FIGHTING FRAUD & CHARGEBACKS 5 STRATEGIES FOR WINNING

FIGHTING FRAUD & CHARGEBACKS 5 STRATEGIES FOR WINNING

2 2016 was a strong year for online sales growth. But fraud and chargebacks more than kept pace. The good news? You can dramatically reduce losses by deploying 5 powerful strategies. 2016: Record Online Sales, Mobile Commerce & Fraud... 3 What Do Chargebacks from Fraud Cost?... 4 Huge ROI When You Reduce Chargebacks... 5 5 Strategies to Fight Chargebacks... 6 1. Superior Fraud Screening and Analytics... 7 2. Real-Time Data... 8 3. Advanced AI and Machine Learning... 9 4. Expert Human Intelligence...10 5. Chargeback Alerts...11 Are You In An Excessive Chargeback Program?...12

3 2016: Record Online Sales, Mobile Commerce & Fraud Desktop ecommerce, mobile sales and CNP fraud all grew by double digits in 2016. 1 The numbers aren t all in yet, however, early data shows: $395 billion in total 2016 U.S. online sales, up 15.6% from $341.7 billion in 2015 2 During Q3 2016, mobile accounted for 20% of all online sales, compared to only 11.1% share just 2 years ago 3 Mobile commerce projected hit nearly $1 trillion next year 4 After one full year of EMV, fraudsters continue moving from card counterfeiting (card present fraud) to card-not-present and mobile fraud, where EMV provides no security. 31% increase in CNP fraud attempts during 2016 holidays in US 5 CNP fraud losses are projected to soar 80% to a record $7.2 billion by 2020, up $3.2 billion from $4 billion in 2016 6 Fraud responsible for nearly 2 out of 3 chargebacks $ BILLIONS 7 Time Period 2015 2016 % Change Q1 (January 1-March 31) $72.2 $83.5 16% Q2 (April 1-June 30) $70.9 $87.2 23% Q3 (July 1-September 30) $69.7 $84.3 21% Q4 (October 1-December 31, estimated) $92.5 $104.5 13% Total $305.3 $359.5 16.4% Thanksgiving + Black Friday 2015 2016 % Change Desktop ecommerce $2.7 $3.3 18% Mobile Commerce $1.0 $1.4 34% Total $3.8 $4.7 23% Cyber Monday 2015 2016 % Change Desktop ecommerce $2.3 $2.7 17% Mobile Commerce $0.8 $1.0 29% Total $3.1 $3.7 20%

4 What Do Chargebacks from Fraud Cost? The true cost of fraud-based chargebacks isn t always apparent. To illustrate the point, we ve highlighted three common merchant types using typical transaction volumes, order sizes, chargeback rates and chargeback fees for various types of ecommerce companies. Even though the chargeback rates are typical, the annual cost of chargeback fees and product losses is striking. -$195,695 chargeback fees and product losses 450 $78 -$470,499 chargeback fees and product losses 2,530 $117 0.6% chargeback rate transactions per day average order 0.4% chargeback rate transactions per day average order Company A is a small e-commerce apparel merchant with fewer than 20 employees. Two employees handle all the phone orders, customer service calls, fraud prevention, manual reviews, chargebacks, etc. Company B is a medium-sized merchant with both brick-andmortar locations and ecommerce sales. They just started offering buy online, pickup in store, which has proven quite popular. -$2,246,960 chargeback fees and product losses 17,100 $33 0.8% chargeback rate transactions per day average order Company C is a large online merchant competing in a highly-competitive market space. They process over 100 thousand transactions every week and use sophisticated e-commerce and fraud prevention tools.

