If you think about the B2B payments software and services innovation landscape, we see four general categories, which includes cash cycle solutions, enterprise software, cards-related and cross border. New rails and faster versions of old rails are mixed in with how these other innovations can be optimized. There is of course a fair amount of overlap among tech providers, and much of the startup and collaboration activity is in the cash cycle, where additional free cash flow can be created by digital adoption. This posting appears in venturebeat and discusses the use of AI by one of the payables automation providers, Bill.com.
‘The company today took the wraps off the Intelligent Business Payments Platform, an end-to-end financial workflow automation toolset designed to streamline payment processes for Bill.com’s more than 3 million members….. How? Well, in part through an AI agent dubbed Intelligent Virtual Assistant, or IVA, that automatically tenders invoices and kicks off the approval process, expediting it by a factor of two to three compared with manual methods. The company says the machine learning algorithms underpinning IVA, which were trained on more than 52 million bills and invoices handled over the past year, can automatically capture data from invoices and spot human errors. Moreover, IVA is capable of recognizing bill approval and thresholds for payments, routing workloads, and automatically creating business rules personalized to customers and payees.’
We just posted a Viewpoint document on the B2B payments space covering all these areas, and again point out the convergence of processes and systems that make up what has generally been referred to as the ‘Procure-to-Pay’ cycle (although it now goes beyond that into reconciliation on both the buyer and supplier side of things). So what Bill.com is doing involves machine learning capabilities that were built upon their own transaction data. Although the SV-based company has been around now for about 11 years, the article indicates that the learning algorithm was based on the past year’s data. ML of course is designed to continuously improve based on the continuous subsequent data reviews. It sounds like this initial offereing is domestic only and will look to add furher features and functionality.
‘IVA currently has a few limitations, chiefly an inability to recognize foreign currency or create separate bills from multipage documents. But Bill.com founder and CEO René Lacerte expects it will still save customers thousands of hours of accurate data entry — the equivalent of over 35 business days per year, on average. Lacerte cites a Bill.com survey indicating that 80% of the $58 trillion paid between businesses each year in the U.S. involves paper checks.’
There are surely more cash cycle improvement options than ever before, and business adoption inertia should further waffle as companies see competitors discover rewards through better navigation and intelligence from their back offices.
Overview by Steve Murphy, Director, Commercial and Enterprise Advisory Payments Service
