oracle financial services crime and compliance studio · about oracle financial services crime and...

Oracle Financial Services Crime and Compliance Studio

User Guide

Release 8.0.7.3.0

March 2020

E91246.01

OFS Crime and Compliance Studio

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For information on third party licenses, click here.

OFS Crime and Compliance Studio User Guide | 1

https://docs.oracle.com/cd/E61555_01/licensing.htm

https://docs.oracle.com/cd/E61555_01/licensing.htm

Document Control

Version Number Revision Date Changes Done

8.0.7.3.0 Updated: March 2020 Updated the guide for 8.0.7.3.0 release.

8.0.7.2.0 Updated: February 2020 Updated the guide for 8.0.7.2.0 release.

8.0.7.1.0 Updated: October 2019 Updated the guide for 8.0.7.1.0 release.

8.0.7.0.0 Created: Feb 2019 Created the first version of the Crime and Compliance Studio User Guide.


Table of Contents

1 Preface ................................................................................................................................. 3

1.1 Summary....................................................................................................................................................................... 3

1.2 Audience ....................................................................................................................................................................... 3

1.3 Related Documents..................................................................................................................................................... 3

2 About Oracle Financial Services Crime and Compliance Studio ................................... 4

2.1 The Architecture of Crime and Compliance Studio ............................................................................................ 4

2.2 Oracle Financial Crime Graph Model ...................................................................................................................... 5

3 Getting Started.................................................................................................................... 7

3.1 Accessing Crime and Compliance Studio Application ........................................................................................ 7

3.2 FCC Studio Interface ................................................................................................................................................... 8

4 Managing Notebooks......................................................................................................... 11

4.1 Creating a Notebook.................................................................................................................................................. 11

4.2 Importing a Notebook .............................................................................................................................................. 12

4.3 Exporting a Notebook .............................................................................................................................................. 13

4.3.1 Exporting All Notebooks .................................................................................................................................... 13

4.3.2 Exporting Individual Notebooks ....................................................................................................................... 14

4.4 Deleting a Notebook................................................................................................................................................. 14

4.5 Common Screen Elements in a Notebook........................................................................................................... 14

4.6 Creating Paragraph................................................................................................................................................... 16

4.7 Interpreter Toolbar.................................................................................................................................................... 17

4.7.1 FCC Python ........................................................................................................................................................... 18

4.7.2 Spark ...................................................................................................................................................................... 18

4.7.3 FCC JDBC .............................................................................................................................................................. 18

4.7.4 PGX-Java .............................................................................................................................................................. 19

4.7.5 FCC PySpark ......................................................................................................................................................... 19

4.7.6 PGQL ..................................................................................................................................................................... 20

4.7.7 FCC ORE ............................................................................................................................................................... 20

4.7.8 Add Paragraph ................................................................................................................................................... 20

4.7.9 JDBC ..................................................................................................................................................................... 20

4.7.10 FCC Spark Scala .................................................................................................................................................. 21

1

4.7.11 FCC Spark SQL .....................................................................................................................................................22

4.7.12 PySpark .................................................................................................................................................................22

4.7.13 Markdown .............................................................................................................................................................22

4.7.14 PGX-Algorithm ....................................................................................................................................................22

4.8 Paragraph Settings Bar ............................................................................................................................................ 23

4.8.1 Paragraph Dependencies ................................................................................................................................. 24

4.8.2 Running All Notebook Paragraphs ................................................................................................................. 24

4.9 Publishing a Notebook............................................................................................................................................. 25

4.9.1 Publishing a Non-Scenario Notebook .............................................................................................................25

4.9.2 Publishing a Scenario Notebook ......................................................................................................................25

4.10 Managing Results...................................................................................................................................................... 27

4.10.1 Paragraph Results ...............................................................................................................................................27

4.10.2 Graph Results ...................................................................................................................................................... 30

5 Managing Out of the Box Notebooks.............................................................................. 35

5.1 Out of the Box Notebooks....................................................................................................................................... 35

5.1.1 RMF Account Scenario .......................................................................................................................................35

6 Managing Graphs .............................................................................................................. 42

6.1 Creating Graphs........................................................................................................................................................ 42

7 Managing Templates ....................................................................................................... 46

7.1 Creating a Template ................................................................................................................................................ 46

7.2 Updating a Template............................................................................................................................................... 47

7.3 Applying Template to a Notebook ....................................................................................................................... 47

8 Create Event API .............................................................................................................. 48

2


PrefaceSummary

1 Preface

1.1 SummaryThis guide provides information related to end-user tasks in the Oracle Financial Services (OFS) Crime and Compliance Studio (FCC Studio) application.

1.2 AudienceThis guide is intended for Data Analysts and Data Scientists and the basic knowledge of the following is recommended:

UNIX commands

Database concepts

Big Data

Python

Scala

Spark

Oracle R

SQL

Groovy

Markdown

1.3 Related DocumentsYou can access the following additional documents related to the OFS Crime and Compliance Studio application from the Oracle Help Center (OHC) Documentation Library:

Oracle Financial Services Crime and Compliance Studio Installation Guide

Oracle Financial Services Crime and Compliance Studio Deployment Guide (Using Kubernetes)

Oracle Financial Services Crime and Compliance Studio Administration Guide

Oracle Financial Services Crime and Compliance Studio Data Model Guides

Oracle Financial Services Crime and Compliance Studio Release Notes and Readme

https://docs.oracle.com/cd/E60570_01/studiohome.htm

https://docs.oracle.com/cd/E60570_01/studiohome.htm

https://docs.oracle.com/en/industries/financial-services/

About Oracle Financial Services Crime and Compliance StudioThe Architecture of Crime and Compliance Studio

2 About Oracle Financial Services Crime and Com-pliance StudioThis chapter provides functional details about the Oracle Financial Services (OFS) Crime and Compli-ance Studio (FCC Studio) application and includes the following sections:

Introduction to Crime and Compliance Studio

The Architecture of Crime and Compliance Studio

Oracle Financial Crime Graph Model

Introduction to Crime and Compliance Studio

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 data-base, 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 Author-ing, 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 lan-guage.

