Why Transparency Matters in Modern Economic Forecasting
At Macrobond, we prioritize providing our customers with the best tools for making informed decisions.
When it comes to economic forecasting and "nowcasting," many in the financial industry are stuck in the past, using outdated models and techniques. It's ironic because nearly every day these same people are asking how Macrobond is adopting AI in our product and our business.
So why haven’t most people adopted more advanced machine learning or “AI” models in their forecasting, when we know these modern techniques yield significantly better accuracy? And why do they persist with pre-canned “black box” solutions? The answer is simple yet complex: it’s difficult. It’s difficult to understand, to implement, to trust, and to explain advanced forecasting methods.
We decided that the answer was to provide our customers with a tool, Indicio, to empower them with a simple yet powerful way to use the most advanced forecast techniques, all fully integrated with their existing Macrobond setup, and offering full control and transparency.
Here’s why I believe this approach is superior to relying on a third party for already calculated forecasts.
Empowerment
One of the primary reasons we integrated Indicio's tools into our platform is the empowerment it offers to our users. By allowing them to select the inputs that are most relevant based on their own experience and expertise, Indicio offers a more personalized experience. This customization ensures that the forecasts generated are not only accurate but also highly relevant to the user's needs. In contrast, black-box models often operate on generic inputs, potentially leading to outputs that are less applicable to specific business scenarios or that can even include factors that the user does not believe are relevant.
Transparency
Transparency is a key factor in building trust in a model. With Indicio integrated into Macrobond, users can see and understand how their inputs affect the outputs. This visibility fosters a deeper understanding of the forecasting process, enabling users to trust the results more. We even provide SHAP values! On the other hand, black-box models often provide little to no insight into how predictions are made. For example, utilizing Indicio, Macrobond’s AI/ML forecasting partner, Middleburg Communities now generates their own forecasts for key market conditions in 400 counties. Brad Case says, “Local market conditions are inherently uncertain, and using Macrobond and Indicio means that we know how they're being forecasted and we know how much confidence we have in our forecasts. That’s just not possible with an off-the-shelf forecast, which tends to be a black box.” Opacity can lead to scepticism and reluctance to rely on the forecasts provided because even when it’s right, you cannot be sure why it was right.
Flexibility
Business environments are dynamic and ever-changing. Indicio’s flexibility allows users to quickly adapt their inputs to reflect new data or changes in the market. This adaptability is crucial for producing timely and relevant forecasts. Black-box models, however, often lack this flexibility, as they are designed to function with fixed inputs and predefined algorithms. This rigidity can make them less responsive to real-time changes.
Enhanced Decision Making
The ability to choose inputs and understand the forecasting process enhances decision-making. Users of Indicio, through the Macrobond platform, are equipped with insights into the underlying factors driving the forecasts. This knowledge allows them to make more informed decisions, as they can identify and adjust for potential biases or anomalies. Conversely, black-box models, with their hidden methodologies, leave users making decisions based on opaque outputs, potentially missing critical nuances.
Competence and Confidence
Finally, tools like Indicio contribute to building users' competence and confidence. As users engage with the customization process and see the direct impact of their choices, they develop a stronger grasp of forecasting principles and data analysis. This empowerment not only boosts confidence but also fosters a culture of data literacy and proactive decision-making within the organization.
Conclusion
While black-box forecasting models offer convenience, they fall short in providing the transparency, customization, and adaptability that modern businesses require. By integrating Indicio into Macrobond, we offer a superior solution that empowers users, enhances trust, and ultimately leads to better decision-making.
In an era where every firm is scrambling to adopt “AI,” leave your outdated models behind.
Choose transparency, choose customization, choose Macrobond x Indicio.