5 Huge ROI When You Reduce Chargebacks Implementing strategies for winning against chargebacks has major financial impact. Revisiting the three merchant scenarios from page 4, you can see that even a conservative 20% reduction in losses from chargebacks delivers significant savings. And when that percentage goes up to a 50% reduction, the financial impact is startling. cut 20% -$195,695 chargeback fees and product losses 450 $78 cut 35% -$470,499 chargeback fees and product losses 2,530 $117 0.48% = $39,139 savings! 0.6% chargeback rate transactions per day average order 0.4% chargeback rate transactions per day average order Company A is a small e-commerce apparel merchant with fewer than 20 employees. After implementing a solution like Kount, they see a 20% decrease in their chargeback rate and save $39,139 in chargeback fees and lost product* annually. 0.26% = $166,774 savings! Company B is a medium-sized merchant with both brick-and-mortar locations and ecommerce sales. With a best-in-class solution like Kount, their chargeback rate drops 35% to save $166,774 in chargeback fees and product losses* annually. * Potential savings equal reduced chargeback fees and product losses only. Does not include additional ROI that Kount can deliver via increased order approvals, reduced fraud mitigation expenses, and other factors, which can be substantial. Kount does not guarantee any level of savings since every merchant is different and may manage their level of risk tolerance differently. cut 50% -$2,246,960 chargeback fees and product losses 17,100 $33 0.4% = $1,123,480 savings! 0.8% chargeback rate transactions per day average order Company C is a large online digital goods merchant competing in a highly-competitive market space. With Kount, their chargeback rate plummets 50%, generating a huge $1,123,480 savings in chargeback fees and product losses* per year.

6 5 Strategies to Fight Chargebacks Win at every stage of the chargeback cycle. Fighting chargebacks isn t a once-a-month task or a discrete event that takes place at a single point in time. There are multiple prevention and interception catch points where you can take action to reduce chargebacks. 1. Superior Fraud Screening and Analytics. Collect & analyze hundreds of data points per transaction, using multiple, integrated technologies to detect fraud. 2. Real-time Data. Check borderline transactions against third party data and capitalize on Big Data in real-time to separate the good from the bad. 3. Advanced AI and Machine Learning. Automate insights from Big Data to reduce manual reviews, cut operating costs, and approve more of your borderline but valid orders. 4. Expert Human Intelligence. Respond to adaptable human adversaries in ways that are best for your specific business. 5. Chargeback Alerts. Intercept bad transactions even after they ve been approved, so you can avoid product losses and chargeback fees.

7 1. Superior Fraud Screening and Analytics Collect and analyze massive amounts of data. Multiple technologies that screen multiple dimensions of every transaction help reduce fraud, lower the number of manual reviews and eliminate false positives (good transactions that only look suspicious). Multiple data elements per transaction. The more data collected Device ID, Geolocation, Transaction Velocity, Order Linking, etc. the more precise and accurate the screening and analysis. Massive network effect. Behavior or attributes that might seem inconsequential within a small data set are revealed to be critical with Big Data analysis. Seamlessly integrated. Individual data points collected by each technology informs the response of all the other technologies to build a cumulative picture of the transaction for maximum fraud detection. Real-time analysis in milliseconds. Fraud prevention should never slow down transactions or impede conversions. Kount employs dozens of proprietary and patented fraud screening technologies integrated at the code level to generate hundreds of data elements per transaction across billions of transactions from over 180 countries...all analyzed in milliseconds.

8 2. Real-Time Data Analysis informed by best-in-class providers. When transaction data by itself is insufficient, outside information sources can fill in gaps to provide crucial context, helping you distinguish good transactions from bad. Integrated access to best-in-class information. Enhance insights by tapping into outside services...but only when necessary. Orchestrate decisions based on your risk criteria. Give weight to factors based on your specific tolerance for risk and fine tune your response to borderline transactions. Single integration, multiple data feeds. The greater the number of information sources, the clearer and more robust the picture, enhancing detection. Multiple and complex use cases. Clear-cut fraud is easy to detect, it s the ability to correctly evaluate borderline transactions that minimizes fraud losses while avoiding lost revenue due to false positives. Kount orchestrates and integrates multiple best-in-class thirdparty data sources to deliver optimal context for detecting and preventing fraud...but only on an as-needed basis to minimize data costs.

9 3. Advanced AI and Machine Learning Machine learning spots patterns in Big Data undetectable to humans. Go beyond just detection and prevention to prediction and thwart emerging fraud threats. Online learning. Extract highly predictive features in real time across the entire network to enhance fraud detection in lowinformation scenarios (e.g., first-time fraud). Offline learning. Non-stop evaluation and refinement of AI results by human fraud experts ensure machine learning algorithms are continuously optimized. Rules integration. AI and machine learning by themselves are not as powerful or precise as when they are complemented by a rulesbased system for maximum control and transparency. Kount s advanced machine learning uses patented graph theory algorithms (PERSONA ) to detect and respond in real-time to emerging threats...but according to rules you set to maximize revenue while holding down fraud.

