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13: Artificial Intelligence in Financial Management

  • Page ID
    150170
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    Concept map illustrating artificial intelligence in financial management, showing applications in risk and fraud management, algorithmic trading and robo-advising, predictive analytics, ethical and data governance, and a transition to conversational AI. These applications connect to core finance concepts such as cash flows, discount rates, risk–return tradeoffs, WACC, and NPV, leading to improved financial decisions and firm value.
    Figure 13.0 – This concept map illustrates how artificial intelligence supports core financial decisions—such as risk assessment, forecasting, capital budgeting, and governance—by improving cash-flow estimation, discount-rate assessment, and ultimately firm value.

    Introduction: Artificial Intelligence in Financial Management

    Artificial intelligence (AI) is reshaping financial management by combining automation, prediction, and analytics. Modern finance teams use machine learning, natural-language processing, and related methods to process large data sets, detect patterns, forecast outcomes, and support faster and more consistent decisions. When implemented with appropriate governance and oversight, AI can lower operating costs, reduce errors and fraud, and improve strategic planning. At the same time, the use of AI introduces important ethical, legal, and regulatory considerations that financial managers must understand and actively manage.

    Why This Matters

    AI matters in managerial finance because it affects the two inputs that drive valuation: expected cash flows and the rate used to discount those cash flows. Improvements in forecasting can reduce estimation error in revenues, costs, and working-capital assumptions, leading to better capital budgeting and NPV decisions. Stronger risk detection and control can protect cash flows from loss events, reduce volatility, and potentially influence the firm’s cost of capital.

    In practice, the financial value of AI is realized not by adopting new tools for their own sake, but by improving how managers allocate capital, price risk, monitor performance, and enforce internal controls. Throughout this chapter, the focus remains on how AI supports these managerial decisions rather than on the technical details of model construction.


    This page titled 13: Artificial Intelligence in Financial Management is shared under a CC BY 4.0 license and was authored, remixed, and/or curated by Andrew Carr.

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