Is Your Economic Forecast Setting You Up for Success?

Financial institutions that rely only on internal signals often miss critical market shifts. Without external indicators like GDP trends, exchange rates, or inflation data, forecasts are incomplete—and decisions become reactive instead of strategic.

🧠 According to the Federal Reserve, improving forecasting accuracy by even one standard deviation can reduce risk prediction errors by up to 20%.

Why External Data Sharpens Economic Forecasts

By integrating market-level third-party data into economic models, financial institutions can:

✅ Identify macro trends that impact growth, returns, and exposure
✅ Strengthen investment strategies with real-time market signals
✅ Improve asset allocation accuracy and reduce volatility
✅ Make informed decisions based on both historical and predictive insights
✅ Increase confidence in strategic planning

How It Works

🔹 Use time-series models to forecast inflation, interest rates, and GDP growth
🔹 Combine internal transaction data with external market indicators to uncover patterns
🔹 Model how sector, regional, or currency shifts will impact portfolio performance
🔹 Layer in economic signals for more accurate lending, investment, or treasury decisions

Real-World Impact: Smarter Forecasts, Smarter Moves

A Vanguard study showed that 90% of portfolio volatility and 87% of returns stem from asset allocation—decisions that are directly informed by economic forecasts.

📩 Want to strengthen your forecasts with data that goes beyond your four walls?

Let’s talk about how Blue Street Data can connect you with the most relevant and predictive market data to improve your forecasting accuracy.

👉 Talk to a Data Expert

Live Webinar

Is “Quality” Killing Your AI? Defining Data Fit for Strategic Success

February 18th, 2026 / 1:00 PM EST

Every data investment carries risk unless you know how to measure its “fit” for the mission. Many organizations assume that “high-quality” data is sufficient for AI and analytics, only to discover too late that data fit is the real determinant of success. In this live session from Blue Street Data’s Building with Better Data series, Andy Hannah and Malcolm Hawker unpack why data that works for BI can be dangerous for AI, leading to model failure, wasted spend, and lost trust. You’ll learn how to define, measure, and validate data fit so your models deliver reliable, business-aligned outcomes. Reserve your spot today!