10 4. Expert Human Intelligence Best practices and the ability to respond to strategic, adaptable fraudsters. Rules set by thinking humans enable a strategic and customized response to rapidly-changing fraud tactics. Domain knowledge. Systems developed by fraud experts start with an inherent advantage over human adversaries. Business-oriented. Instead of rules and thresholds being set to some generic technology standard, you can set them to the precise level of risk suitable to meet your business goals and objectives. Kount fraud experts provide guidance and insight to each merchant, helping them get better at fraud mitigation. Kount s Rules Engine then makes it easy for merchants to finetune rules and thresholds so that detection and prevention responses are customized to each customer s specific appetite for risk.

11 5. Chargeback Alerts When is a chargeback not a chargeback? If you intercept a transaction before the issuing bank applies it to your merchant account as a chargeback, you avoid chargeback fees. But how? It typically takes 45 days from the time a chargeback is actually incurred until a merchant is notified. Yet card issuers often know within hours about a chargeback! It s the lengthy reporting process that introduces the 45-day Chargeback Lag. Fortunately, innovative, cooperative networks of merchants and card issuers like the one founded by Ethoca avoid this Chargeback Lag. With Ethoca Alerts, card issuers send electronic alerts in as little as 1 hour so merchants can intercept bad orders before they become chargebacks. This helps merchants: Avoid merchandise and shipping losses, chargeback fees, etc. Identify other fraudulent transactions linked to the original bad order and halt them, too Approve more borderline transactions (higher sales) yet still reduce chargeback rates Kount integrates Ethoca alerts and reporting to reduce admin time by as much as 75% and automate much of the process of linking other fraudulent transactions to bad order(s).

12 Fight Chargebacks With Kount Complete Avoid chargebacks with a fraud prevention solution like Kount Complete. Kount reviews hundreds of data elements and analyzes them using several technologies and processes. After the data is analyzed, a Kount Score is determined and all relevant data is then reviewed by the Risk Decision Rules Engine to determine whether the transaction is approved, declined or forwarded for further review. All in less than 300 milliseconds...for friction-free checkout. Collect hundreds of data elements per transaction Use data augmentation and feature engineering to multiply the data Massive network effect All capabilities are designed to work together seamlessly Expert system that enables you to control your risk and business strategy We mean real-time decisions in less than the blink of an eye

13 Are You In An Excessive Chargeback Program? In just 30 minutes we ll show you how thousands of other merchants just like you put an end to chargebacks and increased sales as a result. Reduce your chargeback rate in as little as 30 days. SCHEDULE A LIVE DEMO AWARD-WINNING RESULTS Chargebacks are down to less than half of a percent. In fact, we ve been able to reduce dollar losses from chargebacks by 245%. Considering what we pay for Kount, if it stops just one of our big chargebacks a month, it pays for itself. It does that and more, so Kount more than pays for itself. Liz Lee E-Commerce Manager SOURCES: 1 https://www.aciworldwide.com/news-and-events/press-releases/2016/november/us-is-the-global-fraud-hotspot, 2 http://www. fticonsulting.com/about/newsroom/press-releases/fti-consulting-projects-us-online-retail-sales-to-approach-440-billion-in-2017, and, https://www.internetretailer.com/2016/02/17/us-e-commerce-grows-146-2015, 3 http://www.comscore.com/insights/blog/q3-2016-digital- Commerce-Hits-84-Billion-as-MCommerce-Accounts-for-20-of-Sales-for-1st-Time, 4 http://www.statista.com/statistics/226530/mobilepayment-transactionvolume-forecast/, 5 http://cardnotpresent.com/holiday-fraud-attempts-jumped-31-in-2016/, 6 https://cardnotpresent. com/report-businesses-to-lose-7-2-billion-to-cnpfraud-by-2020-may-12-2016/, 7 http://www.comscore.com/insights/presentations-and- Whitepapers/2016/State-of-the-US-Online-Retail-Economy-in-Q3-2016, and, http://www.comscore.com/insights/blog/cyber-monday-becomes- First-Ever-1-Billion-Shopping-Day-on-Mobile