
Forecasting Reimagined: Building Smarter, Adaptive Models
Go beyond static forecasts with adaptive models that combine internal data, external intelligence, and automation. Learn to build more accurate forecasts that respond faster to changing business conditions.
Format
Webcast
Date
Apr 19, 2027
NASBA Field of Study
Finance
Level
Intermediate
CPE Credits
1
Instructor
Allison Ruffino, Aaron Siegel, Michael Burns
Availability
3 months
Product Number
WC5483055
This is a rebroadcast from AICPA ENGAGE 2026.
Traditional forecasting methods often struggle to keep pace with today's rapidly shifting markets, economic conditions, and business realities. Modern finance teams need forecasting models that are dynamic, responsive, and informed by both internal performance data and external market signals.
This webcast explores innovative approaches to forecasting that improve accuracy, reduce manual effort, and support better business decisions.
Learn how automated forecasting assistants can:
- Streamline planning processes
- Minimize common forecasting biases
- Accelerate scenario analysis
You'll also discover how to incorporate industry benchmarks, macroeconomic indicators, and market intelligence into models that continuously adapt as conditions change.
Key features and benefits:
- Learn how to combine internal and external data sources for more informed forecasts
- Explore automated forecasting assistants that improve efficiency and reduce bias
- Build adaptive models designed to respond to changing market conditions
- Incorporate benchmarks, economic indicators, and market signals into forecasting processes
- Enhance forecast accuracy and decision-making with smarter, more responsive planning techniques
Key Topics
- Data-driven forecasting
- Automated & AI-assisted forecasting
- Adaptive planning models
- Scenario analysis & decision support
- Market intelligence, benchmarks & economic indicators
Learning Outcomes
Analyze how to integrate internal data with external intelligence sources to create more robust and responsive forecasting models.
Identify how to deploy automated forecasting assistants that reduce manual effort, eliminate common biases, and accelerate scenario planning cycles.
Apply techniques for creating forecasting models that automatically adjust to changing market conditions and business environments without constant manual recalibration.
Determine how industry benchmarks, macroeconomic data, and market signals can enhance forecast accuracy and relevance.
Who Will Benefit
Corporate finance and controllers
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2 to 5 registrants
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