Digital Transformation » Technology » AI: Artificial intelligence is redefining corporate finance

Sven Denecken, SVP and Head of Product Management and Co-Innovation at SAP, discusses how AI is changing finance functions

Artificial intelligence (AI) and its potential to transform business processes across industries has become a central focus for organizations across the globe. Whether its conversations in the boardroom, sessions at an industry conference or a small-scale team meeting of accountants, companies today are buzzing about AI and the opportunity it poses to help usher in digital transformation.

While many still speculate that AI is more hype than reality, AI is already deeply ingrained in many organisations, driving automation that simplifies business processes.

This is especially true in corporate finance, with a recent study from Oxford Economics and SAP finding that 73% of finance executives agree that automation is improving finance efficiency at their company.

What is AI?

Defining artificial intelligence is perhaps the biggest initial hurdle that many finance stakeholders face in evaluating these technologies and weighing their potential impact in the enterprise. So, to start with the basics, AI can be broadly defined to include any simulation of human intelligence exhibited by machines.

One historical application that many organizations today are using is robotic process automation (RPA), which is rule-based robotic automation that can be extremely beneficial to companies in automating routine tasks. But beyond RPA, AI technology is a huge growth area that is branching into a multitude of areas when it comes to research, development and investment.

Other examples of AI include autonomous robotics, natural language processing or NLP (think of virtual assistants such as Apple’s Siri or Amazon’s Alexa), knowledge representation techniques (knowledge graphs) and more.

Machine learning is one specific subset of AI that has been gaining buzz in the industry today. Machine learning is learning based AI – it aims to teach computers how to accomplish tasks using data inputs, but without explicit rule-based programming that has historically been seen with RPA.

 Drive efficiency in finance with AI

RPA is increasingly common within finance departments today, to help automate routine finance responsibilities, including streamlining transactional tasks and reporting. However, advanced AI technologies, like machine learning, have the power to take this a step further, removing the need for rule-based machines by implementing learning technology.

For instance, invoicing is a finance responsibility that can often be a nightmare for accounts receivable or treasury clerks. Often a customer might pay the incorrect amount for an invoice, combine several invoices together into one check, or even forget to include their invoice reference number. Rectifying this can be a huge time suck in trying to sift through invoices or track down the customer.

This is an area where machine learning could support finance teams in real-time by applying its learning technology to ultimately make suggestions to accounting teams on matching payments to invoices. With this, finance teams can not only better ensure accuracy in aligning payments, they can massively cut down the time spent manually tracking down the relevant information and apply themselves to other needs within the business.

Let AI have a seat at the table

The potential for AI doesn’t just lie in efficiency. As these machines get smarter, there is enormous potential for AI to support CFOs and finance directors in informing strategy and driving action.

In the consumer technology space, NLP applications like Siri and Alexa have helped to “humanize” technology and information for individuals, answering questions about the weather and news headlines – even occasionally entertaining the user with a bad joke. The use of these voice-enabled devices isn’t limited to the consumer setting, and in the coming years we will likely see an increase of NLP technology being applied in the B2B enterprise setting.

For instance, CFOs and other finance executives often receive questions in boardroom meetings around revenue forecasts, and a myriad of other topics. Often, the executive needs to spend countless hours prepping and pulling these figures to anticipate what information might be needed, or alternatively, halt an in-progress meeting to pull up the latest numbers.

These digital assistant devices could be used in the enterprise setting to let the CFO easily ask questions of his or her data analytics system in real-time. This technology would not only enable uninterrupted meetings, but also allow the CFO and other company stakeholders to make informed decisions that drive action quickly and with confidence.

Smart technologies will change the talent landscape

AI offers exciting promise for innovation as companies look to stay-ahead in today’s fast-paced, globalised business landscape, but as its popularity continues to grow, conversations have begun about the possible negative implications for workers.

For finance teams, while AI can have a measurable impact on efficiency, it cannot replace the human element. Human review and monitoring is still required when technology like machine learning streamlines some manual tasks, especially in cases that may be too complex for the machine to rectify.

Additionally, there is an opportunity for finance executives to build their teams by hiring people who are familiar with advanced technologies and can help support, improve and innovate their use within the finance function, ensuring human workers are equipped to excel in their roles.

Eighty-four percent of global companies cite digital transformation as an important factor for survival in the next five years, but to-date, only 3% of organisations have completed a company-wide digital transformation, according to another recent survey by Oxford Economics and SAP.

With this, finance executives in particular, believe that investment in digital skills and technology will have the greatest impact on company revenue in the next two years.

By exploring how AI technology can be implemented, not only in streamlining processes, but also as a valuable resource in informing strategy and driving action in finance, CFOs and other finance stakeholders can ensure their workforce is best armed to drive success in the digital economy.