AI Enabled Frictionless Finance Function

Executive Summary

Top 5 Considerations for AI-Enabled Frictionless Finance Function

• CFO Role Evolution: Shift from traditional financial stewardship to leading innovation and growth initiatives, leveraging AI to drive organisational transformation.
• AI-Powered Process Automation: Implement AI to significantly reduce manual intervention in financial processes, enhancing efficiency and accuracy in financial operations.
• Emphasis on Real-Time Analytics: Transition towards continuous, real-time financial insights, enabling more timely and informed decision-making, moving away from periodic reporting.
• Strategic Data Management: Prioritise high-quality data integration, crucial for the success of AI implementation, ensuring accurate and effective automation of financial processes.
• Revolutionising Finance with SAP’s AI Tools: Utilise SAP’s AI-enhanced systems for a unified, efficient approach to financial reporting, analysis, and predictive insights, supporting a more dynamic and responsive finance function.

The Big Picture

For decades, the finance function and the CFO office have been central to the business. Their evolution, driven by regulatory changes, has reached a pivotal moment, mandating our finance team and CFO to unveil more compelling insights not only to the business but also to the public. These insights have become crucial to be available promptly whenever needed. Now is the time to prepare for a new era of financial transparency and impact.

Companies are increasingly looking to their CFOs to drive innovation and transformation throughout the organisation, prioritising user experience. This necessitates a long-awaited shift for CFOs—from being guardians of financial matters to becoming advocates for innovation and growth.

With traditional ways of working and outdated systems resulting in financial results being available only on a periodic basis after the period-end closing, it became evident that a change is necessary.

If we look at the finance function in any organisation, we will see how much it relies on people. A lot of human intervention throughout the accounting cycle starts from collecting information and data from different sources, processing these data, and generating reports using excel sheets. The moment an accountant or employee is needed to review, edit, or approve anything, the idea of a frictionless finance function becomes nearly impossible.

This might sound unreasonable considering the necessity of human intervention in many processes such as exceptions handling or contracts review but the idea of this thought leadership is to lay out a roadmap and provide some guidance on how, when, and where to apply AI to get closer to a frictionless finance function.

If a business considers using AI for transformation, it is crucial to understand that any technology enabled transformation especially now with AI mandates a business process transformation. AI then will come and enable the short-term partial and long-term full process automation.

Let’s start with how a frictionless finance function could look like. To fully automate the finance function and reduce or eliminate the human intervention, a business would need to aim for; Touchless Processes, no Exceptions at all, apply Continuous Accounting and get Real-time Reporting. While this may sound unreasonable, we need to perceive it as an evolutionary journey and keep these objectives in mind to achieve maximum automation at a reasonable cost to the business.

A question that might arise here is, does this mean that we won’t need accountants anymore? The answer is of course not. AI won’t replace the accountants; it is what accountants can achieve with AI. AI will change the nature of the job, will change the role of the accountants, and will require new skills indeed. Accountants will be required to optimise and transform their business processes rather than just performing it.

Touchless Processes

For a business to truly achieve a touchless process, we need to work on 4 important pillars for the change: Business Processes, Data, Technology, and People. If a business misses any of these pillars, the touchless process objective will still be far from reality. To maximise the benefits of AI adoption, it is crucial to target business processes with substantial potential for cost savings and increased profitability.

Having pinpointed the target business processes, a comprehensive analysis is essential. This examination delves into the current state of the processes, identifying operational nuances, bottlenecks, and variations across different segments of the business. This in-depth analysis allows for the simulation of automation impacts on tasks best suited for it. Process mining tools like SAP Signavio aid in assessing process health through monitoring, analysis, benchmarking, and improvement recommendations. Signavio offers profound process analysis capabilities across both SAP and non-SAP applications.

Integration of robust control measures is equally critical. Controls act as safeguards, ensuring the reliability and accuracy of automated processes. They guarantee that the system functions as intended, maintains data accuracy, and adheres to compliance standards. These controls are meticulously designed to mitigate risks, prevent errors, and uphold the integrity of business processes.

Once these processes are identified, a detailed examination of the underlying data becomes paramount. The success of automation, especially using AI, hinges on the quality and reliability of the data it operates on. Over the past two decades, companies, driven by mergers and acquisitions, have accumulated diverse data sources. These include disconnected legacy systems, inconsistent business processes, unstructured data, and even physical records on paper.

