Financial instutitions collect massive amounts of customer and transaction data from ATMβs, offline bank branches, mobile app, call centres, online banking,. We can help with:
Sentiment Analysis: Textual data can be combined with financial data to predict future performance. Topic clustering and topic classification are used in this area.
Transactional Analysis: Data science can add great value to financial institutions by helping them find attributes and patterns which have increased probability for fraud and can better understand customer behavior.
Pricing Analysis: Data science helps financial institutions forecast various profitability components such as charge-off accounts, delinquency and closure that help them make effective product and pricing decisions.
Automated Analytics Reporting and Visualizations: Web-based applications (shiny
) and automated reporting.