Fraud Detection
Identify and prevent unauthorized activity
Financial losses to consumers and financial institutions from account takeovers (ATOs) rose by 72% last year to reach $6.8 billion.
The Challenge:
The complexities of fraud in today’s world are growing exponentially: state-sponsored terrorism, professional criminals, money-laundering groups, and even basement bad-actors are improving their techniques and becoming more difficult to understand, expose, and prevent.
Organizations have historically taken a fragmented approach to fraud detection, attempting to spot anomalies across disparate data silos that involve manual processes to unify. This approach has resulted in fraud being detected hours, days, or even longer after it occurs – by the time fraud is detected, the perpetrator and your valuable assets are long gone.
A Better Way:
Fraud can now be detected in near real-time thanks to new technologies and predictive analytics techniques. Organizations can now combine big data sources with streaming data and real-time monitoring to score risk and prevent fraud as it occurs.
Introducing FeatureBase
The Real-Time Database for Any Scale
FeatureBase is designed to deliver secure, fast, continuous access to all your data in a machine-native format. The first and most crucial step in leveraging big data for fraud detection is ensuring all of the data is ready and accessible.
Rather than the conventional approach of moving, copying, and preaggregating data, FeatureBase extracts features from each of the underlying data sources and stores them in a centralized access point, making data immediately accessible, actionable, and reusable. FeatureBase maintains up-to-the-millisecond data updates with no time-consuming preaggregation necessary.
Request a Consultation
Contact us today to learn more about how Molecula FeatureBase can transform your business through eliminating preaggregation and unlocking real-time value.