Leveraging AI and Digitalization for Financial Planning and Analysis (FP&A) (2024)

AI-Driven Financial Planning and Analysis

Financial Planning and Analysis (FP&A) of capital expenditure incorporates business case preparation, portfolio budgeting, project forecasting, and reporting. Unfortunately, within many organizations, this capital expenditure management process relies on disconnected processes and disparate data sources. This often requires manual collation of data and relies heavily on spreadsheet administration.

A systemized approach to should address 5 key aspects:

  1. Single source of data for project planning, budgeting, and forecasting.
  2. Flexible digital forms that can capture just the right amount of supporting information.
  3. Seamless collaboration and approval workflow.
  4. Effective initiative evaluation and scoring.
  5. Artificial Intelligence to assist with project definition, selection and control.

Digital transformation and application of artificial intelligence in the financial planning and analysis of capital projects provides many benefits.

Strategic Alignment

Effective capital budgeting does not simply repeat prior period expenditure. Whilst this may have been a viable approach in the past, the current operating environment is more complex.

Rapid technological advances, global competition, and environmental, social, and governance (ESG) expectations are impacting all organizations. This requires a more sophisticated approach to capital allocation and reinvestment.

Adopting zero-based budgeting principles, the critical driver of capital projects must be strategic alignment. Every business unit should define its objectives in line with overall enterprise strategy. These strategic objectives that should then drive the investment priorities for that area.

Effective strategic alignment of capital budgets is most effectively achieved when defined and monitored in a single integrated environment. This will provide all staff and managers with a common yardstick for assessing project importance.

Productivity

The primary motivation for digital transformation of the capex process is to increase productivity of all participants. Disconnected and spreadsheet-based capex management processes are inefficient and inherently risky.

Administrators spend time to updating and distributing business case and forecasting templates. End-users require significant support to complete capital expenditure request (CER) and authorization for expenditure (AFE) forms accurately and completely.

Administrators then need to collect, validate and collate these documents. It takes time and effort to standardise, aggregate and analyse data to produce meaningful reports.

An integrated, digitally transformed process will require only a single point-of-entry of project financial data. All participants can directly use this information to plan, budget, and forecast project financial outcomes. This allows the financial planning and analysis team to focus on providing effective insights, rather than managing spreadsheets.

User-Experience

In addition to the Financial planning and analysis team, an integrated digital capital management system benefits project managers and executive sponsors.

Capital investments range from simple equipment replacements to major strategic infrastructure commitments expecting to generate decades of benefits. Consequently, evaluating the value and priority of investments requires collecting varying amounts of data.

The investment reason for a project will impact its evaluation. For example, we typically score and rank sustenance initiatives based on risk assessments. For growth initiatives, the net present value of future revenues may be more relevant. Environmental projects may require a direct assessment of greenhouse gas emissions.

The nature of the asset will also impact the information required. The information needed to assess building projects is not the same as that needed for intangible software systems.

Static document templates can either overwhelm users or provide insufficient data-entry fields. Unlike a spreadsheet where all fields are visible, a dynamic web form only shows the necessary data fields. This makes it much easier for a user to provide the required inputs.

Online templates react to user input and selections. Real-time validation and help texts ensure that submissions are complete and consistent. Automated calculations and global assumptions make it easier for users to prepare high-quality submissions.

Online business case template can also collect just the right amount of data at the right time to support the nature of the investment. Users can provide more detailed and relevant inputs as an initiative passes through its various stage gates.

The executive approval experience also benefits from consistent access, metrics, and presentation. With an integrated system, capex approvers are familiar with and have confidence in the information presented. They can easily drill-down to supporting details and documents as required from the financial planning and analysis team.

With a fully digital and integrated capital budgeting system, approvers benefit at every stage. Ideas, investment proposals, business cases, and expenditure requests are all approved in the same system in the same way.

Collaboration and Compliance

A key part of the capital planning process is to collaborate with technical experts and gain endorsem*nts as required. Senior executives must then approve capital expenditure in accordance with delegation of authority policies.

Document-based processes are typically reliant on manual approval routing, with a heavy reliance on email. By contrast, a digitally transformed capital financial planning and analysis solution facilitates seamless workflow in accordance with standardised business rules.

A single source of truth enables both parallel and sequential approval. Automated workflow will provide a detailed audit trail of changes, approval actions, and comments.