Embedded with 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.

2.1 The Architecture of Crime and Compliance StudioThe following diagram depicts the architecture of the FCC Studio application:

Oracle Financial Services Investigation Hub User Guide | 4

About Oracle Financial Services Crime and Compliance StudioOracle Financial Crime Graph Model

Figure 1: Crime and Compliance Studio Architecture

2.2 Oracle Financial Crime Graph ModelThe Oracle Financial Crime Graph Model serves as a window into the financial crimes data lake. It col-lates 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.


https://docs.oracle.com/cd/E56133_01/latest/reference/overview/graph-model.html

https://docs.oracle.com/cd/E56133_01/latest/reference/overview/graph-model.html

https://docs.oracle.com/cd/E91852_01/datamodel.htm

https://docs.oracle.com/cd/E91852_01/datamodel.htm

About Oracle Financial Services Crime and Compliance StudioOracle Financial Crime Graph Model

Figure 2: Oracle Financial Crime Graph Model


Getting StartedAccessing Crime and Compliance Studio Application

3 Getting StartedThis section includes the following topics:

Accessing Crime and Compliance Studio Application

FCC Studio Interface

3.1 Accessing Crime and Compliance Studio ApplicationTo access the FCC Studio application, follow these steps:

1. Enter the URL in the following format in the web browser:

https://<Host_Name>:<Port_Number>

Here <Port_Number> is,

7008 for FCC Studio installed on-premise.

30078 for FCC Studio deployed on the Kubernetes cluster.

The FCC Studio application login page is displayed.

Figure 3: Crime and Compliance Studio Login Page

2. Log in with the Username and Password.

3. Click Login.

The Crime and Compliance Studio application’s landing page is displayed.


Getting StartedFCC Studio Interface

Figure 4: Crime and Compliance Studio Landing Page

3.2 FCC Studio InterfaceThe components available in the FCC Studio landing page are as follows:

Studio Workspace: The landing page that is displayed after logging into the FCC Studio applica-tion. It displays the collection of notebooks that are mapped to the role of the logged-in user.

Menu Button: Click this button to display the menu items applicable to the logged-in user.

Figure 5: Menu Items

Home Button: Click this button to navigate to the home page.



Notebook Search Filter: Enter the keyword to filter a notebook by name.

Filter by Tags: The notebooks with common tags are grouped. Click the required tag to filter and display the notebooks with the selected tag.

Create Button: Click this button to create a new notebook.

Select Notebooks: Click this icon to enable the selection of multiple notebooks for bulk opera-tion, such as Delete notebooks.

On clicking this icon, check boxes are displayed for the notebooks.

Import Notebooks: Click this icon to import notebook(s).

Export Notebooks: Click this icon to export notebook(s).



Open Iframe View of Notebooks: Hovering the cursor over notebooks reveals an Open as Iframe button.

Click the Iframe button to open a dialog box with the following settings:

Show toolbar actions

Show add-paragraph actions

Show paragraph actions

Show paragraph code

By default, these settings are enabled and saved locally and are applied each time the Iframe set-tings dialog is opened. This behavior can be disabled by unchecking the 'Save Settings' check box on the dialog.


Managing NotebooksCreating a Notebook

4 Managing NotebooksA notebook is a collection of paragraphs and acts as a container to hold one or more paragraphs. Each notebook is a collection of documentation and snippets of executable code. The notebook allows large scripts to be broken into a modular collection of executable code with tailored results. Different lan-guages, such as Groovy, Scala, Python and Oracle’s own property graph query language (PGQL), can be combined into one notebook. Each notebook is mapped to the role of the logged-in user.

This chapter includes the following sections:

Creating a Notebook

Importing a Notebook

Exporting a Notebook

Deleting a Notebook

Common Screen Elements in a Notebook

Creating Paragraph

Interpreter Toolbar

Paragraph Settings Bar

Publishing a Notebook

Managing Results

4.1 Creating a NotebookTo create a notebook:

1. Navigate to the FCC Studio workspace.

2. Click Create in the upper-right corner.

The Create Notebook dialog box is displayed.

3. Enter the following details:

Table 1: Create Notebook

Field Description

Name Enter a name for the notebook.

The notebook name can be entered in the following format:

<Notebook Name>: A notebook is created in the current directory level.

<Directory Name> /<Notebook Name>: A notebook is created in a new directory within the current directory level.

Descrip-tion

Enter a description for the notebook.

Tags Enter keywords for the notebook. These keywords act as search tags to search the notebook.


Managing NotebooksImporting a Notebook

4. Click Create.

A new notebook is created and listed in the FCC Studio Workspace.

Figure 6: Notebook Page

To know more about the actions that can be performed in a notebook, see Common Screen Elements in a Notebook.

After creating a notebook, you can create Paragraphs in a notebook. For information on creating para-graphs, see Creating Paragraph.

4.2 Importing a NotebookThe Import Notebook feature enables you to import notebooks into your FCC Studio workspace. The file format supported for import is Data Studio Notebook (*.dsnb).

To import notebook(s) into the FCC Studio workspace, follow these steps:

1. Navigate to the FCC Studio Workspace.

2. Click the Import Notebooks icon in the upper-right corner.

Type Select the notebook type.

The notebook types are as follows:

Default (Zeppelin): Applies the look and feel of Apache Zeppelin where paragraphs can be resized and positioned next to each other.

Jupyter: Applies the look and feel of Project Jupyter where paragraphs are displayed in a single column.

Scenario: Use only when creating a behavior detection like scenario with parame-ters.

Table 1: Create Notebook

Field Description


Managing NotebooksExporting a Notebook

The Import Notebook(s) dialog box is displayed

3. Click Choose Files to browse and select the files from your local machine, or drag and drop the required files to upload.

A message is displayed at the bottom of the Import Notebook dialog box to indicate if the selected files are valid for import.

4. Click Import.

The notebooks are imported into the FCC Studio workspace.

