AI Training for FinTech

The Challenge

A leading FinTech company had assembled a team of data scientists and engineers to develop AI capabilities, but struggled with inefficient workflows, inconsistent AI model performance, and a knowledge gap in implementing advanced techniques. Their existing fraud detection systems were generating too many false positives, undermining customer trust.

Our Solution

We designed a comprehensive 12-week training program tailored specifically to their needs. The curriculum covered advanced machine learning techniques, deep learning for financial data, prompt engineering for generative AI, and MLOps best practices. We combined theoretical instruction with hands-on workshops using the company's actual datasets and problems.

Results

• 85% reduction in false positives for their fraud detection system
• 40% improvement in model development time through improved workflows
• Created 3 new AI models that went into production within 3 months of training
• Developed an internal AI Center of Excellence with formalized best practices
• Eliminated $430K in planned external consulting costs through upskilled internal team

Implementation

We began with a thorough skills assessment to identify specific knowledge gaps. The training was structured as a blend of twice-weekly live sessions and asynchronous learning modules. We incorporated their actual business challenges as capstone projects, ensuring immediate application of new skills. Post-training, we provided four weeks of mentorship to support the transition from learning to implementation.

Technologies Used