Data Meetup Byte Academy Chaney Ojinnaka and Ivan

Data Meetup @ Byte Academy Chaney Ojinnaka and Ivan Kotorov ww w. v endormach. com V endor. Mach @ V endor. Mach VENDOR M A CH

Introductions ww w. v endormach. com V endor. Mach @ V endor. Mach VENDOR M A CH

Powering supplier finance while improving efficiencies for buyers VENDORMACH MISSION ww w. v endormach. com V endor. Mach @ V endor. Mach VENDOR M A CH Page 3

Market Drivers SYSTEM COSTS $12 B Invoice Fraud INADEQUACY MANUAL WORKFLOWS $20 B (80% enterprise overhead) ww w. v endormach. com V endor. Mach 31% SMBS underbanked. Out of the system @ V endor. Mach VENDOR M A CH

Market Opportunity 3 Distinct Target Groups BUYERS SUPPLIERS BANKS ü Business continuity ü Liquidity ü New profit centers ü Reputational / financial cost ü Customer lifetime value ü Better underwriting data ü 3 rd party compliance ü New sales opportunities ü KYC compliance ww w. v endormach. com V endor. Mach @ V endor. Mach VENDOR M A CH Page 5

Approach AI and Invoices v ww w. v endormach. com V endor. Mach @ V endor. Mach VENDOR M A CH Processes: ü Neural networks: Thousands of invoices ü Unpaid and Paid ü Truthfulness check, probabilities ü Counterparty insight ü Mapping relationships Page 6

VM Trust Score Model OPEN/REGISTRY CREDIT BUYERS SUPPLIER ww w. v endormach. com V endor. Mach @ V endor. Mach VENDOR M A CH Page 7

Real World Use Cases: Lender API v ww w. v endormach. com V endor. Mach @ V endor. Mach VENDOR M A CH Results: ü Multiple ü Double blind ü Lending and insurance ü Banking more SMBs Page 8

Democratizing supplier finance: getscore. vendormach. com ww w. v endormach. com V endor. Mach @ V endor. Mach VENDOR M A CH Page 9

Questions and Answers ww w. v endormach. com V endor. Mach @ V endor. Mach VENDOR M A CH

Appendix: Insights Current score and interpretation Score components • • • ww w. v endormach. com V endor. Mach @ V endor. Mach VENDOR M A CH Unpaid and paid revenue (liquidity) Supply chain age and relationships Historical events Page 11