It may not be possible to correct the data at the source, especially if the data is fed through external data sources or multiple disparate systems. In such cases, companies might start their transformation journey supported by SAP Central Finance as a stepping stone for automation and standardisation.

SAP strategy is to have a clean core (Read Mark Chalfen article about the Clean Core ), with a wide range of applications connected through its Business Technology Platform (BTP) enabling the integration of SAP and non-SAP systems with real-time analytics.

With the adoption of AI models, the AI engines can be trained to extract data with higher accuracy and transform it precisely based on the target system. This is different from standard APIs where developers need to pre-define mapping tables. The AI solution will predict the mapping rule based on the provided data, and this prediction will be supported by an acceptance confidence level creating a self-learning loop. This will make the transformed business process more dynamic and not impacted by changes in data.

A use case for an AI engine is clear in cash application. The classic ways of matching invoices to collection often requires a lot of manual intervention to validate and process exceptions. But, with AI embedded in the cash application, SAP can match collections with invoices based on different factors even if the data is incomplete. The AI layer will gather all evidences and predict a match that was previously not possible.

Business transformation programmes have long been guided by technology. The utilisation of diverse tools and systems for various processes or the implementation or custom solutions has facilitated task automation within the business. However, the integration of these technologies with AI amplifies their impact significantly. (Read Jonathan R. & Rohit Chandrasekhar article about Fit to Standard or Fit to Vision )

No Exceptions

Exception in the context of a business process refers to situations that deviate from the standard or expected flow of the process. These are instances where the process encounters unexpected circumstances that require special handling or human intervention. In Accounting this can happen due to various reasons, such as errors in data, missing information, wrong GL account or missing account assignment or a failure in a derivation rule. Exceptions can also happen outside the finance function through incorrect input from other functions or other front office systems’ issues.

In a perfect scenario, exceptions must be prevented, but realistically there is always a chance of encountering an exception, hence exceptions need to be properly managed. Here comes the role of AI, instead of relying on human intervention a frictionless finance function will rely on AI for exceptions handling.

Without AI, exception handling will be a responsibility and a regular activity for the finance team to deal with. In many organisations this requires a full-time job to deal with it every month.

You might ask, if we already have a full-time accountant managing these exceptions, why do we need to adopt AI for exceptions handling? It is proven that machines and computers are much better at preventing, detecting, and handling exceptions as they can manage a large number of exceptions more efficiently, deal with exceptions in real-time, pay better attention to details, and easily adapt to continuous changes in data. This means the team will focus on preventing these exceptions from happening rather than solving the exceptions and explaining the variances.

During a business transformation, efforts should be made to minimise and prevent exceptions as much as possible through data flow automation and by avoiding manual input.

Finally, when it comes to automation the business needs to factor the cost of automation and find the sweet spot between the benefits of preventing these exceptions and the cost of resolving them. This requires a deep analysis of the exceptions, understanding the real causes and selecting the right approach to handle and resolve them.

Continuous Accounting

Looking at a traditional month end closing cycle, many organisations close their books on working-day+5 with the final numbers ready for reporting to stakeholders in WD+10. The longer the closing and reporting cycle, the lower the value of the information reported. Many organisations use spreadsheets to monitor closing activities, wherein teams in various locations frequently collaborate on the same file or exchange content through email. This practice can result in conflicts, duplication, and errors. Senior finance leaders face challenges in promptly tracking the status of activities or identifying issues unless these concerns are escalated to them, often with a time lag.

Continuous accounting aims to streamline and accelerate traditional month-end and year-end closing procedures. It is an approach to distribute and automate accounting processes throughout the entire financial period rather than concentrating them at the end of the month through real-time processing of financial transactions and activities, so the latest information required for decision making is available when needed.

Accountants usually spend most of the month end closing time posting adjustment entries and sorting the accounting variances rather than focusing on financial analysis. The larger the number of manual activities needed at the end of the month is an indication of a clear underlying inefficiencies in the business processes. Continuous accounting doesn’t necessarily mean a shorter closing timeline, it ensures that information is available when needed, and the numbers can be clearly explained and understood by the stakeholders. Accountants also can experience an improved work-life balance even during the period-end closing, without experiencing stress.

The initial phase in introducing continuous accounting involves evaluating the activities, efforts, and resources currently required during the month-end closing process. The second phase is process improvement with the first time right approach. Then choose the right tool to manage the month end closing activities such as SAP Advanced Financial Close Cloud solution with ML capabilities for process automation or utilise SAP predictive extension ledgers for predictive accounting.

