See how Moody's Corporation improved forecast accuracy, reduced manual effort, and scaled global treasury operations.
ION Treasury Industry Awards
From challenges to outcome
Download the case study
© ION 2026. All Rights Reserved. All company, product, and service names are acknowledged.
The challenge
Manual forecasting doesn’t scale in complex treasury environments.
At Moody's Corporation, fragmented data, spreadsheet-based workflows, and limited forecasting accuracy created operational inefficiencies and increased risk.
What this meant:
- High manual effort across regions
- Limited ability to model variability
- Time-consuming forecasting cycles
The challenge
Manual forecasting doesn’t scale in complex treasury environments.
At Moody's Corporation, fragmented data, spreadsheet-based workflows, and limited forecasting accuracy created operational inefficiencies and increased risk.
What this meant:
- High manual effort across regions
- Limited ability to model variability
- Time-consuming forecasting cycles
What they set out to fix
Moody's Corporation aimed to modernize forecasting and improve control across treasury operations.
Focus areas:
- Automating manual workflows
- Improving forecast accuracy
- Integrating data across systems
- Reducing operational risk
What they set out to fix
Moody's Corporation aimed to modernize forecasting and improve control across treasury operations.
Focus areas:
- Automating manual workflows
- Improving forecast accuracy
- Integrating data across systems
- Reducing operational risk
Results
A more intelligent, AI-driven approach to forecasting changed the outcome.
The transformation delivered measurable improvements:
- Faster forecasting cycles
- Improved forecast accuracy
- Reduced manual intervention
- Stronger control and auditability
Results
The transformation delivered measurable improvements:
- Faster forecasting cycles
- Improved forecast accuracy
- Reduced manual intervention
- Stronger control and auditability
The approach
Working with ION, Moody’s implemented an AI-driven forecasting approach integrated with its treasury systems.
The solution introduced:
- Automated data integration
- Machine learning-based forecasting
- A unified, scalable framework
Client perspective
“We’ve achieved high-accuracy classification of bank statement items by replacing brittle manual rules with machine learning. This dramatically reduces exception handling and ongoing maintenance and increases accuracy.”
— Deepali Chawla
Chief Treasury Officer, Moody's Corporation
What you’ll learn
Download the full case study to see:
- How Moody’s replaced spreadsheet-based forecasting
- The role of AI in improving forecast precision
- How data from multiple systems was integrated
- The approach used to scale forecasting across regions
- Key outcomes and implementation insights
Move beyond manual forecasting
Learn how Moody's Corporation transformed treasury operations with AI.
From challenges to outcome
The challenge
Manual forecasting doesn’t scale in complex treasury environments.
At Moody's Corporation, fragmented data, spreadsheet-based workflows, and limited forecasting accuracy created operational inefficiencies and increased risk.
What this meant:
- High manual effort across regions
- Limited ability to model variability
- Time-consuming forecasting cycles
What they set out to fix
Moody's Corporation aimed to modernize forecasting and improve control across treasury operations.
Focus areas:
- Automating manual workflows
- Improving forecast accuracy
- Integrating data across systems
- Reducing operational risk
Results
A more intelligent, AI-driven approach to forecasting changed the outcome.
The transformation delivered measurable improvements:
- Faster forecasting cycles
- Improved forecast accuracy
- Reduced manual intervention
- Stronger control and auditability
The approach
Working with ION, Moody’s implemented an AI-driven forecasting approach integrated with its treasury systems.
The solution introduced:
- Automated data integration
- Machine learning-based forecasting
- A unified, scalable framework
Client perspective
“We’ve achieved high-accuracy classification of bank statement items by replacing brittle manual rules with machine learning. This dramatically reduces exception handling and ongoing maintenance and increases accuracy.”
— Deepali Chawla
Chief Treasury Officer, Moody's Corporation
What you’ll learn
Download the full case study to see:
- How Moody’s replaced spreadsheet-based forecasting
- The role of AI in improving forecast precision
- How data from multiple systems was integrated
- The approach used to scale forecasting across regions
- Key outcomes and implementation insights
Move beyond manual forecasting
Learn how Moody's Corporation transformed
treasury operations with AI
with AI
See how Moody's Corporation improved forecast accuracy, reduced manual effort, and scaled global treasury operations.