SAS Detection and Investigation for Banking

Detect and prevent organized and first-party fraud with a single, end-to-end solution.

Identify and eliminate application and online fraud. Address the proliferation of identity theft and synthetic identities.

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.

Key Features

A single, end-to-end framework for better fraud detection and greater operational efficiency across multiple channels and products.

Data management

Integrates data from any internal or external source – watch lists, third parties, unstructured text, etc. – regardless of system or format, and integrates seamlessly with existing rules engines.

Advanced analytics with embedded AI

Provides a broad set of advanced analytic and AI techniques, including modern statistical, machine learning, deep learning and text analytics algorithms.

Rule & analytic model management

Includes prepackaged heuristic rules, anomaly detection and predictive models, and lets you create and logically manage business rules, analytic models, alerts and watch lists.

Detection & alert generation

Enables the systematic detection of suspicious activity using a fraud scoring engine that that combines business rules, anomaly detection and advanced analytics to score transactions in real time.

Alert management

Combines alerts from multiple monitoring systems, associates them with common data and gives investigators a more complete perspective on risk associated with individuals or groups.

Social network analysis

Provides a unique visualization interface that lets you go beyond transaction and account views to analyze related activities and relationships at a network dimension.

Search & discovery

Lets you perform free-text, field-based or geospatial searches across all internal and external data, and refine searches using interactive filters.

Intelligent case management

Systematically facilitates investigative reviews using a configurable workflow, and stores all information pertinent to a case.

Flexible deployment options

Enables you to choose the deployment option that works best for you – complete hosting by SAS, deployment at your site or a combination of the two.

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