Ecommerce Forum - Ogone

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Ecommerce Forum - Ogone

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Ecommerce Forum - Ogone

  1. 1. Increasing sales turnover by lowering fraud<br />Pierre Willaert<br />Country Manager Ogone Belgium<br />Stéphane Fauquenoit<br />3 Suisses Belgique<br />
  2. 2. Ogone presentation<br />3 Suisses presentation<br />Case Study<br />Solutions and results<br />
  3. 3. Ogone – Whatwe do?<br />
  4. 4. Flexible payment solutions<br />
  5. 5. 3 Suisses - Presentation<br />
  6. 6. 3 Suisses Belgium – Part of Group 3SI<br />
  7. 7. 3 Suisses Belgium – Saint Brice S.A. and its commercial entities<br />
  8. 8. 3 Suisses Belgium – Some figures<br />
  9. 9. Case Study<br />
  10. 10. 2006<br />2008<br />Atos et les autres<br />Dès 2006, utilisation de la plateforme Ogone pour les<br />flux Visa / Mastercard et cela en mode « Batch »<br />Dès 2008 avec la poussée du WEB, utilisation du module<br /> « E-commerce ».<br />Introduction of Ogone at St. Brice<br />
  11. 11. 3 Suisses – Payment Methods<br />Increasing Sales Conversion Ratio Thanks To a LargerNumber of Payment Methods…<br />
  12. 12. Two groups of Payment Methods<br />Debit Payment MethodsCreditCards<br />5 M €<br />33.600 Transactions or 48%<br />36.500 Transactionsor 52%<br />
  13. 13. Two groups of Payment Methods<br />Debit Payment MethodsCreditCards<br />Average transaction value: 69,52 €<br />Average transaction value: 80,60 €<br />
  14. 14. 2 groups of Payment Methods – 2 Risks<br />Debit Payment MethodsCreditCards<br />
  15. 15. 2 groups of Payment Methods – 2 Risks<br />BeforeJune 2009<br />Financial and Customer Confidence Impact<br />80,60 €  327 €<br />(Source ATOS)<br />Site Web 3suisses.be<br />
  16. 16. Fraud Impact in stronggrowthcontext<br />Financial and Customer Confidence Impact<br />(Source ATOS)<br />Site Web 3suisses.be<br />
  17. 17. Solution and results<br />
  18. 18. Fraudulent transactions<br />Ogone Advanced Fraud Detection Module as fromJune 2009<br />(Source ATOS)<br />Site Web 3suisses.be<br />Using Ogone Fraud Detection Module Advanced, Online Fraud doesnot ‘undress’ 3 Suisses anymore<br />
  19. 19. Fraud Management – Axe 1 <br />3D Secure technology identifies your customers when validating the payment; the aim is to reduce the risk of contestation due to identity theft<br />
  20. 20. Fraud Management – Axe 2 <br />Blacklisting existing fraud data enables us to anticipate online fraud<br />Information on an existingfraud on one of St.Brice’smerchantsisimmediatelyavailable for all theirmerchants<br />
  21. 21. Fraud Management – Axe 3 <br />Manual check<br />Fraud evaluation in function of an online scoringwhichis 100% linked to our business<br />
  22. 22. Online Fraud Scoring – 65 Key Criteria<br />
  23. 23. Online Fraud Scoring – Use of Key Criteria<br />‘3D Secure’ Cards<br /><ul><li>Cardholderidentified?
  24. 24. Full 3D Secure Card?</li></li></ul><li>Online Fraud Scoring – Use of Key Criteria<br />‘3D Secure’ Cards<br />Country of the IP Address<br />Usage of the IP Address<br /><ul><li>Is the level of utilisation ‘normal’?
  25. 25. Doesitconcern a risky country?</li></li></ul><li>Belgiancardwith 3D Secure OK, but withIndian IP address<br />(All transaction data on this screenshot are fictive and for information purposes only)<br />
  26. 26. Number of transactions on same IP addressisextremelyhigh<br />(All transaction data on this screenshot are fictive and for information purposes only)<br />
  27. 27. Online Fraud Scoring – Use of Key Criteria<br />‘3D Secure’ Cards<br />Country of the IP Address<br />Usage of the IP Address<br /><ul><li>Is the level of utilisation ‘normal’?
  28. 28. Doesitconcern a risky country?</li></ul>Country of the creditcard<br />Usage of the creditcard<br />
