Enhancing order-to-cash with artificial intelligence

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Capgemini’s partnership with YayPay delivers frictionless receivables, cash flow, and collections, leveraging artificial intelligence and machine learning to drive enhanced order-to-cash processing.

During my time working at Capgemini, we’ve entered into many partnerships that open up new possibilities for our clients. Each and every one of these partnerships has been exciting in its own unique way.

Capgemini’s global partnership with YayPay is no different, and we continue to successfully leverage YayPay’s accounts receivable and collections management platform to drive frictionless cash collections and order-to-cash (O2C) processing for our clients.

In a recent blog, Sarah-Jayne Martin, Senior Product Specialist, YayPay, discusses how machine learning algorithms can be leveraged to understand customer payment behavior and deliver an accurate prediction on when individual invoices will be paid.

Why is this important we hear you ask? Well, YayPay is one of the enablers in the digital framework that underpins our AI.Receivables solution – part of our Frictionless Finance offer. So, if you want to know more about how YayPay brings value to our customers’ order-to-cash processes, read Sarah-Jayne’s blog below to find out more!

Sarah-Jayne Martin, Senior Product Specialist, YayPay

The recent year has taught us more than ever, that two critical elements of business health are financial and payment projections. Payment projections and cash flow forecasting are integral to growth and maintaining a steady cash flow in both the best and worst of times. In order to generate additional revenue, or backfill lost revenue, an additional supply of cash is always needed.

Production costs, supply and demand fluctuations and market price of goods and services are important considerations in order to better understand the financial health of a company, its impact on working capital and overall profitability.

There are important benefits to be gleaned from financial projections:

  • Keeping a pulse on your company’s current economic status and where it’s headed
  • The ability to meet supply and demand fluctuations in your target market and plan revenue and cash supply
  • Objective goal setting and expectation management within your company for necessary expenses needed for long-term business success
  • Perform market analysis against the competition and track areas of competitive edge and improvement
  • Mitigate risk and long-term concerns by proactively deploying solutions to conserve cash and withhold from unnecessary business expenditures.

YayPay’s proprietary algorithms – a strong competitive edge

YayPay uses a family of machine learning algorithms to understand the payment behavior of your customers and come up with the most accurate prediction on when each individual invoice is going to be paid.

What are the algorithms? YayPay has created two separate models that use the same input data, but have different architectures and approaches:

  • On-time prediction – this model looks at current invoices and is designed to predict if an invoice is going to be paid before the due date. The resulting prediction of this algorithm is a probability of the invoice being paid in time.
  • Overdue prediction – this algorithm is used for overdue invoices only and it is designed to predict which bucket this invoice is going to end up in. The following buckets are used for the predictions:
    • 1–30 days overdue
    • 31–60 days overdue
    • 61–90 days overdue
    • 90+ days overdue

What drives the prediction? When YayPay integrates with your ERP system, it pulls historical documents for the last few years of business, including paid invoices, old payments, credit memos, etc. This data is the core of YayPay’s payment prediction algorithm. YayPay then uses this data to create a customer profile that is based on behavioral patterns of your customers such as average payment time, credit limit, age of the relationship, average days overdue, and seasonality behavior, etc.

The same profiling approach is taken to your business as a whole to understand your typical customers, how they pay you, and what to expect from them. Then, at the invoice level, YayPay also analyzes the individual invoice parameters, such as total invoice amount, the number and dollar amount of invoice items, what invoice items there are (we use natural language processing to understand which kind of product your customers are more inclined to pay for), and notes on the invoice, etc.

All this can be found on our customizable dashboard. YayPay has two separate charts that show projections on when invoices are going to be paid, and how much money you will have on a particular day.

YayPay works with clients from many industries and lines of business. Every business is different and some are more predictable than others. Overall, the accuracy is anywhere from 83% to 94%, which means that YayPay can correctly predict if an invoice is going to be paid in time, or predict what bucket it is going to end up for at least 83% of your invoices. Note, that when we measure the accuracy of the predictions, we use a normalized validation dataset that consists of invoices that were paid 60 to 180 days prior.

Enable a holistic view of your order-to-cash process

Having visibility into your future cash position can prepare you for certain unexpected disturbances. At the end of the day, profitability of a business alone isn’t what keeps the lights on, it’s having a lucrative cash supply. According to an article written by Driven Insights: “Your cash flow projections will never be perfect since there are too many variables (which influence timing) outside of your control. But the general direction will be correct and you will soon learn to use the “levers” for controlling your future cash position. For example, can you invoice your customers earlier? Should you place that collections call? In a pinch, which payment commitments might have flexibility on payment timeline?”

Maintaining a regular pulse on your cash flow, leveraging solutions like YayPay and regularly reviewing aging reports that use payment algorithms will allow your business to respond to short-term payment issues and long-term cash sustainability. The key here is to maintain visibility into your company’s cash flow on a regular basis so you can begin to see trends, analyze the data, and evolve your business planning according to this regular digestion of data.

Having a holistic view of your entire receivables business will better position you for greater financial health, happier customers and an improved total customer experience.

This blog is reproduced with the kind permission of YayPay. Read the original here.

Keen to know more? Learn how Capgemini’s AI.Receivables solution – enabled by YayPay –delivers frictionless, next-generation order-to-cash processes to make Frictionless Finance a reality for your organization.

Divya Turner is the current global process owner for order-to-cash (O2C), the product owner for AI. Receivables, and has over 15 years of experience in driving innovation in O2C.



Sarah-Jayne Martin is a finance professional specializing in the areas of credit management, payment processing, collections, and accounts receivable. With over 20 years’ experience in the field managing large global teams with a strong focus on improving efficiency within the O2C cycle. Hailed as an industry expert in the field, Sarah-Jayne makes active appearances in the space, frequently featuring on thought-leading panels and discussions.

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