Gain a 360-degree view into the customer to understand their spending behaviors, improve customer experiences and drive significant cross-sell opportunities.
Scale on the lakehouse to acquire, process, categorize and contextualize 1 billion card transaction data points
Extract customer insights from the contextual data passed from a merchant to a bank to boost card transaction authorization efficiency
Reduce manual effort and streamline operations with automation through machine learning
Hyper-personalized customer experiences
Uncover actionable insights into customer preferences, behaviors and patterns to deliver highly tailored experiences or to prevent fraudulent activity.
Classify card transaction data with clear brand information to unlock deeper customer insights
Leverage behavioral clustering to segment customers based on transactional patterns
Understand spending patterns using advanced techniques like graph analytics, matrix computation and natural language processing
Reduce the risk of financial losses for customers by identifying and flagging potentially fraudulent transactions
Regularity of payments
Improve the financial health and well-being of customers while reducing the risk of financial losses for banks.
Extract information about the regularity of payments from card transaction data to help customers be more responsible in their payment practices
Detect fraudulent activities that may impact the regularity of payments, such as identity theft or unauthorized transactions
Leverage machine learning to automatically send notifications to customers about upcoming payments
Estimate customer income to feed back into KYC processes