Economics Forecasting Risk Analysis 
Trade Credit & Liquidity Management
JULY 24, 2025
Furthermore, decisions made by credit management directly influence working capital performance, bad debt exposure, and the ability of the treasury function to forecast liquidity with accuracy. Macro factors: economic trends, sector volatility, and for exporters, country and political risks. Closing Thoughts.
Fpanda Club
NOVEMBER 15, 2022
Various types of uncertainty can be well illustrated by the so-called Rumsfeld matrix widely used in risk analysis and risk management. From the FP&A’s standpoint the level of awareness and the level of accuracy can be used as these dimensions and then incorporated into forecasting and analysis.
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Planful
JANUARY 26, 2016
Static budgets rely on set periods, a fiscal year for example, and create a fixed forecast for that period. Rolling forecasts, as an extension to financial budgeting, support periodic updating of budget assumptions, and extend the time period out beyond the end of the fiscal year. Improved Risk Analysis.
PYMNTS
APRIL 30, 2020
According to Lori Frank, president and CEO of Argos Risk , COVID-19 is the black swan event for supplier relationship management and supply chain risk analysis. “Before, companies would think they needed to assess risk once a year,” Frank said. ” A Dramatic Shift. ”
Future CFO
AUGUST 27, 2023
You need constant monitoring of your economic outlook because then you can adjust your risk management strategy that will help you mitigate third-party risks." I think what’s important is to find out what data is out there to augment your data analysis," Kesuma added. He called for faster forecast scenarios.
PYMNTS
NOVEMBER 11, 2016
Sure, a corporation with complex international supply chains can never exactly forecast the socioeconomic or environmental factors that could impact business. But sophisticated data management does offer some predictability to vendor risk mitigation and supply chain management. . That’s quite a tall order, however. .
Future CFO
MARCH 27, 2025
He notes that AI-driven predictive analytics has also improved forecasting accuracy, particularly in demand planning, working capital management, and revenue projections. Instead of manually sifting through spreadsheets, CFOs can now ask AI-powered assistants questions like: 'How did our Q4 OPEX compare to forecast?'
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