AI-powered chatbots provide instant customer support, answer queries, and assist with account-related tasks. Natural Language Processing (NLP) enables chatbots to understand and respond to customer inquiries. Application in Oracle’s Enterprise Performance Management (EPM) platform, providing CIOs and CFOs by Improving customer experience, reducing response times, and handling routine tasks, freeing up human agents for more complex issues. 

Introduction 

The introduction of artificial intelligence has significantly enhanced the financial sector’s precision, velocity, and decision-making procedures. Artificial intelligence (AI) is a critical component of Oracle’s Enterprise Performance Management (EPM) platform, providing CIOs and CFOs with significant benefits. Predictive analysis, financial operations, and strategic planning are all enhanced (Contributor, 2018). AI-powered Oracle Enterprise Performance Management (EPM) provides a variety of applications designed to satisfy the financial requirements of businesses. This article examines a number of the ways in which Oracle EPM and AI collaborate, as well as the advantages that chief information officers and chief financial officers can anticipate. Incorporating AI algorithms into Oracle Enterprise Performance Management (EPM) permits the analysis of vast quantities of data in order to produce precise financial forecasts. In order to make more informed strategic decisions, machine learning models can assist chief financial officers (CFOs) in comprehending financial risks, consumer behavior, and market trends. Masel, Zwerling, and Sorensen (2022) posit that this competency facilitates the forecasting of future development, allocation of budgets, and management of resources. 

The use of Artificial intelligence in finance 

Financial specialists can optimize their performance by leveraging sophisticated analytics. With Oracle Enterprise Performance Management (EPM), you can analyze and consolidate data from multiple sources and systems onto a dependable platform. Additionally, it monitors and regulates the data. Financial professionals can utilize the scenario modeling and planning capabilities of Oracle Enterprise Performance Management to generate and compare a multitude of predictions and scenarios utilizing AI and ML. Their perspectives and recommendations will be received in advance should they adopt this approach. By employing sophisticated methodologies, Oracle EPM enables financial professionals to assess and improve risk-adjusted performance measurement, portfolio management, and capital allocation (Frankenfield, 2019). Oracle EPM enables financial specialists to identify and mitigate risks including credit risk, operational risk, market volatility, and compliance risk by utilizing AI and ML to detect trends and outliers. 

The demand and sales projections created possible by Oracle EPM’s AI and ML capabilities can be relied upon by the finance team. This type of forecasting considers numerous variables, including marketing, consumer behavior, and seasonality (IBM, 2023). Chatbots powered by AI can help with account-related activities, answer questions, and give quick customer service. With the use of Natural Language Processing (NLP), chatbots can comprehend and answer to consumer questions. For chief financial officers and information officers, there is an application in Oracle’s EPM platform that helps with customer service, speeding up responses, and automating mundane jobs so that human agents may focus on more complicated problems. Mer and Virdi (2023) posit that financial professionals can derive advantages from utilizing Oracle Enterprise Performance Monitoring (EPM) software, a specialized tool designed to facilitate performance monitoring and budgeting. The system’s incorporated AI and ML functionalities enable finance professionals to enhance the alignment between financial and operational objectives, monitor progress, identify discrepancies, and capitalize on favorable circumstances (Team, 2022). 

Oracle EPM provides AI-powered forecasts and analytics to the finance and controllership departments.

Experts in finance can utilize Oracle EPM to: An enhanced and more cohesive cloud solution that includes advanced enterprise analytics and modular financial management software. User experience and enterprise-wide administration were facilitated. Decisions based on data are more precise and timelier (Insider Intelligence, 2022). Service delivery that is more effective and efficient, resulting in increased consumer satisfaction and loyalty. In times of volatility, Oracle EPM assists CIOs and CFOs in administering agile organizations. In order to ascertain public sentiment towards the market, artificial intelligence analyzes news articles, social media updates, and other forms of textual information. This data facilitates the prediction of market movements and enables informed investment decisions. The sentiment analysis tool is a component of Oracle’s Enterprise Performance Management (EPM) platform and is accessible to chief financial officers and chief information officers. It facilitates traders and investors in comprehending public sentiment and forecasting market fluctuations, hence assisting in risk mitigation and decision-making (Oracle, 2021). 