4.3 Exporting a NotebookThe Export Notebook feature enables you to export notebooks from the FCC Studio workspace to your local machine. Notebooks are exported in the Data Studio Notebook (*.dsnb) format and are copied to the Downloads folder in the local machine. These files can be shared or imported.

You can either choose to export all the notebooks at once or export individual notebooks.

Exporting All Notebooks

Exporting Individual Notebooks

4.3.1 Exporting All Notebooks

The Export All Notebooks feature enables you to export all the notebooks from the FCC Studio work-space to your local machine.

To export all the notebooks:


2. Click the Export Notebooks icon in the upper-right corner.

The Export Notebooks dialog box is displayed.


Managing NotebooksDeleting a Notebook

3. Select the required Additional Settings in the Export Notebooks dialog box and click Export.

All the notebooks in the FCC Studio workspace are exported to your computer.

4.3.2 Exporting Individual Notebooks

To export an individual notebook:


2. Select the required notebook to export.

The selected notebook is opened.

3. Click the Export Notebook icon.

The notebook is exported to your computer.

4.4 Deleting a NotebookTo delete a notebook:


2. Click the Select Notebooks icon.

The check boxes are displayed for each notebook.

3. Select the required notebook(s), and click the delete icon.

The selected notebook(s) are deleted.

4.5 Common Screen Elements in a NotebookThe screen elements in a notebook are as follows:


Managing NotebooksCommon Screen Elements in a Notebook

Table 2: Common Screen Elements in a Notebook

Button Icon Action/Description

Modify Note-book

Modifies the details of a notebook, such as the name, descrip-tion, and/or tags.

Hide Code Hides or shows the Code Section in all the paragraphs in a notebook.

Hide Result Hides or shows the Results Section in all the paragraphs in a notebook.

Read-Only Sets the notebook to read-only mode.

NOTE:The notebook is protected from edit, clear result, delete, share, reset session, and run paragraphs in Read-only mode.

Write Sets the notebook to write mode.

Run Para-graphs

Executes all the paragraphs in a notebook in sequential order. For more information, see Running All Notebook Para-graphs.

You can view the results in various formats. For more informa-tion, see Managing Results.

Reset Session Resets any connection or code executed in a notebook.

Delete Note-book

Deletes a notebook.

Clear Result Clears results for all the paragraphs in a notebook.

NOTE: This action clears all the results. You must run the paragraphs again to view the results.

Clear Para-graph Dependen-cies

Remove all defined paragraph dependencies.


Managing NotebooksCreating Paragraph

4.6 Creating ParagraphA paragraph is a piece of code that can be executed to obtain the result. Paragraph offers a workbench to author code or query using interpreter-friendly scripting languages supported in FCC Studio.

Data scientists and analysts can use paragraphs to interactively explore financial crime data by author-ing queries and applying these queries on the financial crime data lake to fetch results in various for-mats. This enables them to rapidly discover and model financial crime patterns.

Paragraphs can be created using interpreters that are supported in FCC Studio. For more information on interpreters supported in FCC Studio, see Interpreter Toolbar. For information on configuring the interpreters, see Manage Interpreters.

To create a paragraph in a notebook:

1. Navigate to the Notebook page.

2. Hover the mouse above or below a paragraph and click on an icon in the Interpreter Toolbar to add a new paragraph.

Open as Iframe

Opens a notebook in Iframe. This allows a notebook to be embedded inside another webpage.

Share Note-book

Shares a notebook with another user, user group, or role.

Clone Note-book

Creates a copy of a notebook. All paragraphs in the current notebook are replicated in the new notebook.

The cloned notebook is created with the default name, Copy of <Current Notebook Name>.

Export Note-book

Exports a notebook to your computer as a DNSB file. For more information, see Exporting Individual Notebooks.

Layout Sets the preferred layout: Zeppelin or Jupyter.

Default Tem-plate

Applies the overall look and feel of the notebook using the default template. For more information, see Applying Tem-plate to a Notebook.

Default View Switches between Default, Simple, and Report views.

Show Panel Shows or hides the Paragraph Settings Bar Commands, Results Toolbar, and Settings Dialog for a selected paragraph in a panel to the right of the notebook.

Table 2: Common Screen Elements in a Notebook

Button Icon Action/Description


Managing NotebooksInterpreter Toolbar

A new paragraph is added with the selected interpreter. For more information on interpreters, see Interpreter Toolbar.

Each paragraph contains the following sections:

Title Section: Contains the user entered title of a paragraph. It is hidden by default.

Code Section: Contains a piece of text and/or programming code that can be independently executed.

Results Section: Displays the result of the executed code.

A paragraph invokes only one programming language and the language applied can differ from one paragraph to the next. Paragraph allows modularized code to be executed and examined independently of each other and the notebook as a whole. As the complexity increases in a note-book and workflow, this code modularity and independence are crucial.

For information on interpreters, see Interpreter Toolbar.

4.7 Interpreter ToolbarThe Interpreter Toolbar appears when the mouse is hovered above or below an existing paragraph. The toolbar contains icons associated with various Out-of-the-box interpreters. Selecting an interpreter icon automatically creates a new paragraph and populates the 1st line of code with the interpreter call as follows:

%<Interpreter>

The interpreters in the Interpreter Toolbar are as follows:

FCC Python

Spark



FCC JDBC

PGX-Java

FCC PySpark

PGQL

FCC ORE

Add Paragraph

JDBC

FCC Spark Scala

FCC Spark SQL

PySpark

Markdown

PGX-Algorithm

4.7.1 FCC Python

Use this icon to create a paragraph with an FCC Python interpreter. It is a Scientific language, simple to learn, and highly productive. Preferred for Machine Learning Prototyping as it contains a large number of packages available.

The interpreter call is as follows:

%fcc-python

4.7.2 Spark

Use this icon to create a paragraph with Spark interpreter.


%spark

println("Hello, world")

4.7.3 FCC JDBC

Use this icon to create a paragraph with an FCC JDBC interpreter. It performs the following:



Establish a connection between different database connections.

