By James Kelly and Nicolas Christiaen
Cash forecasting arguably plays the most important role in ensuring that a company has real visibility of its expected liquidity and can enable treasury teams to invest efficiently. In addition to these benefits, cash forecasting and robust analysis are key to identifying potential problems in converting profit to cash flow during your cash conversion cycle. Operational issues and instances where payments are being accelerated or customer payment terms could be extended can be planned for with the proper tool. This “working capital”-oriented analysis, often left out of the scope in cash flow forecasting projects, can generate the most benefits and therefore deserves more attention.
When we dive into the details of the cash forecasting process, discussions usually produce a lot of guesswork. This is because the challenges can be subtle:
> Modeling your forecast using the different available data sources, while ensuring data quality.
> Incorporating Customer Payment Behavior and handling exception like overdues.
> Avoiding reconciliation issues from intercompany cash flow activity.
> Managing the impact of treasury infrastructure on the cash flow forecast (including the usage of in-house banks, virtual accounts, POBO, COBO).
> Extending the horizon beyond the typical 2 – 4 weeks / 13 weeks (to a long-term cash forecast).
> Excluding FX variations from the overall forecast variance.
In the world of financial technology, the rise of artificial intelligence (AI) carries the potential to increase the power of your data, but often leaves you wondering if the hype lives up to reality. While the idea is intriguing, what role does AI play in the story of cash forecasting?
This year at AFP 2021, we will see how AI-powered technology can make the cash forecasting process more intelligent, automated and efficient. By allowing the consolidation of multiple data sources, the production of smart forecasts, and the fast analysis of differences between actuals and forecasts, treasury teams can gain control of their liquidity and working capital. This allows more time for optimizing the underlying drivers of cash flow and working capital, rather than on the process of pulling together data or asking accountants to pull together direct cash flow forecasts.
In this session, “Cutting Through the Hype: Pearson's AI-Based Cash Forecasting Marvel,” you will learn:
> How Pearson created its data structures and centralized the process of cash forecasting, both short and long range.
> Where exactly Pearson used AI in this overall process, and how the coronavirus pandemic affected this.
> How Pearson improved cash flow forecasting accuracy and what significant benefits were reaped from that improved accuracy.
> What value can be gathered from bank statements and ERP data to provide real insight into the efficiency of the working capital cycle.
This session will cut through the complexity and hype around AI and cash flow forecasting and show you how treasury teams can benefit from this type of technology. Please join us, either in-person or virtually, for this exciting session.
Don’t miss James Kelly and Nicolas Christiaen’s session, “Cutting Through the Hype: Pearson's AI-Based Cash Forecasting Marvel,” and check out all the sessions on the AFP 2021 SESSION EXPLORER. Register for the conference HERE.