The Importance of Time

Project expenditure typically occurs over a number of months or years. Future returns are dependent on project completion. However, resource availability, supply constraints and technical complexities frequently result in shifting project schedules.

Time is money: the timing of future cashflows is thus an important factor in the evaluation of projects when making investment decisions.

An integrated capital budgeting solution will be able to immediately reflect the impact of changes in project schedules. This will impact the evaluation of the net present value of both costs and future benefits.

The Impact of Rates

Disparate data sources inevitably lead to discrepancies in assumptions. This can invalidate metrics that managers rely upon to prioritize initiatives.

4 standard key assumptions include:

  1. The discount rate applied to future cashflows.
  2. Foreign currency translation rates.
  3. Asset useful lives.
  4. Tax rates.

A single data store will ensure that these rate assumptions are common. A consistent mechanism for evaluating initiatives will ensure calculations are consistent, and that comparisons are reliable.

Business Partner Engagement

Most significant capital projects rely on business partners to deliver new solutions. The selection of business partner can be as crucial to successful capital investment as the choice of project. With disconnected capex management systems, it is difficult to monitor and optimize partner engagement.

An integrated project planning system will identify partner relationships. Monitoring these key relationships can help optimize terms of trade and mitigate supplier compliance and performance risks.

Resource Levelling

In addition to funding constraints, a practical constraint to most organizations’ capital project portfolio selection is internal capacity. Key business representatives must oversee and pay attention to capital projects while also fulfilling their business-as-usual activities and responsibilities. With disconnected project planning processes, there is risk that key individuals become over-loaded leading to project failure.

In a connected system, you can identify key-person dependencies early on and consider them when optimizing project portfolios.

Objectivity and Consistency

Passionate representations often heavily influence capital expenditure management decisions. The less structured and formalized the planning process, the greater the risk that persuasion will override data-driven decisions.

Standardizing project definition, scoring, and ranking can greatly improve the objectivity and transparency of decision-making. This will ultimately lead to improvement in the consistency and quality of decisions.

Cashflow vs Profit

Financial planning and analysis teams must evaluate both the economic and an accounting views of capital expenditure effectiveness.

The economic view relies on evaluating future cashflows. The accounting view looks at the accounting and financial reporting impact of capital investments. Whilst the economic view provides the true justification for capital expenditure, the accounting view can significantly impact stakeholders.

Key stakeholders include shareholders and executives. Shareholders focus on short-term reported results as these directly affect share prices. Executive bonuses may also be more closely linked to short-term accounting profits than longer-term business value.

Many legacy processes emphasise one or other of these metrics. Often it is the accounting view of capital project benefits that dominates. The accounting payback period often trumps detailed net present value (NPV) calculations.

An online capital budgeting solution has the ability to simultaneously report both cashflow and accounting impacts. This can be for both an individual project and for the entire capital project portfolio.

AI and Machine Learning

Artificial Intelligence (AI) is not truly intelligent. AI has just learned from a vast amount of data to extrapolate patterns of behaviour.

The CapEx management process can benefit from AI in 3 ways:

  1. Preparing business cases.
  2. Optimizing project portfolios.
  3. Providing more objective forecasts on project costs and schedules.

AI systems learn from your project experiences and provide valuable insights. AI can then extrapolate patterns based on similar projects and individuals.

But only if your project planning and execution data is accessible. Isolated systems conceal this incredible source of insight from the enormous potential of AI-powered assistants.

An online budgeting tool that learns from your experiences and others’ can help plan and control capital projects. AI assistants can access large language models such as ChatGPT to prepare high quality business case submissions. AI can analyse candidate projects and help identify the ‘efficient frontier’ of project portfolios. AI tools can rationalize human forecasts to provide more realistic estimates of future costs and timing.

Digitalized and AI-Driven Financial Planning and Analysis

The key benefit of digitally transforming your capital planning process is that it enables better business decisions. You can avoid waste by not starting bad projects, or by terminating them early. You can select higher value initiatives by more fully evaluating benefits and risks.

Projects aligned to strategic imperatives achieve objectives faster, cheaper, and with less risk. A solution such as Stratex Online Project Forecasting and Analysis helps you make better capital budgeting decisions using trustworthy data and AI insights. Learn more about Stratex Online and how it can transform the effectiveness of your capital budgeting strategies by clicking the button below.