Run individual SQL queries against data held in a relational database management system (RDBMS) and use the obtained result for data visualization in various graph formats.


%fcc-jdbc

The FCC JDBC interpreter supports the following functions:

#help: This command lists the available custom functions of an interpreter.

fcc.printDatasets(): This command prints all the available datasets in a tabular form. It cannot be used in conjunction with any other code.

For example: fcc.printDatasets().

fcc.printGraphs(): This command prints all the available graphs in a tabular form. It cannot be used in conjunction with any other code.

For example: fcc.printGraphs()

fcc.getGraphDetails(code): This code retrieves the graph details in a tabular form. It cannot be used in conjunction with any other code.

For example: fcc.getGraphDetails("code")

fcc.loadGraph(code,graphtag[--optional,date]): This code loads the graph for a particular date in yyyy-mm-dd format. The return type is void, and should not be assigned to any variable.

For example: fcc.loadGraph("code","graphtag","date");

4.7.4 PGX-Java

Use this icon to create a paragraph with a PGX-Java interpreter.


%pgx-java

PgxGraph graph = session.readGraphWithProperties(dataSourceName, "graphName");

var program = session.getCompiledProgram("myAlgorithm");

var result = program.run(graph);

4.7.5 FCC PySpark

Use this icon to create a paragraph with an FCC PySpark interpreter. It is a Python code modified to work with Big Data. Spark is a tool to perform parallel computation with large datasets and it integrates well with Python.




%fcc-pyspark

4.7.6 PGQL

Use this icon to create a paragraph with PGQL (Property Graph Query Language) interpreter.

Graph pattern-matching query language is used with a property graph data model. Use this interpreter when executing individual PGQL queries.

For information on Property Graph Query Language (PGQL), see http://pgql-lang.org/


%pgql

4.7.7 FCC ORE

Use this icon to create a paragraph with an FCC ORE interpreter. It is used to create scripts for statistical, machine learning, and graphical analyses on data stored in the Oracle Database. The FCC Oracle R Enterprise (ORE) is integrated with Oracle Database. ORE can run any R package via embedded R while the database manages the data served to the R engines. This Interpreter is widely used among statisti-cians and data miners for statistical and data analysis use cases.


%fcc-ore

4.7.8 Add Paragraph

Use this icon to add a blank paragraph with no pre-defined interpreter call. Users can manually enter an interpreter call in the 1st line.

4.7.9 JDBC

Use this icon to create a paragraph with an JDBC interpreter.


%jdbc

-- Write your code here - e.g.: SELECT * FROM foo


http://pgql-lang.org/

http://pgql-lang.org/


4.7.10 FCC Spark Scala

Use this icon to create a paragraph with the FCC Spark Scala interpreter. It is an engineering language and does not provide many machine learning (ML) packages as Python.


%fcc-spark-scala

The FCC Spark Scala interpreter supports the following information:

#help: This command lists the available custom functions of an interpreter.

fcc.loadGraph(code,graphtag [--optional,date]): This command loads graph for a particular date in yyyy-mm-dd format. The return type is void and should not be assigned to any variable.

For example: fcc.loadGraph("code","graphtag","date");

fcc.saveGraphAs(graphtag, usertag): This command creates a snapshot of a graph against a new tab. The return type is void and should not be assigned to any variable.

For example: fcc.saveGraphAs("graphtag","usertag");

fcc.printGraphs(): This command prints all the available graphs in tabular form. It cannot be used in conjunction with any other code.

For example: fcc.printGraphs()

fcc.getGraphDetails(code): This command gets the graph details in a tabular form. It cannot be used in conjunction with any other code.

For example: fcc.getGraphDetails("code")

fcc.loadDataset(code): This command loads a particular dataset. It returns a DataFrame.

For example: var ds = fcc.loadDataset("code"))

fcc.loadDataset(code,date): This command loads dataset for a particular date in yyyy-mm-dd format. It returns a DataFrame.

For example: var ds = fcc.loadDataset("code","date"))

fcc.loadDataset(code,startDate,endDate): This command loads dataset for a specific time period with date in yyyy-mm-dd format. It returns a DataFrame.

For example: var ds = fcc.loadDataset("code","startDate","endDate"))

fcc.printDatasets(): This command prints all the available datasets in a tabular form. It cannot be used in conjunction with any other code.

For example: fcc.printDatasets()



4.7.11 FCC Spark SQL

Use this icon to create a paragraph with the FCC Spark SQL interpreter. It executes individual SQL que-ries against data held in a relational database management system (RDBMS) and uses the obtained result for data visualization in various graph formats.


%fcc-spark-sql

4.7.12 PySpark

Use this icon to create a paragraph with a PySpark interpreter.


%pyspark

print('Hello World')

4.7.13 Markdown

Use this icon to create a paragraph with a Markdown interpreter. It is a formatted free-text to describe subsequent paragraphs within a notebook.


%md

4.7.14 PGX-Algorithm

Use this icon to create a paragraph with a PGX-Algorithm.


%pgx-algorithm

import oracle.pgx.algorithm.PgxGraph;

import oracle.pgx.algorithm.annotations.GraphAlgorithm;


Managing NotebooksParagraph Settings Bar

@GraphAlgorithm

public class MyAlgorithm {

public void myAlgorithm(PgxGraph g) {

System.out.println("Hello World!");

}

}

4.8 Paragraph Settings BarThis section provides details of the elements in the Paragraph Settings Bar.

Table 3: Elements in Paragraph Settings Bar

Button/Icon Action/Description

Execute Paragraph Click this button to execute the code or query in a paragraph.

After execution, you can view the result in various formats. For more infor-mation, see Managing Results.

Enter Dependency Mode Click this button to add or remove dependent paragraphs.

Paragraphs with dependent paragraphs are executed in the dependency order.

For more information, see Paragraph Dependencies.

Comments Click this button to add comments to a paragraph.

Expand Click this button to expand a paragraph and view the paragraph in full-screen mode.

Show/Hide Line Numbers Click this button to show or hide line numbers in the code in a paragraph.

NOTE:This button is applicable only to the code section.

