16 | Low cost of entry for card counterfeiters • Counterfeiting cards can be done easily and cheaply. • Card-making materials – including magnetic strip encoders, embossers and readers are not illegal to buy. • Overseas web-sites peddle stolen card numbers for $15 to $20 ©2013 Elan Financial Services & Mercator Advisory Group 17 | Debit Card Skimming at the ATM • The skimmer is a device a criminal places over the slot where a customer inserts their debit card in an ATM. • The skimmer scans the data from the card’s magnetic strip, and then passes the card into the ATM where it was originally intended to go. • To obtain the PIN number, the suspects either used a small hidden camera to catch video of what people were typing, or a device placed over the keypad that stores PIN numbers. ©2013 Elan Financial Services & Mercator Advisory Group 18 | • • • The Cost of Skimming in the U.S. Over 400,000 ATM’s located in the U.S. ATM skimming costs U.S. banks almost $1 billion annually. Cases reported to the Secret Service has grown 10% for the past 3 years. ©2013 Elan Financial Services & Mercator Advisory Group 19 | ©2013 Elan Financial Services & Mercator Advisory Group Compromised ATM 20 | ©2013 Elan Financial Services & Mercator Advisory Group Compromised ATM 21 | ©2013 Elan Financial Services & Mercator Advisory Group Receiver in car… 22 | ©2013 Elan Financial Services & Mercator Advisory Group Card Encoder 23 | ATM Skimming Protection • NCR Skimming Protection Service and Diebold ATM Skimming Alert™ Monitoring • Provide real-time detection and alerting of the presence of a fraudulent device on the ATM ©2013 Elan Financial Services & Mercator Advisory Group 24 | Data Analytics Tools • Used daily to analyze identified ATM and POS transaction fraud. • Analysts sift through data to find the starting point of the fraud – also known as the “point of compromise.” ©2013 Elan Financial Services & Mercator Advisory Group 25 | • Next Step: Identify cardholders that conducted “good” transactions at that location, but have yet to experience fraud on their accounts. • Counterfeit Card Alerts delivered on a daily basis allowing FIs to take proactive action to prevent fraud. ©2013 Elan Financial Services & Mercator Advisory Group Counterfeit Card Alerts 26 | Transaction Authorization Blocking • A powerful weapon to stop debit card fraud • Block ATM or POS transactions in real-time using pre-defined criteria • Transaction authorization blocking may include a single rule or a combination of rules set by the client ©2013 Elan Financial Services & Mercator Advisory Group 27 | • • • Why Transaction Authorization Blocking is So Effective Allows banks to tailor denial conditions to a specific footprint Create, update or delete transaction authorization blocking rules according to their schedule Create Individual Rule Exceptions to remove individual cards from a specific transaction authorization blocking rule condition ©2013 Elan Financial Services & Mercator Advisory Group 28 | Pairing Transaction Authorization Blocking with Neural Network Monitoring Elan’s Neural Network Monitoring will help protect your cardholders through three critical stages: • • • Detection & modeling Multi-level transaction analysis Suspicious transaction management ©2013 Elan Financial Services & Mercator Advisory Group 29 | How EMV will Combat Skimming Understanding the main points about EMV: • • it protects cards from duplication it is only useful if a card is required for transaction, and the terminal uses the physical card for authentication ©2013 Elan Financial Services & Mercator Advisory Group 30 | Questions? [email protected] ©2013 Elan Financial Services & Mercator Advisory Group 31
© Copyright 2026 Paperzz