Over the past decade, the digitisation of finance has helped CFOs and finance leaders adapt to challenging market conditions more easily. By liberating finance decision-making from the confines of spreadsheets and manual processes, organisations have unlocked huge operational efficiencies while improving the accuracy of decision-making within finance functions.
The proliferation of AI within financial business processes promises an even greater wave of innovation for finance leaders. AI is a transformative technology, allowing organisations to unlock the power of their financial data and improve decision-making while also easing regulatory compliance and providing accurate predictive and analytical insights.
The International Monetary Fund highlights AI applications in finance that range from the use of machine learning algorithms to improve forecasting and credit risk scoring, to natural language processing powering chatbots that support customer service and report generation processes. For CFOs, AI’s ability to improve anomaly detection provides an essential layer that can help financial institutions limit insider trading and enhance fraud detection.
McKinsey data suggest the potential annual value of AI and analytics within the global banking sector could reach $1-trillion, with marketing and sales, risk, and HR as the highest-value business functions for AI support. A separate report by IDC found widespread interest in AI among global finance leaders, who recognise its potential to dramatically increase the performance of a broad range of finance processes.
Embedded AI powers optimisation, efficiency
While consumer-friendly AI applications such as ChatGPT have achieved mainstream success and secured immense public interest over the past two years, the true value of AI for businesses lies in embedded AI.
Embedded AI involves purpose-built algorithms running within standard business processes such as invoicing and reporting. For finance teams, embedded AI delivers enhanced analytical and data processing capabilities as well as process automation to improve the functioning of key financial business processes.
One example is the use of optical character recognition (OCR) technology to streamline invoice-to-cash processes within SAP S/4HANA. The OCR technology extracts key information from payments notes, with AI models matching that with open receivables. The information is then loaded into S/4HANA and routes matching exceptions to accounting teams for clearing. This frees finance professionals to focus on more high-value strategic tasks that can drive the business forward.
Another example is the use of AI in reconciliation. Consulting firm Accenture leveraged SAP Cash Application to match invoices faster and with fewer errors. The efficiency gains allowed Accenture to achieve an automatic clearing hit rate of 54% and unlock time savings that allowed the business to redirect resources to higher-value activities.
Improved business risk and compliance management
With finance being one of the most heavily-regulated industries, CFOs have to keep statutory compliance top-of-mind. Embedded AI can play a vital strategic role by powering improved governance, risk and compliance processes that enable organisations to identify and respond to emerging risks.
One example is the application of AI and behavioural analytics to large volumes of transactional data. By analysing historic and real-time transactions, finance teams can discover errors or even fraudulent transactions that may expose the business to financial liability, and take corrective measures to protect the organisation.
Similarly, the use of AI-powered invoice payment forecasting can help finance teams predict when payments from at-risk customers can be expected, thereby allowing for more optimised payment strategies and improved cash flow management.
Reporting accuracy, paramount within finance business processes, can further be enhanced through AI-powered automation. By automating the posting of new journal entries in record-to-report processes, finance teams can avoid manual errors and improve reporting accuracy and compliance.
In the midst of an uncertain global economic environment and faced with an increasingly complex regulatory environment, CFOs and their finance teams will need to maintain the highest levels of efficiency and accuracy throughout all financial activities. With the support of embedded AI integrated to core business applications, CFOs can significantly reduce inaccuracies, improve decision-making, and effectively steer the organisation through challenging conditions.