Certegy provides banking authorization and risk management of $43 billion in check processing for more than 4,000 retailers, including 23 of the top 50, in 300,000-plus locations around the world. Preventing fraud is critical for retailers that strive to provide superior customer service yet must decide to either accept or reject payroll checks or government-issued income assistance checks.
Processing and analyzing banking payment data for 100 million unique consumers requires speed and accuracy to stay one step ahead of criminal activity.
With Oracle Analytics and Autonomous Data Warehouse on Oracle Cloud Infrastructure, Certegy should cut fraud by 10% and improve customer service by reducing declined transactions. The company created a single repository of 850 million records for more accuracy, convenience, and simplicity by improving integration of more than 15 data sources from authorization systems that are both on premises and in Oracle Analytics Cloud.
Oracle Autonomous Database’s autoscaling increases processing capacity for peak performance on demand, and also decreases capacity when idle to minimize costs. Routine database administration in tuning, patching, and repairing is entirely automated—reducing downtime, error, and risk to equip staff with increased data quality and more time to spend on value-added statistical modeling and predictive analysis. Spatial analysis using Oracle’s Autonomous Data Warehouse, allows Certegy to use maps to visually track the fraudulent behavior patterns and locations of an individual across cities and states.
Oracle Analytics Cloud has made data more accessible to the company’s 25 risk analysts and data scientists to better manage overall risk strategies with an intuitive, extensive toolset. Certegy can share interactive risk performance and assessment reports with retail clients in live presentations to better understand their current and past trends.
Oracle Machine Learning in the Oracle Autonomous Database empowers the company’s data scientists to create real-time statistical models using neural networks and linear regression to calculate risk scores and high probabilities of loss with more than 100 variables to help retailers quickly decide to accept or deny a check, with no administration needed, unlike Microsoft Power BI. Certegy staff can very easily compare the expected check cashing vicinity, based on the location of where a payroll check is received, to the actual check cashing location to identify anomalies and aid investigations with law enforcement agencies to apprehend established criminals.
With a robust data and analytics platform from Oracle, Certegy is expanding to mobile payments. This will allow retailers to accept payments directly from consumers’ bank accounts in a fast, simple, and secure way that reduces costs with lower interchange fees. In addition, retailers don’t store any private information, and can process more sales transactions without physical contact.
By using the Oracle Analytics and Autonomous Data Warehouse, our goal is to apply machine learning and spatial analysis to better track check cashing behavior that mitigates risk and prevents fraud in real time to help businesses and consumers more confidently engage in commerce.
Senior Manager, Fraud Analytics, Certegy