Category: Risk Management
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Caveats and Pitfalls When Using AI for Price Optimization
1. Data Quality Is a Bigger Risk Than Algorithm Choice AI pricing engines rely heavily on historical data to train demand forecasting and elasticity models. If that data contains gaps, errors, or inconsistencies—such as outdated costs, missing promo labels, or inconsistent SKUs—the resulting price recommendations may be worse than manual judgment. Example: A model trained on…
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AI in Financial Forecasting: How Banks and Financial Institutions Can Predict and Manage Risks
In today’s fast-paced and volatile financial landscape, banks and financial institutions face unprecedented challenges. From fluctuating markets to evolving regulatory demands and rising cyber threats, the ability to predict and manage risks has never been more critical. Fortunately, artificial intelligence (AI) is stepping up as a game-changer, offering predictive tools that empower these institutions to…