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From Artificial Intelligence to Financial Intelligence: Leveraging AI to Strategically Transform Finance Teams

08/03/2018 By

Spend Matters welcomes this guest post from Laurent Charpentier, chief innovation officer and COO at Yooz North America.

As some call it the fourth industrial revolution, artificial intelligence (AI) fascinates us, raises many questions, excites us, even scares us a little. (I’m still not sure I want to be on the same roads as self-driving cars!) But there is no denying that AI makes our daily lives so much easier than it was a few years ago, and much more than imagined.

When we talk about AI, we immediately think about what we use every day, such as virtual assistants or chatbots (e.g., Siri or Cortana), smartphones that identify us through fingerprint or facial recognition, cars that are able to detect pedestrians and to park themselves (often better than humans do). We also think about computers that recognize and analyze documents automatically.

AI is also widely present in the business environment. There is evidence of this in:

  • HR departments that more efficiently optimize a selection process
  • Quality assurance departments anticipating and even preventing problems before they may occur
  • Marketers who predict customers’ needs and optimize interactions between brands and consumers

And AI has made its way into finance departments. As a finance leader or accounting professional, you may ask, How do these technologies impact finance functions and workflows? What transformations can be predicted? How will this technology shape tomorrow’s finance department? The CFO is playing a key role in bringing emerging technologies such as AI to the business.

The concept of automating accounts payable processes first surfaced about 20 years ago. While earlier solutions had nothing to do with current approaches, especially in terms of performance and reliability, they did have the same objective: Automate a tedious and repetitive process to make AP personnel lives easier and optimize the efficiency of finance processes.

Before AI, accounting teams manually created and processed invoices, purchase orders or delivery orders on paper documents. Those documents were then manually entered in computer systems, coded and finally transmitted to the managers for approval and payment. Today, thanks to AI, there are no more manual processes! The AP workflow process is automated by software that analyzes, recognizes, directs and exports data into a company’s ERP/financial system. Before automating the AP workflow, suppliers had little to no insight into payment timing details; now, they have full access to this information in real time.

The use of AI in AP solutions makes a significant positive impact on the finance department. The maturity, reliability and industrialization of the intelligent AP automation solutions of today are leveraging AI to create business models that are now accessible to the small and mid-sized markets — previously only available to enterprise firms. In addition:

  • Algorithms have become more and more reliable, flexible and adaptable, permitting solutions to automatically manage documents with variable structure, such as invoices. As a result, data is automatically recognized in an exhaustive and reliable way, with no prior configuration
  • Software-as-a-service (SaaS) cloud solutions are available to millions of users, which results in constant technological enhancements. This contrasts to older on-premise solutions that limited usage
  • The self-learning (machine learning) capabilities of cloud-based software solutions are constantly improving. These solutions essentially “learn” from their mistakes and do not make them again once humans correct them

The use of AI in financial and accounting systems is also leading to real profits. AI-driven AP automation solutions are able to learn as fast and as accurately as an experienced human to:

  • Identify and interact with suppliers
  • Automatically intake, code, process and route invoices, using OCR (optical recognition technology)
  • Denote payment deadlines, approval workflows and the approvers

All leading to dramatic reduction in processing cycle time and a corresponding savings in costs at every level.

The different thresholds organizations typically reach are based on their automation maturity, illustrating that significant improvements in processing times and cost savings follow technology implementation. We’ve seen improvements in invoice processing time from 45 days to 5 days, processing costs per invoice reduced from $15.00 to about $2.00, and the opportunities to capture early payment discounts rise from only 18% of the time to 75% of the time.

Finance teams will notice a positive transition from a task-driven approach to one of empowerment in which systems driven by AI are now in charge of low-value repetitive tasks — data entry, verifications, referrals and fraud detection — and employees are freed to produce real added value with time for analysis, strategy, creative thinking and decision-making.

In view of the spectacular progress of AI, this new world will be more familiar to you long before a self-driving mail truck will drop the last paper invoices in your office.