Data Meetup @ Byte Academy By Chaney Ojinnaka and Ivan Kotorov ww w . v endormach.com ww w . v endormach.com V endorMach @ V endorMach VENDOR M A CH
Introductions ww w . v endormach.com V endorMach @ V endorMach VENDOR M A CH
Powering supplier finance while improving efficiencies for buyers VENDORMACH MISSION Page 3 ww w . v endormach.com V endorMach @ V endorMach VENDOR M A CH
Market Drivers INADEQUACY SYSTEM COSTS MANUAL WORKFLOWS $20B $12B Invoice Fraud 31% SMBS underbanked. (80% enterprise overhead) Out of the system ww w . v endormach.com V endorMach @ V endorMach VENDOR M A CH
Market Opportunity 3 Distinct Target Groups SUPPLIERS BUYERS BANKS Liquidity Business continuity New profit centers Reputational Better underwriting data / financial Customer lifetime value cost KYC compliance New sales opportunities 3rd party compliance Page 5 ww w . v endormach.com V endorMach @ V endorMach VENDOR M A CH
Approach AI and Invoices Processes : Neural networks: Thousands of invoices Unpaid and Paid Truthfulness check, probabilities Counterparty insight Mapping relationships Page 6 ww w . v endormach.com V endorMach @ V endorMach VENDOR M A CH
VM Trust Score Model OPEN/REGISTRY CREDIT BUYERS SUPPLIER Page 7 ww w . v endormach.com V endorMach @ V endorMach VENDOR M A CH
Real World Use Cases: Lender API Results : Multiple Double blind Lending and insurance Banking more SMBs Page 8 ww w . v endormach.com V endorMach @ V endorMach VENDOR M A CH
Democratizing supplier finance: getscore.vendormach.com Page 9 ww w . v endormach.com V endorMach @ V endorMach VENDOR M A CH
Questions and Answers ww w . v endormach.com V endorMach @ V endorMach VENDOR M A CH
Appendix: Insights Current score and interpretation Score components • Unpaid and paid revenue (liquidity) • Supply chain age and relationships • Historical events Page 11 ww w . v endormach.com V endorMach @ V endorMach VENDOR M A CH
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