The Balanced Approach
Case study:
AI-First Approach in Cash Flow Issues Detection
A mid-sized professional services firm with 9 years of steady 10-20% annual growth suddenly faced unexpected cash flow problems.
Approach:
- Gathered 3 years of financial data
- Used AI to create comprehensive graphs of cash flow and revenue
- Employed AI algorithms for pattern identification and change point detection
- Analyzed AI-generated insights and correlated with business operations
- Engaged in discussions with stakeholders to understand the context.
Key Findings:
- AI analysis highlighted a significant change point about 14 months ago, where the relationship between revenue and cash flow began to diverge.
- Investigation revealed that the company had changed its payment policy around this time, offering more generous terms to attract new customers.
- While this boosted revenue, it also extended the cash conversion cycle, leading to cash flow issues.
Mitigation:
- Refined customer segmentation for payment terms
- Implemented early payment incentives
- Adjusted pricing to account for extended payment periods
Bottom Line: AI significantly accelerated the analysis process and provided insights that would have been challenging to uncover using traditional methods. The combination of AI-driven analysis and CFO expertise led to a comprehensive understanding of the issue and targeted solutions.
Case study:
AI-Powered Cash Flow Forecasting
Develop a more efficient and accurate method for cash flow forecasting
Approach:
- Uploaded a year's worth of cash flow statements from multiple banks into AI
- AI consolidated and standardized the data format across all statements
- AI classified transactions, identifying their nature with minimal guidance
- Generated weekly summaries of cash flow patterns
- Identified trends and patterns in the dataset
- Produced a 12-week cash flow forecast based on historical data
- Created a comprehensive graph to visualize the results
Key Outcomes:
- High-quality forecast that accounted for weekly trends
- Matched or surpassed traditional forecasting accuracy, especially for weeks 5-12
- Significant time savings compared to manual forecasting methods
- Potential for improved forecast quality over time with consistent use
The AI-based cash flow forecast saved substantial time and energy while providing accuracy comparable to or better than traditional methods, especially for medium-term projections. This approach allows CFOs to focus more on strategic analysis and decision-making rather than data processing.
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