Visibility Click this button to manage the visibility settings in a paragraph. It controls how a paragraph can be viewed by the author and other users who have access to the notebook.


Managing NotebooksParagraph Settings Bar

4.8.1 Paragraph Dependencies

The Paragraph Dependencies feature allows you to add dependencies between paragraphs. The dependents of a paragraph are automatically executed after the original paragraph itself or any graph manipulation on the original paragraph is executed.

To create paragraph dependencies, follow these steps:

1. Click the Dependency icon in the Paragraph Settings Bar of a paragraph.

The Dependency Mode window is displayed.

2. Select or unselect paragraphs in order to add or remove them as dependents.

The order in which the paragraphs are selected appears as a number over the selected para-graphs. The number indicates the order in which the dependent paragraphs will be executed.

3. Click Save.

The changes are saved. Every time a paragraph is executed or graph actions are applied, its dependent paragraphs will be executed automatically.

4.8.2 Running All Notebook Paragraphs

You can run all the paragraphs in a notebook.

Settings Click this button to perform the following:

Resize the width of a paragraph.

Change the order of placement of the paragraphs by moving them up or down.

Clear the paragraph result.

Delete a paragraph.

Table 3: Elements in Paragraph Settings Bar



Managing NotebooksPublishing a Notebook

1. Click Run Paragraphs button in the Notebook Toolbar.

All the paragraphs will execute in order from top to bottom. If a paragraph was deleted during the Run Paragraphs job execution, it is ignored and paragraph execution continues for the rest of the paragraphs.

4.9 Publishing a NotebookA notebook is modifiable by the author. When a notebook is published:

The original notebook is cloned and a published notebook is created.

Any changes made to the original notebook will have no impact on the published notebook.

Whenever the original notebook is re-published, a new version of the published notebook is cre-ated.

The published notebook is in a read-only format.

The published notebook can be run in a batch pipeline.

4.9.1 Publishing a Non-Scenario Notebook

The non-scenario notebook is of Notebook Type, Default or Jupyter. Upon publishing an original note-book, you must select the user role or group to which the notebook will be published. After publishing, the original notebook is cloned and a published notebook is created.

4.9.1.1 Publishing a NotebookTo publish a non-scenario notebook, follow these steps:

1. Navigate to a Scenario Notebook detail page.

2. Click Publish Notebook button on the top left corner.

The Publish Notebook dialog box is displayed.

3. Click Publish.

The notebook is published and a confirmation message is displayed to indicate that the note-book is published.

4.9.2 Publishing a Scenario Notebook


Managing NotebooksPublishing a Notebook

The scenario notebook is of Notebook Type, Scenario. For scenario notebooks, the publish functional-ity provides four eyes approval process.

When a scenario notebook is published, the published notebook is shared with the user who is mapped to the DSBATCHGRP group for approval.

when a notebook is approved by the batch user:

The original notebook is cloned and a published notebook is created.

Scenario metadata is created.

A threshold set is created with values for all the parameters that you have provided in the note-book.

The approved scenario notebook can be executed with any threshold set which has been created while the notebook is being approved by the batch user. Whenever a user wants to create a new threshold set, the notebook has to be re-published with different threshold values. Once a notebook is approved, a new threshold set is created for the same scenario.

To perform batch execution of the published scenario notebook, follow these steps:

1. Navigate to the <Studio_home>/ficdb/bin directory.

2. Run from the terminal using the following:

./FCCM_Studio_NotebookExecution.sh "notebookID" "null" "scenarioID" "thresstoresetID" "null"

This section includes the following

Publishing a Notebook

Approving a Notebook

4.9.2.1 Publishing a NotebookTo publish scenario notebook, follow these steps:

1. Navigate to a Scenario Notebook page.

2. Click Publish Notebook button on the top left corner.

The Publish for Approval dialog box is displayed with the Parameter Keys and the correspond-ing Parameter values added to the paragraphs.

3. Click Publish.

The Scenario Notebook is published for approval and listed in the Notebooks page with the "For Approval" tag. The published scenario notebook is shared to the user mapped to the DSBATCH-GRP group in OFSAA, with the tag, "For Approval".

NOTE Ensure parameters with the same name must have the same val-ues


Managing NotebooksManaging Results

4.9.2.2 Approving a NotebookTo approve a notebook, follow these steps:

1. Log in to FCC Studio application as DSBATCHGRP user.

2. Navigate to the Scenario Notebook page, that you want to approve.

3. Click Approve Notebook button on the top left corner.

The Approve Notebook dialog box is displayed.

4. Click Approve.

A confirmation message is displayed to indicate that the notebook is approved.

The following scenario and threshold tables are updated in the BD Atomic Schema:

KDD_SCNRO

For an approved notebook, a scenario record is created in the KDD_SCNRO table and the col-umns scnro_id and cntry_id are updated with the values, ML and, customer focus value (113000004) respectively.

KDD_TSHLD_SET

KDD_TSHLD

For an approved notebook, the parameters are captured in the KDD_TSHLD table. Publishing multiple notebooks creates multiple threshold sets in the KDD_TSHLD table.

SCNRO_NB_PUBLISH

4.10 Managing Results Paragraph Results

Graph Results

4.10.1 Paragraph Results

After the execution of a paragraph, the result is displayed in the Results section.



This section contains the following topics:

Result Toolbar

Results Search Filter

Customizing Paragraph Result Settings

4.10.1.1 Result ToolbarThe details of the various result formats supported in FCC Studio are given in Table 4.

Table 4: Result Formats in Studio


Table Chart Click this button to view result in tabular format.

Area Chart Click this button to view the result in the area chart format.

Bar Chart Click this button to view the result in bar chart format.

Funnel Chart Click this button to view the result in the funnel chart format.

Line Chart Click this button to view the result in the line chart format.

Pie Chart Click this button to view the result in the pie chart format.

Pyramid Chart Click this button to view the result in the pyramid chart for-mat.

TreeMap Click this button to view the result in the tree map format.



4.10.1.2 Results Search Filter

Available only in Table Format. Instantly searches for an entered value in the results.