  29. 29. Creditcard country is not autorised<br />(All transaction data on this screenshot are fictive and for information purposes only)<br />
  30. 30. Online Fraud Scoring – Use of Key Criteria<br />‘3D Secure’ Cards<br />Country of the IP Address<br />Usage of the IP Address<br /><ul><li>Is it ‘normal’ to have 2 different countries?
  31. 31. Is it ‘normal’ to use a belgiancardwith an IP fromIvoryCoast?</li></ul>Country of the creditcard<br />Usage of the creditcard<br />Creditcard country <> IP address country<br />
  32. 32. Online Fraud Scoring – Use of Key Criteria<br />‘3D Secure’ Cards<br />Country of the IP Address<br />Usage of the IP Address<br />What about the email addresstransmittedwhencreating the 3suisses.be account (…@hotmail, …@gmail, …)?<br />Country of the creditcard<br />Usage of the creditcard<br />Email Address<br />Creditcard country <> IP address country<br />
  33. 33. Impact on the score … potentialrisk<br />(All transaction data on this screenshot are fictive and for information purposes only)<br />
  34. 34. Impact on the score … potentialrisk<br />(All transaction data on this screenshot are fictive and for information purposes only)<br />
  35. 35. Online Fraud Scoring – Use of Key Criteria<br />‘3D Secure’ Cards<br />Country of the IP Address<br />Usage of the IP Address<br />Country of the creditcard<br />Usage of the creditcard<br />Time and day of the transaction<br />Email Address<br />Creditcard country <> IP address country<br />
  36. 36. Online Fraud Scoring – Use of Key Criteria<br />‘3D Secure’ Cards<br />Country of the IP Address<br />Usage of the IP Address<br />Country of the creditcard<br />Usage of the creditcard<br />Time and day of the transaction<br />Email Address<br />Creditcard country <> IP address country<br />
  37. 37. Transaction withlow score – situation is OK<br />(All transaction data on this screenshot are fictive and for information purposes only)<br />
  38. 38. Autorised transaction, withhigh score – attention required<br />(All transaction data on this screenshot are fictive and for information purposes only)<br />
  39. 39. 1st ‘positive’ indicator – cardholderidentified<br />(All transaction data on this screenshot are fictive and for information purposes only)<br />
  40. 40. 2nd indicator – combination of differentparameters shows a veryhighrisk<br />(All transaction data on this screenshot are fictive and for information purposes only)<br />
  41. 41. Filter on transactions with same parameters – 3rd indicator gives a « suspicion of fraude »<br />(All transaction data on this screenshot are fictive and for information purposes only)<br />
  42. 42.
  43. 43. The suspiciousfraudisconfirmed – the nextday, a new transaction has been blockedthanks to blacklisted email<br />(All transaction data on this screenshot are fictive and for information purposes only)<br />
  44. 44. Startingfrom the initial transaction, 34 transactions withat least 1 commonparameterdetected and stopped<br />(All transaction data on this screenshot are fictive and for information purposes only)<br />
  45. 45. Profile of our transactions and fraude<br />62.49%<br />20.99%<br />2.68%<br />122 fraudes pour 110.075 transactions soit 0.11% de fraude<br />PB / GB / USA / …<br />(Source ATOS - base de 2008 à 03/2010)<br />13.84%<br />
  46. 46. Conclusion<br />
  47. 47. Conclusion<br />Rien n’est jamais gagné, il faut une vigilance de tous les instants, et dans ce domaine la solution OGONE permet de juguler l’impact « financier et client » de la fraude. <br />De 06/2009 à 03/2010, nous avons arrêté 71 cas de fraudes pour un montant total de 22.612,14 €, soit un panier moyen de 318,48 € et 793 transactions ont été refusées pour un montant de 173.889,42 €, soit un panier moyen de 219,28 €<br />
  48. 48. Questions?<br />

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