AI automates financial reporting duties in Oracle EPM, thereby conserving time for CFOs and finance teams.

The utilization of NLP and machine learning enables the platform to generate individualized reports that contain perceptive evaluations and pertinent suggestions. Strategic planning and decision-making are streamlined as a result (McKinsey, 2020). Automated reporting and insights generate and disseminate financial reports and analyses by utilizing data visualization and AI. With AI, financial professionals can automate laborious and prone to error data collection, verification, combination, and organization. Financial specialists can utilize AI to identify patterns, trends, anomalies, and projections within massive data sets. Financial experts have the ability to effectively and succinctly convey these insights through the use of data visualization technology.  

Using artificial intelligence and data visualization, Oracle EPM automates reporting and provides insights into financial operations and controllership. Oracle EPM enables financial and information officers to optimize cloud-based solutions and business intelligence tools, streamline financial closing and reporting, enhance decision-making through the integration of embedded intelligence, simplify account reconciliation and compliance, and integrate planning and budgeting (Gelinas, Dull, & Wheeler, 2018). Oracle EPM’s predictive modeling is enhanced by AI, enabling CFOs to simulate financial scenarios. CIOs and CFOs have the ability to forecast market fluctuations, assess strategic approaches, and formulate data-centric decisions regarding the expansion of the organization by leveraging AI-powered predictive analytics and historical data. 

Predictive financial modeling utilizes past financial data to forecast forthcoming financial outcomes.

By utilizing machine learning and data mining, AI is capable of analyzing historical and current data, identifying patterns and trends, and generating intelligent recommendations to enhance predictive financial modeling. The optimal financial modeling solution for controllership and finance operations is Oracle EPM, which is propelled by AI (Oracle, 2021). Oracle EPM enables CIOs and CFOs to generate and evaluate a variety of estimates and scenarios. Machine learning and AI generate forecasts and recommendations. Oracle EPM assists CIOs and CFOs in forecasting and optimizing capital allocation, portfolio management, and risk-adjusted performance measurement. Oracle EPM facilitates enhanced decision-making for CIOs and CFOs through the utilization of data-driven insights and scenario modeling (Parmar, 2024). 

The incorporation of AI into Oracle EPM optimizes operational procedures by diminishing reliance on manual labor and errors.

This increase in efficiency improves overall organizational productivity, streamlines workflows, and expedites financial closure cycles, which are all advantageous for both CIOs and CFOs. Improving the operational efficacy of finance results in a streamlined, expedited, and cost-effective financial function. To achieve this objective, AI can automate manual processes, enhance workflows, and reduce errors and other hazards (Team, 2022). Utilizing AI-powered software, Oracle EPM increases the effectiveness of finance and controllership.  

Using AI and machine learning, data collection, validation, consolidation, and formatting can be automated and streamlined.

AI and ML can be utilized to automate account reconciliation and ensure rule compliance by identifying discrepancies and anomalous activities. Maximize your potential with an all-in-one cloud solution that combines adaptable accounting software with robust BI capabilities. Embedded intelligence can enhance the process of decision-making through the utilization of advanced analytics, AI, and ML (Maisel, Zwerling, and Sorensen, 2022). 

The AI functionalities of Oracle EPM provide CFOs with comprehensive decision support by delivering recommendations and insights that are supported by data.

This facilitates capital allocation, strategic investment decision-making, and cost optimization, thereby ensuring that financial strategies are in line with overarching business goals. AI-Driven Decision Support assists financial professionals in making more informed choices by generating insights, forecasts, and ideas based on data. Financial professionals can benefit from AI in the following ways: Using Oracle EPM’s scenario modeling and planning capabilities, financial professionals can construct and compare predictions and scenarios with the assistance of AI and machine learning (Oracle, 2021). 

Oracle EPM enhances the risk-adjusted performance evaluation, portfolio management, and capital allocation of finance professionals (Tarver, 2019).