4.10.1.3 Customizing Paragraph Result SettingsTo customize the paragraph result format:

1. Navigate to the Notebooks page.

2. Click the required result format for a paragraph in the Result section and then click the Settings icon:

The Settings window is displayed and contains the following category:

General

Visualization

Text

Sunburst Click this button to view the result in the sunburst chart for-mat.

Tag Cloud Click this button to view the result in the tag cloud chart for-mat.

Box Plot Click this button to view the result in the box plot chart for-mat.

Text Click this button to view the result in text format.

Settings Click this button to customize the results based on the selected format.

Enter the required values for the General, Visualization, and Text settings.

Download As Click this button to download the result in the following for-mat:

Raw: Available for all formats.

SVG Format: Available for Graph and Visualization formats.

Table 4: Result Formats in Studio




3. Select a category and enter the required values for that category.

The result is customized as per the entered values.

4.10.2 Graph Results



This section contains the following topics:

Customizing Graph Result Settings

Graph Manipulation

Manipulation ToolBar

4.10.2.1 Customizing Graph Result SettingsTo customize the graph result format:

1. Navigate to the Notebooks page.

2. Click the required result format for a graph in the Result section and then click the Settings icon:

The Settings window is displayed and contains the following category:

General

Visualization

Highlights



3. Select a category and enter the required values for that category.

The result is customized as per the entered values.

4.10.2.2 Graph ManipulationThe Manipulation Toolbar is visible only when Graph Visualization is selected. This toolbar allows users to interact with the loaded graphs.

4.10.2.3 Manipulation ToolBar



This section provides details of the elements in the Manipulation Toolbar.

Table 5: Elements in Manipulation Toolbar


Drop Click this button to remove selected vertices from the graph view.

Group Click this button to group selected vertices into a super vertex.

Ungroup Click this button to ungroup a super vertex.

Expand Click this button to fetch n-hop neighbors of selected vertices.

Focus Click this button to shifts focus of the graph view; drop every-thing and fetch n-hop neighbors of selected vertex.

Undo Click this button to undo the last performed action.

Redo Click this button to redo the last performed action.

Reset Click this button to reset the graph view into its default state.


Managing Out of the Box NotebooksOut of the Box Notebooks

5 Managing Out of the Box Notebooks

5.1 Out of the Box NotebooksThe FCC Studio application is packaged with the following default Notebooks:

5.1.1 RMF Account Scenario

The RMF Account notebook contains the Rapid Movements of Fund (RMF) - Account Focus scenario. The scenario logic is defined in the Oracle SQL query. This also shows the capabilities to visualize the data at every data point.

This section includes the following topics:

Scenario Objective

Alert Generation

Sample JDBC Scenario

5.1.1.1 Scenario ObjectiveMoney launderers typically move funds between accounts to help integrate the funds and give the appearance of legitimacy. One possible indication of money laundering activity is the rapid movement of funds in and out of an account.

The scenario detects new accounts and more seasoned accounts that move Electronic Funds Transfer (EFT) transactions in and out of an account or accounts within a specified Lookback Period. The sce-nario can take into account the amount or velocity of funds through the account relative to the account balance or net worth.

Table C–1

Notebook Name Description

Graph_Alive In an Investigation Hub notebook, the graph is lost whenever a session is reset and this occurs as part of the session clean-up. You must execute the Graph_Alive notebook to retain the link to the graph even when a session is reset.

NOTE:Ensure to execute the Graph_Alive notebook after each time you start/restart the PGX service. For more information, see Installing PGX Service section in the Oracle Financial Services Crime and Compliance Studio Administration Guide.

HRG Scenario - AC Focus The notebook contains the High-Risk Geography scenario logic defined in Scala and Spark SQL.

RMF Account (sql) The notebook contains the Rapid Movements of Fund (RMF) - Account sce-nario. The scenario logic is defined in the Oracle SQL query.

RMF Scenario - AC Focus The notebook contains the Rapid Movements of Fund (RMF) - Account Focus scenario. The scenario logic is defined in the Oracle SQL query.

RMF Scenario - CU Focus The notebook contains the Rapid Movements Of Fund (RMF) - Customer Focus scenario. The scenario logic is defined in Scala and Spark SQL.


https://docs.oracle.com/cd/E91852_01/technicalguides.htm




5.1.1.2 Alert GenerationScenarios involve using some predetermined threshold values against which customer behaviors are compared. When the scenario meets the defined threshold value, alerts are generated.

Different thresstores can be applied to new accounts and seasoned accounts for alert generation. A defined threshold, Open Days, can be used to decide whether an account is to be depicted as new or seasoned. For the Account-focused scenario, the account open date of the focal account is used to decide whether the focal account is new or seasoned.

This scenario determines the total amount of incoming and outgoing EFT transactions made by the focal entity within the Lookback Period and produces alerts for new accounts in certain cases.

5.1.1.3 Sample JDBC ScenarioYou can run the RMF Account scenario using the JDBC Interpreter. This interpreter uses Oracle (RDBMS) as the source and target database to create the required temporary tables.

Temporary tables are used in the scenario development process. The result obtained from various combinations of these table data is used in alert generation. For information on temporary tables, see Data Elements.

The temporary tables are given as input to the Create Event API to generate alerts based on the defined threshold values. For information on the Create Event API, see Appendix 8, "Create Event API". The alerts are populated in the event tables. For information on the event tables, see Event Tables.

This section includes the following topics:

Data Elements

Tips to Create Temporary Tables

List of Temporary Tables

Table 1 Details

Table 2 Details

Event Tables

5.1.1.3.1 Data Elements

The data elements are the columns in the temporary tables that store the data temporarily.

The data elements are grouped in the form of database tables.

Some data elements are mandatory or fixed, and some are variables that vary from one scenario to another.

The table name can be an arbitrary value and the column names for the fixed data elements must be as per the column names specified in Table 1 Details and Table 2 Details.

Elements that are specified as the threshold in a scenario must be prefixed with ACT_ or TH_ for the Actual or Threshold values respectively.

