Service Introduction Document_(O-PLUX Summary).pdf
- 1. Note: This document is an excerpt translation of the original Japanese document and is only for reference purposes. In the event of any discrepancy between this translated document and the original Japanese document, the latter shall prevail.
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- 4. （C）Cacco Inc. All Rights Reserved. 4 *1 TOKYO SHOKO RESEARCH, LTD., “Survey on the number of EC sites in Japan introducing paid fraud detection service,” (as of the end of May 2021) *2 Only selected companies with permission to be listed are included. As of end of April, 2022. Hobby Food and health food PC and tablet Cosmetics and hair care Apparel and sports Video and audio equipment Travel Furniture and DIY Hosting Online shopping malls, MVNO, and others Bank Ticket NFT Game
- 5. （C）Cacco Inc. All Rights Reserved. 5 Ecommerce Enabler/ Shopping Cart Payment Gateway / PSP
- 7. Chargeback Purchases made with someone else's credit card information. Both the product and money are uncollected due to a chargeback request from the credit card company. Promotion Abuse Promotion abuse by users creating duplicate accounts Resale Fraud Bulk purchases, hoarding, and high resale of products. Claims from the original purchasers and damage to the brand image due to resale also occur. Spam Order Nuisance behavior with repeated orders and cancellations, with no intention to purchase Sample Abuse Unauthorized acquisition and resale of samples that are limited to a first time or limited quantity Increased Monitoring Increased man-hours spent responding to fraud by in-house personnel who visually check orders for suspicious items Point Abuse Fraudulent point acquisition by repeatedly returning or canceling orders in order to earn points without purchasing the products Lost Sales Opportunity Opportunity losses such as concerns about basket drops due to 3D Secure, suspension of foreign- issued cards, and capped amounts. COD Fraud Refusal to receive cash on delivery orders. It occurs with the failure of a resale, and the loss of sales opportunities and, Increased return shipping costs. Generation of unauthorized affiliate commissions due to self- made efforts. Inability to measure correct CVRs and negative impact on sales promotions. Affiliate Fraud 1 2 3 4 5 6 7 8 9 10
- 8. Chargeback Flow of chargeback from fraudulent card use Fraudster orders and receives the products The cardholder notice the false transaction The cardholder files a claim to the card company The Card company chargeback the E- Commerce The Fraudster obtains card detail illegally Approximately 2-3 months until the fraud is discovered Unauthorized user Cardholder Merchant
- 9. Promotion Abuse Flow of promotion abuse The fraudster order the discounted or promoted product The Fraudster make another fake account to claim and order the promoted product The honest customer cannot claim the promotion because the quota has been used by the fraudster The EC company loses customer trust and revenue The fraudster saw the promotion and claimed it The effect is instantaneous, and the promotion is not effective Unauthorized User Customer Merchant ? ?
- 10. 10 Resale Fraud Flow of fraudulent reselling activities The fraudster receives the product The fraudster sets up an online store to sell the product People buys products from the fraudster at an inflated price The E-commerce suffered customer trust issue The fraudster buy discounted/ limited products in bulk The participating merchant will lose out customers and customers will have to buy with the inflated price Unauthorized User Customer Merchant
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- 12. V Benefit 02 Automation of Monitoring Work • Able to reduce monitoring operation workload in each platform • Standardizes operations regardless of skill or order volume. V Massive Economic Impact • Reduce the amount of fraudulent damage and increase Revenue • Solid Fraud system costs a fortune to build, but our system can be installed for $249/month (lowest price in the industry) Benefit 03 V Real-time Fraud Detection • Real-time analysis of multiple screening factors are combined to check for possible fraudulent orders/ transactions prior to actions(like shipment) Benefit 01 V • Incorporating specialized fraud consultants and machine learning/AI rule tuning, the our system can responds & adapt quickly to new fraudulent tactics. Benefit 04 Professionals x AI Examinations
- 13. O-PLUX Case Studies - Summary JINS (Glasses Retailer) The Issue Fraudulent orders and the number of chargebacks have skyrocketed with the increase in orders done through the client’s e-commerce site Engagement ROI O-PLUX solution was implemented within 2 months and reduced the client’s chargeback costs by 80% within the first four months of usage “The API collaboration went smoothly and was very helpful.. We feel that the significant reduction in chargebacks is a result of the implementation.” -Dai Sato, IT Digital Department DIY Factory (Online DIY Shop) The Issue As transactions reach 1,500 per day, fraudulent orders and chargeback costs cause great financial burden and require significant man-hours Engagement ROI Fraudulent orders, which were previously at an average of ~100 cases per month, have been reduced to almost zero “The number of fraudulent orders decreased rapidly from the first month of implementation…I feel that we have become an `EC site' that is not targeted by people who repeatedly place malicious orders.” -Niko Yokoyama, E-Commerce Department PetGo (Pet Supplies Store) The Issue The client detects an increasing number of fraudulent orders with varying complexity, about 5,000 cases per month, using their own system Engagement ROI During the trial phase, O-PLUX was able to detect cases which went unnoticed by the client’s internal system “I think that the fact that O-PLUX detected fraudulent orders that went unnoticed because our company's system had a lot of fraud detection logic built in was more than we expected.” -Fumihiko Koide, Director