Oracle EPM identifies trends and anomalies through the use of machine learning and artificial intelligence to assist financial specialists in managing market volatility, credit risk, operational risk, and compliance risk. Customers of the Oracle EPM for finance and controllership are able to utilize AI-Driven Decision Support. Using advanced analytics, AI, and machine learning, AI has the ability to detect unusual patterns and anomalies in financial transactions, which may indicate fraudulent activity. Machine learning models have the ability to modify and adjust themselves in order to counteract newly emerging fraudulent activities. This program, developed on Oracle’s EPM platform, assists Chief Information Officers (CIOs) and Chief Financial Officers (CFOs) in protecting financial institutions from fraudulent conduct. It achieves this through real-time transaction monitoring, anomaly detection, and behavioral analysis. (Taher et al., 2023). 

Conclusion 

Fundamentally, the incorporation of AI into Oracle EPM provides a comprehensive suite of tools that augment operational efficiency, risk management, financial analysis, and strategic planning, thereby empowering CIOs and CFOs. These executives can confidently navigate complex financial environments by utilizing AI-driven insights, thereby ensuring that their organizations maintain agility, competitiveness, and preparedness for the future. 

References 

Contributor, W. (2018). Workday BrandVoice: Global Finance Leader Study: Unlock the Power of Advanced Analytics by Combining Finance and Non-Finance Data. [online] Forbes. Available at: https://www.forbes.com/sites/workday/2018/08/30/global-finance-leader-study-unlock-the-power-of-advanced-analytics-by-combining-finance-and-non-finance-data/ [Accessed 15 Jan. 2024]. 

Frankenfield, J. (2019). Reading Into Predictive Modeling. [online] Investopedia. Available at: https://www.investopedia.com/terms/p/predictive-modeling.asp. 

Gelinas, U. J., Dull, R. B., & Wheeler, P. (2018). Accounting information systems. Cengage AU. 

IBM (2023). What is artificial intelligence in finance | IBM. [online] www.ibm.com. Available at: https://www.ibm.com/topics/artificial-intelligence-finance. 

Insider Intelligence (2022). Artificial Intelligence in Financial Services: Applications and benefits of AI in finance. [online] Insider Intelligence. Available at: https://www.insiderintelligence.com/insights/ai-in-finance/. 

Maisel, L.S., Zwerling, R.J. and Sorensen, J.H., 2022. AI-enabled Analytics for Business: A Roadmap for Becoming an Analytics Powerhouse. John Wiley & Sons. 

McKinsey (2020). Using advanced analytics can help companies create more accurate forecasts | McKinsey. [online] www.mckinsey.com. Available at: https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/predictive-sales-forecasting-is-your-finance-function-up-to-code. 

Mer, A., & Virdi, A. S. (2023). Navigating the paradigm shift in HRM practices through the lens of artificial intelligence: A post-pandemic perspective. The Adoption and Effect of Artificial Intelligence on Human Resources Management, Part A, 123-154. 

Oracle (2021). Enterprise Performance Management | Oracle. [online] Oracle.com. Available at: https://www.oracle.com/performance-management/. 

Parmar, R. (2024). Council Post: Deep Impact: The Emergence Of AI-Driven Processes In Finance. [online] Forbes. Available at: https://www.forbes.com/sites/forbesfinancecouncil/2024/01/04/deep-impact-the-emergence-of-ai-driven-processes-in-finance/ [Accessed 14 Jan. 2024]. 

Taher, K. A., Reza, S. S., & Majumder, B. G. M. M. K. (2023). Board of Examiners. 

Tarver, E. (2019). Financial Forecasting and Financial Modeling: Knowing the Difference. [online] Investopedia. Available at: https://www.investopedia.com/ask/answers/difference-between-financial-forecasting-and-financial-modeling/. 

Team, E.I.D. (2022). About EPM System Products. [online] Oracle Help Center. Available at: https://docs.oracle.com/en/applications/enterprise-performance-management/11.2/hitis/launch.html [Accessed 15 Jan. 2024].