5.1.1.3.2 Tips to Create Temporary Tables

1. Ensure to prefix or suffix the table name with keywords of the abbreviation of the scenario. For example, RMF_<Table_Name>. This helps to differentiate the tables created for different scenar-ios.

2. Indexes can be created on a temporary table immediately after the table creation for faster exe-cution of queries.



5.1.1.3.3 List of Temporary Tables

Running the sample RMF Account scenario creates the following temporary tables in the following sequence:

1. RMF_ACCT: This temporary table stores account-related records. The SQL query is provided to populate this table based on filter conditions.

2. RMF_WIRE_TRXN: This temporary table stores wired transaction-related records. The SQL query is provided to populate this table based on filter conditions.

3. RMF_CASH_TRXN: This temporary table stores cash transaction-related records. The SQL query is provided to populate this table based on filter conditions.

4. RMF_MI_TRXN: This temporary table stores MI transaction-related records. The SQL query is provided to populate this table based on filter conditions.

5. RMF_BACK_OFFICE_TRXN: This temporary table stores back-office transaction-related records. The SQL query is provided to populate this table based on filter conditions.

6. RMF_ALL_TRXN: This temporary table stores the consolidated data obtained from the transac-tions performed in Step 2, Step 3, Step 4, and Step 5.

The wired transaction is categorized into originator, secondary originator, beneficiary, and sec-ondary beneficiary. The MI transactions are categorized into remitter, beneficiary, and secondary beneficiary. These details are stored in the RMF_ALL_TRXN table.

7. RMF_TRXN_ACT: This temporary table stores the aggregated transactions for each account.

The data such as total debit transaction count, total credit transaction count, total credit amount, and the debit amount for each account that is created in Step 6 is obtained from the RMF_ALL_TRXN table and inserted into the RMF_TRXN_ACT table after aggregation.

8. RMF_FINAL_TRXN_ACT: This table stores mandatory data elements such as data origin, focus type, jurisdiction, business domain, and scenario ID. The combined data from the RMF_TRX-N_ACT and RMF_ACCT tables are inserted into this table.

9. RMF_FINAL_TRXN_ACT_DS: This table stores high-risk, medium-risk, and low-risk alerts that are processed from the RMF_FINAL_TRXN_ACT table based on the threshold filter condition. For more information, see Table 1 Details.

10. RMF_TRXN: This temporary table stores data of all the transactions from the RMF_ALL_TRXN table. For more information, see Table 2 Details.

11. Call the Create Event API by passing the tables that are created in steps 9 and 10. For more infor-mation, see Appendix 8, "Create Event API".

The Create Event API uses input from the tables created in steps 9 and 10 to generate alerts. The alerts are populated in the event tables. For more information on event tables, see Event Tables.

12. After the successful generation of alerts, drop all the temporary tables.

5.1.1.3.4 Table 1 Details

Table 1 contains information related to the direct focus. This information is aggregated for focus. For example, the account number and the total transaction amount for that account will be stored in Table 1. Here, one record is inserted for each focus (account or customer).



Table 6: Column Details for Table 1

Column Name Sample Values

Description

V_FOCUS_TYPE ACCOUNT The main focus of the scenario. The value can be obtained from the kdd_dataset_base table.

V_ENTITY_NAME ANDERSON Name of the focused entity, that is, account display name and cus-tomer display name.

V_DATA_ORIGIN AMLBIG Data origin, that is, MAN, DLY and so on.

V_STATUS_CD NEW Event status code.

Default value: New.

D_EVENT_CREAT-ED_DATE

3/11/2019 15:02

Event creation date.

V_JURISDIC-TION_CD

AMEA Jurisdiction.

V_BUSINESS_DO-MAIN_CD

a Business domain.

V_COMMENTS General comment for the scenario.

V_SCENARIO_-CLASS

AML Class to which the scenario belongs to, that is, AML, TC, and BC.

V_FOCUS_CD ACMLTER-RORFIN-FAC-005

Code for focus, that is, account internal ID in case of account.

ACCT_DSPLY_NM ANDERSON Name of the focused entity, that is, account display name and cus-tomer display name.

V_ENTITY_CD 832 Focus sequence ID, that is, account sequence ID in case of account focus.

MAX_-DATA_DUMP_DT

12/10/2015 Data Dump date for which business data is involved.



MAX-_NOT_EFT_TRANS

0 Specific for an account. This column can be ignored for other sce-narios.

TOT_TRXN_AMT 10500

TOT_TRXN_CNT 2

EFFECTIVERISK 9

ACTIVITYRISK 10

RISK_CATEGORY HR

ACCT_TYPE Seasoned

TRUSTED_PRCTG 0

PASS_THRU_PRCTG 0

LRF_PRCTG 0

HR_PRCTG 0

ACT_TOT_CRED-IT_TRXN_AMT

5400 Threshold specific for an account. It can be different for other sce-narios.

TH_TOT_MIN_-CREDIT_TRXN_AMT

50

TH_TOT_MAX_-CREDIT_TRXN_AMT

10000000

ACT_TOT_CRED-IT_TRXNCT

2

TH_TOT_MIN_-CREDIT_TRXNCT

1

TH_TOT_MAX_-CREDIT_TRXNCT

20

ACT_TOT_DEB-IT_TRXNCT

2

TH_-TOT_MIN__DEB-IT_TRXNCT

1

TH_TOT_MAX_DEB-IT_TRXNCT

20

ACT_TOT_DEB-IT_TRXN_AMT

5100

TH_MIN_DEB-IT_TRXN_AMT

20

REMARK Remark for a scenario.



Description



5.1.1.3.5 Table 2 Details

Table 2 contains information on all the transactions involved in alert generation.

5.1.1.3.6 Event Tables

The Create Event API must run successfully to generate alerts. These alerts are populated in the follow-ing event tables:

fcc_am_events

SCENARIO_CD 10000 Scenario ID can be any number. The value is updated by the Create Event API by actual scenario ID which is generated during publish-ing.

