In the upcoming years, the finance department is expected to go through significant changes just like other job roles and departments. These changes will be caused by advancements in automation and the application of artificial intelligence (AI) technologies.
The finance industry is experiencing a significant transformation driven by the rapid progress in automation and artificial intelligence (AI). Today, finance professionals must manage a complex array of financial data, adhere to stringent regulations, and maintain consistent client interactions. The integration of automation and AI is set to revolutionize these functions, offering both unprecedented opportunities and challenges.
Historically, finance practices have relied on meticulous data entry, routine bookkeeping, and detailed financial analysis. These essential processes are often time-consuming and susceptible to human error. The advent of automation and AI presents a unique opportunity to overhaul these conventional methods, making them more efficient and accurate.
Recognizing the immense potential of these technologies, the finance profession is at acritical juncture. Automation and AI are not just enhancing efficiency; they are reshaping the very foundation of how finance is practiced, heralding a new era of innovation and precision.
AI and Automation are huge topic on their own, in this blog, we focus on the important factors that business and finance leaders should keep in mind when exploring AI and automation.
Difference Between Artificial Intelligence (AI) and Automation
Automation repeatedly performs the same tasks without needing manual effort or changes. Its main goal is to increase efficiency, reduce time, minimize human error, and cut costs by handling repetitive tasks.
AI, on the other hand, involves technology and algorithms that learn and improve over time. It can adapt to new information, perform tasks more efficiently, analyze data, solve problems, make complex decisions, and create forecasts—all without human intervention.
Banking and investment management are areas in the financial sector where AI and automation are actively driving efficiency and innovation.
AI Automation banking benefits
Machine Learning
Machine learning, a subset of AI, emphasizes the development of algorithms and models that enable machines to learn from data, predict behaviours and trends.
Predictive Analytics
Technology is used in predictive analytics to forecast specific events based on historical data and patterns within a given time frame.
Generative AI
While it is less crucial to a finance function and is currently more prevalent in fields such as marketing, generative AI is used to learn patterns and structures to create something similar or new. It is currently being utilized more for generating items like content, images, art, and product designs.
Finance Function
The finance function often involves numerous routine and repetitive tasks that can be effectively automated. Many of these automation capabilities are already available in online accounting software, encompassing tasks such as invoice generation, receivables tracking, payment logging, automated bank transaction reconciliation, and data capture from receipts and invoices.
Numerous finance functions still rely on manual task execution and processes. Introducing automation to handle these tasks and transform these processes can markedly improve efficiency by reducing processing times and costs, as well as potentially enhancing data accuracy. By relieving your finance team from these routine tasks, your business can not only save time but also leverage their expertise in other critical areas.
AI can enhance efficiency by offering a thorough analysis of a company's financial data. This analysis can be utilized to optimize working capital management, forecast customer debts, and improve the order-to-cash cycle. AI can also pinpoint business opportunities by aiding in forecasting, strategic planning, and modelling customer behaviour.
The Role of CFO and Finance Leaders
The responsibilities of finance leaders in contemporary companies are continually evolving to encompass providing future insights, enhancing risk management, improving efficiencies, and leveraging technology.
The modern CFO is tasked with leveraging financial data to support growth, reporting to key stakeholders, identifying risks, forecasting future trends, and spearheading digital transformation within the finance function as part of the overarching business strategy.
Few Facts
According to a survey by McKinsey, adoption of AI has doubled since 2017, though the proportion of organizations using AI has plateaued between 50 and 60 percent for the past few years.
According to Gartner, 80% of CFOs surveyed in 2022 expected to spend more in AI in the coming two years. Around two thirds of finance leaders think their function will reach an autonomous state within six years.
By 2025, 70% of organizations will use data-lineage-enabling technologies such as graph analytics, machine learning (ML), artificial intelligence (AI) and blockchain as critical components of their semantic modelling.
By 2028, 50% of organizations will have replaced time-consuming bottom-up forecasting approaches with AI, resulting in autonomous operational, demand and other types of planning.
Implementing AI and Automation
The rise of AI has brought attention to the current state of financial software and the evolving role of CFOs. CFOs now hold greater responsibility for technology decisions, making it crucial for them to prioritize the adoption and utilization of AI to ensure future success. From the perspective of CFOs, implementing AI and automation is vital for effectively managing financial operations, fostering growth, and maximizing organizational value.
Financial planning and analysis
Financial Planning and Analysis (FP&A) plays a pivotal role for CFOs and their teams, as they oversee budgeting, forecasting, and strategic decision-making. While traditional planning focused on historical data to inform future strategies, the advancement of AI enables CFOs to provide more profound insights and predictive analytics related to market trends, customer behaviour, and financial forecasts.
Forecasting Growth
As part of their role, CFOs often assess the financial feasibility of potential growth opportunities. AI has the capability to analyze extensive data sets to identify patterns, offer enhanced data visualization, improve forecasting accuracy, generate detailed reports, and facilitate AI-driven scenario planning.
Productivity and Efficiency
CFOs are tasked with the responsibility of aiding the business in boosting productivity and efficiency. Automation serves as a powerful tool to accomplish this objective by taking on routine tasks, minimizing errors, and modernizing or streamlining outdated processes. Embracing technology to automate repetitive and time-consuming tasks paves the way for swifter completion of deliverables, leading to increased operational efficiency and effectiveness.
Risk Management & Fraud Detection
AI serves as an asset in scrutinizing internal financial control points and pinpointing fraudulent activities within a company. By leveraging AI and machine learning, organizations can swiftly detect irregularities and patterns indicative of fraud within vast datasets.
Furthermore, AI empowers companies to effectively navigate risks by bolstering risk identification, refining assessment processes, and enhancing predictive accuracy. Through the analysis of intricate datasets and the recognition of nuanced patterns, AI expands the scope of risk management beyond what traditional human analysis may uncover.
Decision Making
With AI, establishing connections between disparate data points is a swift and straight forward process. Through this capability, finance gains access to trends within the data, which can then be utilized to inform decision-making in strategy and planning. These insights garnered from AI-powered analyses prove to be instrumental in guiding finance professionals towards informed and impactful business decisions.
Begin Your AI and Automation Journey
For an AI digital transformation to thrive within any business, it is crucial for the entire organization to have a well-defined AI strategy that is aligned seamlessly across all departments.
To kickstart your automation and AI journey, begin by identifying recurring tasks within departments and mapping out key processes to gain a deeper insight into your organization's automation and AI requirements. Subsequently, explore the available tools to streamline or automate these tasks and processes effectively.
Transitioning from operational tasks, the next phase involves exploring strategic avenues where AI can offer support. This could encompass activities such as financial planning and reporting, scenario planning, risk management, or fraud detection.
Final Thoughts
Finance Automation Should be the Next Step for Companies. The rapid advancement of AI and automation is reshaping the operations of finance functions. Finance teams are crucial players in embracing new technologies and leveraging AI and automation both presently and in the coming years.
AI has the potential to deliver significant advantages to a business within the finance sector, such as automating and accelerating processes, enhancing productivity, minimizing human error, reducing risk, and facilitating simpler and more precise financial forecasting and modelling.
Finance professionals and teams must adapt and acquire new skills to transition their focus from mundane tasks to more strategic work. Incorporating artificial intelligence enables CFOs and FDs to cultivate strategic insights. Through the utilization of real-time insights and predictive analytics, finance professionals and their teams will have a vital role in fostering business growth. To learn more about how finance process automation can benefit your business, book a consultation with one of our experts.