Finally SAP has introduced Joule as a personal assistant to all SAP end users. With Joule you will be able to communicate with it using native languages and chat. You can ask it questions like: How many open sales orders do we have? How many overdue invoices this month?” In response, Joule will intelligently provide you with accurate technical and business process related information. Read this Article written by Jonathan R. & Rohit Chandrasekhar about Joule & AI with S/4HANA )

Real-time Reporting

The importance of real-time reporting arises from the actions that depend on this information. It allows the finance team to access and analyse financial data as it happens, without delays or lags. For a CFO, having real-time reporting is crucial because it allows for prompt decision-making. In a rapidly changing business environment, the ability to access up-to-date financial information is invaluable.

Timely reporting enables the business to promptly generate reports, facilitating a comparison between actual results and forecasts. This empowers the business to recognize deviations and implement appropriate actions in a timely manner.

While our current reporting capabilities enable some real-time reporting, a notable gap exists in many companies where each function concentrates solely on its individual priorities and activities, often neglecting the broader perspective. Consequently, functional reporting falls short in terms of linking operational drivers to financial metrics. Insufficient accountability, limited collaboration, and conflicting priorities collectively squander valuable insights.

Having a single source of truth is paramount in addressing the identified gaps in reporting capabilities. A unified and comprehensive source of data ensures a holistic view of the business. The importance of a single source of truth lies in:

• Providing consistency and accuracy in data, mitigating discrepancies that may arise when disparate functions operate independently.
• Providing a unified view, helping each function to move beyond individual priorities and activities, fostering a holistic perspective across the organisation.
• Facilitating the seamless connection between operational drivers and financial metrics, overcoming the shortcomings of fragmented functional reporting
• Establishing clear accountability as it becomes the authoritative reference, reducing the likelihood of conflicting or inconsistent data interpretations.
• Relying on a consolidated and accurate dataset, enabling more informed and efficient decision-making processes.
• Optimising resources utilisation, avoiding the wastage of time and effort on rectifying inconsistencies.

SAP provides several cloud-based, AI-enabled reporting systems designed for collaborative use, offering seamless data connectivity between finance and non-finance systems. SAP Analytics Cloud SAC is a comprehensive solution that integrates business intelligence, augmented analytics, and planning capabilities. It facilitates collaboration by allowing users to create, share, and analyse reports and dashboards collaboratively. Additionally, SAC ensures seamless connectivity to various data sources, fostering integration between SAP and non-SAP systems. Its Predictive Analytics Features enhance data analysis, providing real-time insights and predictions that contribute to more informed decision-making across the organisation.

Highlights

The objective of the new Frictionless Finance Function is to transition from being a cost centre solely focused on delivering accurate financial results to the business, to becoming a strategic partner that actively drives value, facilitates informed decision-making, and champions financial innovation across the organisation.

Now, where to start? While some organisations are undergoing a complete business transformation, others might be ahead of the game and looking to improve certain processes using the right tools to achieve the maximum ROI with minimum risk or disruption to the business operations.

SAP is currently undergoing a transformation towards becoming an open platform. This shift is aimed at enhancing flexibility and agility in implementing process changes and integrating services. The envisioned state is an ERP with a clean core like SAP S/4HANA and cloud solutions for other processes (Read Rohit Chandrasekhar article about SAP’s Vision for the Future with RISE AND GROW . This architectural shift supports a seamless user experience through the Fiori layer, cross-product analytics via SAP Analytics Cloud and data warehouse, and adherence to open integration standards through SAP BTP. Data generated across various systems can now be transmitted in real-time, allowing multiple systems to utilise it.

The fundamental principle of the SAP AI strategy is to enrich its products and application with embedded AI engines to empower its customer base. Additionally, customization options for developing custom AI services are exposed to the end users via the SAP Business Technology Platform (BTP) enabling businesses to leverage trustworthy AI at scale.

Now is the right time to envision and invest in a future enabled by AI where Finance professionals will operate in a manner similar to autopilot in a plane. Just as the pilot holds the Yoke while the plane operates autonomously, finance professionals will stay engaged in steering and overseeing the financial processes with a heightened focus on strategic decision-making.

** Do you think your business is ready for AI? Let's have a conversation about how we can help you utilize AI to drive efficiency, and increase productivity and profitability.