SCENARIO_MN RMF Account(sql)

Name of scenario notebook.

N_RUN_ID 84 The Create Event API automatically creates this value.

N_EVENT_CD 366

V_ENTITY_CD 25291 Transaction sequence ID.

V_FOCUS_CD ACML-NOAAC-302

Account Internal ID in case of account focus.

N_ENTITY_ID FOML-NOAAC-301

Transaction Internal ID.

TRXN_DATAD-UMP_DT

12/10/2015 Transaction Data Dump date.

TRXN_PRDCT_TYPE WIRE_TRXN Transaction Product type. The value can be obtained from the kdd_-dataset_base table.


Columns Sample Values Description

V_ENTI-TY_CD

25291 Transaction sequence ID.

V_FO-CUS_CD

ACMLNOAAC-302 Account Internal ID in case of account focus.

N_ENTITY_ID FOMLNOAAC-301 Transaction Internal ID.

TRXN_DATA-DUMP_DT

12/10/2015 Transaction data dump date

TRX-N_PRDCT_-TYPE

WIRE_TRXN Transaction Product type. The value can be taken from the kdd_data-set_base table.



Description



fcc_am_event_binding

fcc_am_event_details

fcc_am_event_entity_map


Managing GraphsCreating Graphs

6 Managing GraphsIn FCC Studio, you can load graphs from external sources or create custom graphs. Using PGX, you can load multiple graphs into a notebook and create PGQL queries against different graphs. The result obtained from running a paragraph in a notebook can be used as an input to other paragraphs in the notebook. The results of analytics algorithms are stored as transient properties of nodes and edges in the graph. Pattern matching can then be used against these properties.

For information on configuring data sources for graphs, see the Configuring Data Sources for Graph section in the OFS Crime and Compliance Studio Administration and Configuration Guide.

For information on the Oracle Financial Crime Graph Model, see Oracle Financial Crime Graph Model.

6.1 Creating GraphsTo create a graph, follow these steps:


2. Click the menu icon in the upper-left corner.

The menu items are listed.

3. Click Graphs.

The Graphs page is displayed.

Figure 7: Graphs Page

4. Click Create a Graph.

The Create new Graph Configuration dialog box is displayed.

5. Click the Plain Mode icon on the left.

6. Enter the Name for the graph.

7. Enter the JSON Configuration as shown in the following example:

{





"vertex_labels": false,

"edge_label": true,

"loading": {

"load_edge_label": true

},

"date_format": "yyyy-MM-dd HH:mm:ss",

"vertex_props": [

{

"type": "string",

"name": "type"

},

{

"type": "string",

"name": "religion"

},

{

"type": "string",

"name": "company"

},

{

"type": "string",

"name": "musicGenre"

},

{

"type": "string",

"name": "show"

},

{

"type": "string",

"name": "name"

},

{

"type": "string",

"name": "country"

},

{



"type": "string",

"name": "team"

},

{

"type": "string",

"name": "genre"

},

{

"type": "string",

"name": "occupation"

},

{

"type": "string",

"name": "role"

}

],

"edge_props": [

{

"type": "float",

"name": "weight"

}

],

"format": "edge_list",

"vertex_id_type": "integer",

"attributes": {},

"header": "",

"uri": "http://pgx.us.oracle.com/graphs/connections.edge_list",

"separator": "\t "

}

8. Click Create.

A graph configuration is created. This newly created graph configuration can be used in a note-book for the following:

Load a graph using the PGX interpreter.

To load a graph, create a notebook and a paragraph with a PGX interpreter. Enter the code format given in the following example:

graph = session.readGraphWithProperties(dataSourceName, 'graphName')

Here, dataSourceName refers to the graph name that you have created.



Query a graph using the PGQL interpreter.

To query a graph, create a notebook and create a paragraph with a PGQL interpreter. Enter the code format given in the following example:

SELECT n,e,m FROM GRAPH_NAME MATCH (n) -[e]-> (m)

Here GRAPH_NAME refers to the graph name that you have created.


Managing TemplatesCreating a Template

7 Managing TemplatesThe FCC Studio offers different formats to view the result after the execution of a Paragraph. Templates enable you to define parameters to customize the result formats. You can customize the visualization of the result by defining parameters in a template and then applying that template to a notebook. The customized parameters in the template are applied to the result format in the notebook.

This chapter includes the following topics:

Creating a Template

Updating a Template

Applying Template to a Notebook

7.1 Creating a TemplateTo create a template, follow these steps:


2. Click the menu icon on the upper-left corner.

The menu items are listed.

3. Click Templates.

The Templates page is displayed.

Figure 8: Templates Page

4. Click Create Template.

The Create Template dialog box is displayed.

5. Enter the Name for the template.

6. Click Create.

A new template is created and listed on the LHS. The details of the template are displayed on the RHS.

7. Select the required result format icon on the RHS to define parameter values for that format.


Managing TemplatesUpdating a Template

8. Enter the required values. For every result format in a template, you can define values for the General, Visualization, and Text parameters.

9. Click Update.

A template is created with the defined parameters.

7.2 Updating a TemplateTo update an existing Template:

1. Navigate to the Templates page.

2. Select the template that you want to update from the list displayed on the LHS.

The details of the selected template are displayed on the RHS.

3. Modify the required values for the General, Visualization, and Text parameters.

4. Click Update.

The template is updated.

7.3 Applying Template to a NotebookTo apply a template to a Notebook:

1. Navigate to the Notebook page to which you want to apply a template.

2. Click the following icon in the upper-right corner.

The available templates are listed.

3. Select the required template that you want to apply to the notebook.

The selected template is applied to the notebook.



Create Event API

8 Create Event API The Create Event API is a collection of DB program units. This API accepts inputs from two tables to generate alerts that are populated in the event tables.

The syntax to call the Create Event API is as follows:

SELECT FUNC_CREATE_EVENT(<Table_1>,<Table_2>) FROM DUAL;

For information on Table_1 and Table_2, see Table 1 Details and Table 2 Details.

For information on Sample RMF Scenario, see Sample JDBC Scenario.