A financial institution is facing increasing challenges in identifying and mitigating fraudulent transactions amid growing volumes of complex financial data. Critically analyze how advanced machine learning $($ML$)$ techniques can be leveraged to develop a robust fraud detection system. Additionally, evaluate the key factors and criteria that must be considered when choosing the most suitable ML methods to ensure continuous improvement and adaptability evolving fraud patterns and emerging threats.