KYC Automation: Scale, Speed, Standardize Merchant Underwriting
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- Annabella Holmes
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1 Know Your Customer (KYC) KYC Automation: Scale, Speed, Standardize Merchant Underwriting
2 Visit to join in MAC Benefits include: Protect and invest in your organization by receiving fraud alerts. Leverage professional development opportunities for you and your employees. Get the latest updates from card brands and government agencies. Discounts to MAC and partners events. Members include: Banks Card Brands Payment Facilitators Processors ISOs/Acquirers Vendors Cost: Corporate memberships - $ for four individuals. $75 for each person thereafter. Vendor memberships - $ for four individuals. $100 for each person thereafter.
3 KYC: A Broad Term and Business Process Different KYC by Industry and Use Case: Banking Lending Vendor Management Merchant Acquiring
4 Facets of Merchant KYC
5 What is Merchant KYC? 1. Validate what a merchant discloses 2. Discover what might be omitted 3. Using trusted data sources
6 Trusted Information Sources for KYC Government databases Secretaries of State CFPB FTC Pacer / Justia OFAC List Proprietary databases Better Business Bureau Yellow Pages Whois domain ownership Open Source databases Business Reviews, Yelp, Social Media Consumer complaints board s Places databases and APIs Web / News / Mapping Google / Bing web and news searches Satellite and Street views Address validation
7 Merchant KYC Automation 1. What is Merchant KYC? 2. Why Automate KYC? 3. How to Automate? 4. Who Should Automate? 5. Results of Successful KYC Automation
8 What is Merchant Business Discovery? High Level A lot of questions to answer! 1. Is merchant a real business? 2. Can applicant be associated with business? 3. What is the business actually selling? 4. How can the business be categorized? 5. Does business fall within accepted parameters? 6. How is business disclosing consumer practices? 7. Is business ripping off consumers? 8. Is business a bad actor? 9. Does business have legal or compliance problems? 10. Is business or principals on sanctions lists?
9 Merchant Business Discovery: Low Level A lot of manual work to perform! 1. Validate the business exists at address provided on the application. 2. Validate the name of applicant is associated with the business. 3. Determine what products and services the business is selling. 4. Determine the business primary and secondary categories. 5. Determine if the business is involved in prohibited or high risk products. 6. Crawl the business Website capturing samples of products and services. 7. Determine if the Merchant has a Website if URL not provided. 8. Locate merchant s consumer policy disclosures (refund, privacy, shipping, terms of service, contact us). 9. Crawl Website for both prohibited and required words or phrases. 10.Detect in which country the Website is hosted.
10 Merchant Business Discovery: Low Level Even more work to perform! 11. Perform OFAC fuzzy matching on business and principals names and address. 12. Detect if the website is hosting malware, adult content or spam. 13. Review the the Website s traffic history and affiliated websites. 14. Review the domain name ownership. 15. Determine if the business has a working website or is it parked or down? 16. Does the business have a poor reputation with consumers? 17. Does the business have legal problems? 18. Does the business have governmental compliance problems? 19. Is the business address provided a business location or a PO Box? 20. Review the social media of the business and principals. 21. Perform Web and News searches on the business and principals.
11 Why automate KYC? Manual KYC is a lot of effort! 1. Gather KYC Data 2. Analyze KYC Data 3. Apply Analysis to Underwriting
12 Why automate KYC? Underwriting Bottleneck! Manual KYC Often the slowest part of the merchant underwriting process. 90% is manual information gathering Only about 10% analysis Expensive and Inconsistent Cannot Avoid KYC Big fines Risk loss of acquiring bank or card brand Automating KYC eliminates the chore Additional Benefits Allows KYC data to be used to automate underwriting Unless KYC is automated, underwriting can not be fully automated.
13 What does Automated KYC Look Like? Readable KYC PDF Report All KYC data in one PDF file Proof proper KYC performed Starting point for analysts to review potential red flags Enhanced due diligence research starting point Meets card brand requirements to capture certain information Samples of merchant s products/services Required consumer disclosures Determine if website is parked
14 What does Automated KYC Look Like? KYC API Data for Rulesets or Scoring "bbb_results": { "grade": "F", "OrganizationName": "Vemma Nutrition Company", "BusinessURLs": [ " " " " " " " ] "ftc_result": { "n_total_by_site": { "Federal Trade Commission": "5" }, "justia_dockets": { "n_total": 8, "n_scraped": 5 },
15 Automated KYC Medium and Large Scale via API I. KYC Business Process Accomplished Automatically Handle large scale Speed underwriting Make KYC consistent Improve KYC and underwriting quality Eliminate data entry to request KYC Eliminate manual retrieval of KYC reports II. Then, Leverage KYC API Data for Merchant Decisioning Achieve auto-approvals on a % of applicants
16 KYC API as Part of Automated Underwriting KYC data is pulled into an Underwriting Management System via API to further automate the merchant underwriting process.
17 How to Automate KYC: Use APIs to Gather KYC Data Several API data sources: 1. Merchant Review & Discovery 2. Credit 3. Bank Account Validation
18 What s an API? (Application Programming Interface) APIs communicate information back and forth between computer systems securely over the Internet: 1. Request for credit information 2. Request for bank account validation 3. Request for KYC discovery information
19 How to Make it Work: Use KYC API Data to Help Automate Decisioning 1. Determine KYC questions to be answered 2. Map KYC and other data to answer questions 3. Create automated decisioning using: a) Rule sets b) Scoring c) Machine Learning 4. Identified potential red flags routed to an underwriter for manual review 5. A percentage of applicants can be auto-approved
20 Example Rule Sets: Using KYC data to answer underwriting questions 1. Is company legitimate? 2. Can applicant name be associated with company? o Secretary of State registration data o Better Business Bureau o Yellow Pages o Places databases o Reviews and Complaint databases o Web & News searches o Whois database
21 Example Rule Sets: Using KYC data to answer underwriting questions What is the merchant selling? Website crawl data Social media analysis Web searches Business classification data from: o Better Business Bureau o Yellow Pages o Corporate records o Places APIs
22 Example Rule Sets: Using KYC data to answer underwriting questions Is the merchant a potential bad actor? Consumer ratings Consumer complaints Legal actions Governmental actions Regulatory actions Watch lists Business category
23 Does it make sense to automate KYC without APIs? Yes. Automate the KYC Business Process: Save 90% of time over manual KYC Consistency, quality, fully documented KYC Still manual: o Data entry to request KYC reports and data o Manual review of KYC reports o Application of KYC information to decisions
24 Does it make sense to integrate into KYC APIs? Yes! Automate the KYC Business Process: Scale and speed KYC Cost reduction Plus, Further Automate Merchant Underwriting: No manual input or retrieval Use KYC data in scoring/rule sets/ machine learning Auto-decision a percentage of merchant applicants Speed and scale merchant underwriting
25 KYC Automation Results Successful KYC Automation Delivers: Scale KYC Cost savings KYC consistency and quality Significant KYC speed increase Well-documented KYC for audits Further automate underwriting with KYC data Underwrite faster with high quality
26 Q & A Contact Info Matthew Parker Principal KYC Systems LLC matthew.parker@kycsitescan.com Palo Alto and New York City Areas kycsystems.com
27 SAVE THE DATE MAC 2019 Annual Conference March 12-14, 2019 Park MGM - Las Vegas, NV Don t miss the premier payments industry risk conference.
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