This referenced article is in Forbes and describes the main business focus of Ramp, a 2019 fintech startup based in New York City. The company already has substantial funding and develops corporate card software to improve the end user experiences and ultimately, saves time and money for companies using a Ramp corporate card.
The fintech is a sponsored issuer on the Visa network, and this particular piece describes a main feature of the Ramp card program; that is, expense management.
‘Ramp’s growth and success in attracting venture funding in a challenging economic environment further prove that their business model is prescient and signals the future of fintech, which is using AI and machine learning to deliver more savings to customers….Keeping track of receipts and submitting them with expense reports is the greatest time-waster any corporate cardholder has today. From purchasing software subscriptions, services and supplies to paying contractors, keeping track of receipts to reconcile a corporate card wastes time. For small businesses where people have multiple jobs, tracking receipts can get chaotic.’
Anyone who has ever used a corporate card will understand some level of time consumption and frustration with standard expense reporting processes at many companies. A new level of automation has entered the picture in the past few years with more mobile capabilities available that offer process relief. Ramp automates the matching process of a card transaction and the payment receipt using machine learning.
So highlighting such a feature can create selling differentiation, especially among smaller businesses that may not be particularly dependent on gaining large spending rebate share, and who may have employees more in the ‘app’ generation. Although corporate cards have been primarily used for travel and expense, one of the main challenges for the broader commercial card-based programs (including P cards and virtual cards) is gaining acceptance by merchants in the general B2B payments landscape, thereby limiting spend (and revenues).
That resistance has dissipated somewhat as a result of the pandemic and greater appreciation of card impact on DSO. The article points out that Ramp is gaining spend through their broader platform controls, so in effect replacing P.O.s, which is where P Cards and virtual cards have their use cases. So spend management becomes a more automated and flexible experience, opening up more spend channels.
‘Having designed in AI and machine learning from the very start, Ramp’s spend management platform has the flexibility to tailoring specific workflows to specific customers, matching the nuances of their business. Using machine learning algorithms to learn from and tailor spending policies to each workflow shows accuracy and scale gains because the platform continually looks for and learns what’s best for every client. Eric says that clients can put in rules that further refine the platform’s performance for individual workflows. “You can put further rules too, to say, “Look, I, as a business, want to know anytime that someone spends above $100,” and you can get alerted. There’s a number of safeguards, both in terms of advanced controls that haven’t been possible on other cards and workflows, notifications based on activities that businesses can be set,” Eric explained. Ramp is delivering on this vision as their customer satisfaction and G2 ratings show. The following is an example of how intuitive the user interface is to Ramp, while also providing a glimpse of how powerful its AI and machine learning-based workflows are in highlighting transactions that need attention. ‘
Overview by Steve Murphy, Director, Commercial and Enterprise Payments Advisory Service at Mercator Advisory Group