Leveraging AI and Digitalization for Financial Planning and Analysis (FP&A) (2024)

FAQs

How can AI be used in FP&A? ›

AI can analyze data to help predict cash flow and identify potential risks, for instance, making it easier for your FP&A team to map a better course for the future.

How can AI help with financial planning? ›

An AI system can help monitor a client's portfolio based on a predetermined plan, balancing assets as the market changes without needing human intervention.

How is AI used in financial analysis? ›

Banks use AI algorithms to analyze market data and news quickly and also use social media to guide investment decisions and trading strategies. Also, insurance companies leverage AI to predict the risk better, detect fraud earlier, and set more accurate premiums.

How AI is the next step in the digitization of the finance sector? ›

Real-time Use Cases Of AI In Finance

It can help improve efficiency, cut costs, and make processes easier for customers and employees. From chatbots and digital assistants to fraud detection and risk management, AI is streamlining various processes and making them more efficient.

How does AI help in money laundering? ›

AI Transaction Monitoring To Alert And Remediate

Financial institutions (FIs) can now employ AI-powered anti-money laundering (AML) transaction monitoring (TM) tools to spot trends and modify algorithms and policies in real time to adapt to new trends as they emerge.

Can AI take over financial analyst? ›

Can AI replace CFA? AI may assist CFAs in their work. Still, it's unlikely to completely replace the knowledge and skills acquired through the rigorous CFA program. The human touch and ethical considerations are crucial aspects of financial analysis that AI cannot replicate.

How AI will transform financial management? ›

Financial reporting and analysis

AI can then use the data to help generate financial statements, such as income statements, balance sheets, and cash flow statements, transforming the data into reports that highlight key performance indicators (KPIs), trends, and observations. It can also help with regulatory reporting.

What impact will AI have on accounting and finance? ›

One of the most immediate and tangible impacts of AI in accounting is the automation of repetitive tasks. Activities such as data entry, invoice processing, and reconciliations, which can be time-consuming and prone to human errors, are efficiently handled by AI-powered systems.

What are the application of AI in financial management? ›

How is AI used in finance? AI in finance can help in five general areas: personalize services and products, create opportunities, manage risk and fraud, enable transparency and compliance, and automate operations and reduce costs.

What is the role of artificial intelligence in financial forecasting? ›

AI-powered financial forecasting isn't just for budgeting. You can leverage this technology to gain valuable insights into things like: Sales forecasting: AI can analyze historical sales data, customer behavior patterns, and market trends to predict future sales figures with greater accuracy.

What is the current use of AI in finance? ›

AI is particularly helpful in corporate finance as it can better predict and assess loan risks. For companies looking to increase their value, AI technologies such as machine learning can help improve loan underwriting and reduce financial risk.

In what ways artificial intelligence is used in banking and finance? ›

AI for corporate banking automates tasks, boosts customer services through chatbots, detects fraud, optimizes investment, and predicts market trends. This increases productivity, lowers costs, and provides more individualized services.

How does JP Morgan use AI? ›

J.P. Morgan is also using AI to automatically show insights to clients, such as cashflow analysis, when they need it. Meanwhile Microsoft recently announced a partnership with risk assessment firm Moody's to develop enhanced risk, data, analytics, research and collaboration solutions powered by generative AI2.

How does AI help digital transformation? ›

Acting as a catalyst, AI helps processes adapt to new information or unexpected changes, leading to improved business operations. Artificial Intelligence is revolutionizing digital transformation by automating routine tasks and optimizing business processes, freeing up human resources for strategic roles.

Will finance be automated by AI? ›

AI is being used in finance to automate manual tasks, such as inputting invoices, tracking receivables, and logging payment transactions so employees are free to focus on value-added strategic work.

How is AI used in automated financial investing? ›

AI's multifaced role

In terms of data analysis, AI can sift through vast amounts of market data and historical trends to identify ideal assets and adjust portfolios in real time as markets fluctuate. AI is also used to improve risk management by analysing complex data and making sophisticated decisions.

What is generative AI in financial planning and analysis? ›

Advanced Forecasting: Generative AI can analyze historical data, market trends, and other variables to create more accurate and reliable forecasts for financial metrics such as revenue, expenses, and cash flow.

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