Identify and eliminate application and online fraud. Address the proliferation of identity theft and synthetic identities. SAS Detection and Investigation for Banking provides a single, end-to-end framework for better fraud detection and greater operational efficiency across multiple channels and products.
Detect more fraud, and reduce your losses.
Our unique, hybrid analytic approach uses multiple techniques – automated business rules, predictive modeling, text mining, database searches, exception reporting, network link analysis, etc. – to spot more suspicious activity with greater accuracy. A powerful fraud analytics engine uses embedded AI and machine learning techniques, combined with traditional detection methods, to process all data (not just a sample) in real time or in batch, to find more fraud and reduce false positives. And by analyzing device data in conjunction with demographic data, you can quickly uncover application and online banking fraud.
Get a consolidated view of fraud risk.
Identify cross-brand/product fraud by viewing customer accounts and transactions for all lines of business in one consolidated view. A unique visualization interface lets you spot linked entities and banking fraud crime rings that you would otherwise miss. Social network diagrams and sophisticated data mining capabilities enable you to better understand new banking fraud threats, so you can prevent substantial losses early. And stay on top of changing fraud trends by continuously improving models and adapting the system.
Boost investigator efficiency, reduce false positives and gain a competitive advantage.
The solution applies risk- and value-based scoring models to accurately score and prioritize alerts before they go to investigators. With the time saved, investigators can work more cases with greater efficiency, and focus on higher-value networks that generate a better ROI. More accurate scoring also means fewer false positives – and that translates to less customer inconvenience and greater customer satisfaction. You can also boost the efficiency of collection processes by identifying banking fraud losses that result from synthetic identities and have little to no chance of recovery.
- Data management. Consolidates and cleanses data from internal and external sources for fraud analysis and investigation.
- Advanced analytics and embedded AI. Provides a broad set of advanced analytic and AI techniques, including modern statistical, machine learning, deep learning and text analytics algorithms, accessible from a single environment.
- Rule and analytic model management. Lets you create and logically manage business rules and analytical models.
- Detection and alert generation. Scores data in real time with an online scoring engine that uses multilayered detection methods – business rules, anomaly detection, advanced analytics, etc. – for greater accuracy.
- Alert management. Combines alerts from multiple monitoring systems, associates them with common data, and gives analysts and investigators a more complete view of risk.
- Search and discovery. Enables free-text, field-based or geospatial searches across all data (internal and external), and lets you refine searches using interactive filters.
- Social network analysis. Provides a unique visualization interface that goes beyond transaction and account views to analyze related activities and relationships at a network dimension.
- Workflow and intelligent case management. Streamlines operations with a systematic process for investigations, using a configurable workflow. Stores all information pertinent to a case for future use.
- Auditability. Enables you to run reports and produce a complete audit trail for all alerts and investigations, in accordance with compliance requirements.
Read the SAS Detection and Investigation for Banking product brief.
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