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Thanks to sophisticated tools, the role of CFOs is increasingly visible within companies. It gives them room to use their expertise, insights and leadership more broadly. What are the key building blocks and techniques they use to monitor financial stability and increase profitability?

On the one hand, real-time financial data allows CFOs to react more quickly to changing circumstances and take timely action, at the same time they are also better able to look further into the future. Thanks to new techniques, more accurate forecasts can be made about future financial performance. CFOs can also respond more proactively to trends, opportunities and risks.

New technology offers additional opportunities for data analysis, automation, risk management and strategic planning. This allows CFOs to take a more integrated approach to financial management. What kind of tools and building blocks are we talking about? 

Predictive Analytics: By using historical data and machine learning models, CFOs can forecast future cash flows, debt levels and funding needs. This helps plan capital needs and optimise debt structure.

Dashboards and visualisations: BI tools allow CFOs to get real-time insights into financial performance (including cash flow, working capital) and risk profiles. This facilitates monitoring debt ratios and identifying trends that may affect capital structure. BI tools (such as Tableau, Power BI and QlikView) provide detailed analyses of cost structures and identify where costs can be reduced without affecting operational efficiency.

Blockchain can provide transparent and immutable transaction records. This improves the integrity of financial data and helps identify operational risks. Blockchain can also provide real-time insights into cash flows by directly recording transactions. This helps CFOs accurately monitor and manage cash flow. Also through fast payment processing, blockchain can help accelerate cash flows, improving the company's liquidity position.

Smart Contracts: this allows financial transactions to be executed automatically if certain criteria are met. This requires less 'labour', speeds up transactions and reduces costs. They also ensure that conditions (e.g. for loan repayments) are met. 

With RPA, repetitive tasks within risk management can be automated. Think of data collection, financial reporting and compliance monitoring. This increases accuracy and efficiency. Discrepancies and suspicious transactions can also be quickly identified with RPA. Furthermore, all kinds of practical tasks can be handled with RPA (such as making payments, processing invoices and sending payment reminders). Hardly any human hands are involved. In other words: less personnel costs and less risk of errors.

Optimisation of Financing Decisions: Scenario analysis and simulations allow CFOs to assess the impact of different economic scenarios on debt and capital requirements. For example, early identification of the impact of changing interest rates on debt and interest payments is possible. Also, by analysing different refinancing scenarios, the CFO can determine when it is advantageous to refinance or repay debt to minimise funding costs.

Scenario analysis (with tools such as Tableau, Adaptive Insights, BOARD and Jedox) can be used to test the robustness of the company under extreme conditions, such as economic recessions, market shocks or unexpected operational disruptions. By simulating the impact of different risks (such as currency risk, credit risk and market risk), CFOs can develop strategies to mitigate these risks.

Automation of hedging: Algorithmic trading and automated hedging strategies can help manage interest rate and currency risks. This can contribute to a more stable financial position by minimising unexpected debt fluctuations.

Cloud computing and ERP systems: cloud-based ERP systems offer comprehensive functionalities for (real-time) management of financial processes, including debt management and capital planning.

AI-driven Risk Assessment: AI can be used to analyse and assess credit risk, among other things, allowing CFOs to make more informed decisions on debt financing and capital allocation. ML algorithms can be used to develop optimisation models for capital structure. As a result, the cost of debt and return on equity can be maximised.

Listed examples are not exhaustive. Not named, for example, are RegTech and SurTech for managing regulatory, compliance and insurance risks. Advanced tools are also available for Cybersecurity such as threat intelligence platforms and applying distributed ledger technology (DLT) for verification to prevent fraud.

The bottom line is that all this technology gives the CFO tools to operate even more strategically and proactively to increase financial stability as well as profitability. As automation advances, the role of the CFO will become increasingly dominant within the company.