- 14. “The API collaboration went smoothly and was very helpful.. We feel that the significant reduction in chargebacks is a result of the implementation.” -Dai Sato, IT Digital Department JINS O-PLUX Case Studies - JINS Pre-Implementation of O-PLUX Post-Implementation of O-PLUX Fraudulent orders and the number of chargebacks have skyrocketed with the increase in orders done through the client’s e-commerce site O-PLUX solution was implemented within 2 months and reduced the client’s chargeback costs by 80% within the first 4 months of usage Coｍpany 80% Reduction All Transactions Chargeback All Transactions Chargeback Business Overview Year Established Annual Sales Employees Jins Co., Ltd. Japan’s #1 Eyeglass Brand 2018 US$ 351 million (Aug 2022) 2,118 Credit Card Transactions (50%) Credit Card Transactions (50%)
- 15. “The number of fraudulent orders decreased rapidly from the first month of implementation…I feel that we have become an `EC site' that is not targeted by people who repeatedly place malicious orders.” -Niko Yokoyama, E-Commerce Department DIY Factory O-PLUX Case Studies – DIY Factory Pre-Implementation of O-PLUX Post-Implementation of O-PLUX The client receives ~1,500 transactions per day and manually checks for potential fraud, which require lengthy man-hours and does not stop cases accurately After unsuccessful results of installing 3D Secure initially, the client implemented O-PLUX which was able to prevent fraudulent orders and reduce chargeback costs to almost zero Coｍpany Business Overview Year Established Annual Sales Employees Daito Co., Ltd. Japan’s largest online DIY shop 1952 US$ 44 million (Dec 2022) 26 All Transactions Checked manually but only 50% are stopped successfully leading to: Fraudulent Orders Uncollected payments Chargeback costs Lengthy man-hours for manual checking Fraudulent orders have decreased and chargeback amounts reduced to almost zero All Transactions Fully automated transaction monitoring
- 16. O-PLUX Case Studies – How Fraud is reduced 0 100 200 300 400 500 600 700 How Fraud is reduced after O-PLUX implementation
- 17. Competitor’s FDS Cacco’s FDS Internal labor cost for anti-fraud measures (2~3 persons) Fraud Detection System operation costs (infrastructure, software, etc.) In-house FDS Fraud Damage Cost Internal labor cost for anti-fraud measures (0~0.5 persons) Internal labor cost for anti-fraud measures (2~1 persons) Cacco Service fee Fraud Damage Cost System service fee Fraud Damage Cost Able to reduce total cost! ■ Service fee •Cacco’s service fee is cheapest compared to other company ■ Internal labor cost •Increased transactions do not increase monitoring man-hours due to economies of scale ■ Fraud Damage cost •High detection accuracy reduces the amount of fraudulent damage Internal labor costs/Fraud damage cost can be reduced Able to reduce total cost significantly if you use Cacco’s service compared to in-house operation
- 18. Cacco provides a low-cost and easily deployable option, making it accessible not only for large enterprises but also for SMEs, thanks to its industry-leading price Cacco Individual FDS company Payment Gateway FDS Service Coverage Cost Overview Deployment Accuracy Evalu ation • Most solutions are for enterprise companies, and it leads higher price and longer implementation time than Cacco • Transaction-based billing, making the service more expensive than Cacco • Lower detection accuracy due to fewer inputs handled for detection • Low cost/short implementation time • Full coverage of login/payment fraud prevention •Provides total anti-fraud solutions •No solution to prevent login fraud •Provides total anti-fraud solutions •95%~ •Minimum 1,000~2,000 USD per month •4 weeks for implementation •Accuracy is lower because only payment information is used. •4 weeks for implementation •95%~ •Minimum 1,000~ USD per month •Start from 249 USD •8~12 weeks for implementation
- 19. 300K USD 36K USD Before After Amount of fraud damage (chargeback damage) Large size company (Total transaction amount: 120M USD) Annual savings of 264K USD per year Small-Mid size company (Total transaction amount: 6M USD) 15K USD 1.8K USD Annual savings of 13.2K USD
- 21. O-PLUX uses various detection logics to analyze order information in detail, which lead high accurate detection
- 23. （C）Cacco Inc. All Rights Reserved. Initial Cost Monthly Fee Transaction Size Price 0 USD ～500/month 249 USD ～1,000/month 299 USD ～3,000/month 549 USD ～5,000/month 799 USD 5,001~/month 799 USD +0.07 USD/trx