Banking - Data Driven Customer Service

Impact generated: #BankingDataAnalytics #CustomerServiceOptimization #MachineLearningFinance #FinancialDataAnalysis #DataDrivenBanking #B2BClientSegmentation #FinancialOptimization #DataScienceBanking

(Q3 2018)

I directed the data vertical of a strategic project aimed at transforming the B2B customer service structure for one of the leading Latin American banks. The project's goal was to optimize service delivery for a client base of millions of medium-to-big-size businesses across Brazil by creating service categories that addressed common client characteristics while reducing operational costs. 

Using advanced machine learning techniques, such as factorial analysis and clustering, I identified the distinct client segments.

Linear optimization and simulation were then employed to design a tailored service structure for each segment. The proposed structure was presented to the bank's board, facilitating refinement and validation of criteria. This process required navigating the complexities of a highly sensitive, proprietary data environment and collaborating with bank subject matter experts to ensure accurate data interpretation and usage.

The project successfully reorganized clients into four defined classes, each with clear assignment rules. This enhanced client experience and optimized operational efficiency. The project demonstrates my ability to apply complex data analysis and machine learning techniques to solve high-stakes business problems within the financial industry, and to effectively communicate insights to C-level executives.