This chapter provides functional details about the Oracle Financial Services (OFS) Crime and Compliance Studio (FCC Studio) application.
Topics:
· The Architecture of FCC Studio
· Oracle Financial Crime Graph Model
To effectively monitor anti-money laundering and anti-fraud programs in financial institutions, the most challenging requirement is to quickly identify and adapt to the changing patterns of financial crime. This ability to discover new and emerging criminal behavioral patterns, coupled with the facility to rapidly deploy as models, is a critical requirement.
Data scientists and analysts can use FCC Studio to interactively explore financial crime data and gain insights into new and emerging financial crime patterns and trends.
The key features of FCC Studio include the following:
· Provides an integrated and comprehensive analytics toolkit designed to rapidly discover and model new financial crime patterns.
· Interacts with the database, process the data, and generate patterns in various formats using interpreters.
· Provides secure access to an institution's financial crime data with predefined scenarios, out-of-the-box graph queries, and visualizations.
· Uses Graph Analytics and Graph Query methods to analyze historic data available in the database, and forecast the generated patterns using various interpreters.
· Uses Machine Learning Algorithms to gain insights from historical alert data to prioritize the alerts generated by the detection engines.
· Offers a unified tool for Graph Analytics, Data Visualization, Machine Learning, Scenario Authoring, Pattern Discovery, Data Mashups. and testing for financial crime data.
· Works with Apache Spark, the most prevalent analytics engine on Big Data.
· Works with Apache Zeppelin, a web-based notebook that enables interactive data analysis.
· Supports Polyglot Scenario Authoring to author new scenarios in SQL, Scala, Python, or R language.
· Embedded with a highly scalable in-memory Graph Analytics Engine (PGX).
· Enterprise-ready with underlying OFSAA framework.
· Works with earlier 8.x releases of Oracle Financial Crime and Compliance Management Anti Money Laundering (AML) and Fraud applications.
· Integrated with Oracle Financial Crime Application Data and readily usable across the enterprise financial crime data lake. This can automatically load Oracle AML and Fraud data into the data lake and mashup FCC Studio data with third-party data for discovery and modeling.
The following diagram depicts the architecture of the FCC Studio application:
Figure 1: FCC Studio Architecture
The Oracle Financial Crime Graph Model serves as a window into the financial crimes data lake. It collates disparate data sets into an enterprise-wide global graph, enabling a whole new set of financial crime use cases. The Graph model enables to accelerate financial crime investigation use cases.
For information on Graph Data Model, see Graph Data Model.
For information on the node and edge properties of the Oracle Financial Crime Graph Model, see the Data Model Guides.
Figure 2: Oracle Financial Crime Graph Model
NOTE |
The Case node in this Financial Crime Graph Model is loaded only when you load the FCDM data from Enterprise Case Management (ECM). When data is loaded from ECM, the graph includes “CASE” nodes and “has event” edges. |