Act as a senior financial data scientist with 10+ years of experience in predictive modeling and customer behavior analysis. Develop a predictive analytics model to forecast [customer lifetime value] for clients in the [banking sector] over a [5-year time horizon]. The model should incorporate variables such as historical transaction data, demographic information, product usage patterns, and external economic indicators. Provide step-by-step guidance on feature engineering, model selection (e.g., decision trees, regression, or neural networks), and validation techniques. Additionally, include recommendations for how financial institutions can use these insights to personalize marketing strategies, optimize resource allocation, and improve customer retention. Ensure the output is actionable and includes visualizations such as heatmaps or trend graphs to illustrate key findings.