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Supercharge Your Anti-Financial Crime Program with Advanced Analytics
Oracle Financial Services Crime and Compliance Studio is an advanced analytics application that supercharges anti-financial crime programs for better customer due diligence, transaction monitoring, and investigations. It comprises a suite of advanced tools that leverage the latest innovations in artificial intelligence, open source technologies, and data management. Purpose-built for fighting financial crime, it is fully integrated with other Oracle Financial Crime and Compliance Management applications.
Benefits
Get more value from your data
Bring all your data—both internal and third-party—together and get seamless, secure access to it. Explore in real time and extract previously inaccessible insights.
Gain speed and insights with Investigation Hub
Surface hidden relationships using graph visualizations—embedded in your case manager—that put data at your fingertips. Automatic case narratives further boost efficiency.
Outsmart new criminal schemes
Use our in-memory graph to find emerging financial crime patterns, then create new scenarios or models with your preferred open source programing language.
Play Beyond the Rules: Fight Money Laundering with Graph Analytics
Learn how to leverage this powerful technology to maximize the long-term success of your anti-money laundering program.
Key Product Features
Open all Close allGraph analytics
Uncover hidden relationships and power intuitive visualizations
Easily explore any relationship among entities in real time to extract valuable, previously inaccessible insights from your data.
- Succinctly express complex money patterns, detect multi-hop relationships, and identify hubs and spokes of activity using 30+ supplied graph algorithms and a built-in, SQL-like query language.
- Power intuitive, dynamic visualizations in Investigation Hub for faster, more accurate investigations.
- Drive better modeling through better understanding of the network.
- Enhance detection by applying deep learning to find similar criminal networks.
- Boost efficiency by applying machine learning to graphs to automate case decisions.
Entity resolution
Gain a single view of each customer and external entity
Preconfigured and extensible entity resolution ensures your global graph is accurate.
- Targeted techniques for different attributes allows for missing or multiple information sources.
- UI-based configurations for weighting scoring methods.
- Machine learning tuning for enhanced resolution scoring.
- Increase the confidence of resolved entities by examining their surrounding graph structure.
Machine learning with the Adaptive Intelligence Foundation
Adaptive, machine-based customer behavior models
Augment existing rules-based models and increase effectiveness.
- Integrated environment to manage both rules-based and advanced machine models.
- Explainable AI (XAI) for insight into sophisticated black box machine models.
- Advanced, time-series feature engineering techniques to enrich data and detect trends.
- Easily customizable with 300+ out-of-the-box risk indicators.
Open source technologies
Build models and scenarios using the tools you love
Leverage popular open source languages, technologies, and standards, minimizing the need to retrain staff, increasing productivity.
- Publish machine-learning (ML) notebooks in R and Python. Use open source packages in R, Python, Spark ML, or Oracle’s optimized libraries for machine learning, such as Oracle R Enterprise and Oracle Advanced Analytics for Hadoop.
- Author, deploy, and test scenarios in SQL, Scala, Python, or R.
- Leverage Apache Zeppelin and Jupyter notebooks, the de facto standard development tools for data scientists.
Advanced data management
Explore all your data, in one place
Maximize the value of your data lake.
- Embedded, pre-defined graph analytics engine automatically loads data from the Financial Services Data Foundation into a lighting fast, in-memory graph.
- Explore internal and third-party data together, in memory.
- Preloaded data from the International Consortium of Investigative Journalists adds context to investigations and highlights areas of unknown risk.
