Oracle® Financial Services Crime and Compliance Studio · 2020-02-17 · 2 Getting Started...

Oracle® Financial Services Crime and Compliance StudioUser Guide

Release 8.0.7.2.0

E91355-01

February 2020

User Guide, Release 8.0.7.2.0

E91355-01

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iii

Contents

Document Control........................................................................................................................................ vii

Preface ................................................................................................................................................................. ix

Summary ........................................................................................................................................................ ix

Audience......................................................................................................................................................... ix

Related Documents ........................................................................................................................................ ix

1 About Oracle Financial Services Crime and Compliance Studio

The Architecture of Crime and Compliance Studio ............................................................................... 1-2

Oracle Financial Crime Graph Model ..................................................................................................... 1-2

2 Getting Started

Accessing Crime and Compliance Studio Application ........................................................................... 2-5

FCC Studio Interface ................................................................................................................................. 2-6

3 Managing Notebooks

Creating Notebook ..................................................................................................................................... 3-9

Importing Notebook ................................................................................................................................ 3-10

Exporting Notebook ................................................................................................................................ 3-11

Exporting All Notebooks ................................................................................................................... 3-11

Exporting Individual Notebooks ........................................................................................................ 3-12

Deleting Notebook ................................................................................................................................... 3-12

Common Screen Elements in Notebook ................................................................................................ 3-12

Creating Paragraph ................................................................................................................................ 3-14

Interpreter Toolbar................................................................................................................................. 3-15

FCC Python........................................................................................................................................ 3-15

Spark .................................................................................................................................................. 3-16

FCC JDBC ......................................................................................................................................... 3-16

PGX-Java ........................................................................................................................................... 3-17

FCC Pyspark ...................................................................................................................................... 3-17

PGQL ................................................................................................................................................. 3-17

FCC ORE ........................................................................................................................................... 3-17

Add Paragraph.................................................................................................................................... 3-18

JDBC.................................................................................................................................................. 3-18

iv

FCC Spark Scala ................................................................................................................................ 3-18

FCC Spark SQL ................................................................................................................................. 3-19

Pyspark............................................................................................................................................... 3-19

Markdown .......................................................................................................................................... 3-19

PGX-Algorithm.................................................................................................................................. 3-20

Paragraph Settings Bar .......................................................................................................................... 3-20

Paragraph Dependencies .................................................................................................................... 3-21

Running All Notebook Paragraphs .................................................................................................... 3-22

Publishing a Notebook ............................................................................................................................ 3-22

Publishing a Non-Scenario Notebook................................................................................................ 3-22

Publishing Notebook................................................................................................................... 3-22

Publishing a Scenario Notebook ........................................................................................................ 3-23

Publish Notebook........................................................................................................................ 3-23

Approve Notebook...................................................................................................................... 3-24

Manage Results........................................................................................................................................ 3-24

Paragraph Results............................................................................................................................... 3-24

Result Toolbar............................................................................................................................. 3-25

Results Search Filter ................................................................................................................... 3-26

Customizing Paragraph Result Settings...................................................................................... 3-26

Graph Results ..................................................................................................................................... 3-28

Customizing Graph Result Settings ............................................................................................ 3-28

Graph Manipulation .................................................................................................................... 3-31

Manipulation ToolBar................................................................................................................. 3-31

4 Manage Out of the Box Notebooks

Out of the Box Notebooks ....................................................................................................................... 4-33

RMF Account Scenario...................................................................................................................... 4-33

Scenario Objective ...................................................................................................................... 4-33

Alert Generation ......................................................................................................................... 4-34

Sample JDBC Scenario............................................................................................................... 4-34

Data Elements...................................................................................................................... 4-34

Tips to Create Temporary Tables ........................................................................................ 4-34

List of Temporary Tables .................................................................................................... 4-35

Table 1 Details..................................................................................................................... 4-35

Table 2 Details..................................................................................................................... 4-37

Event Tables ........................................................................................................................ 4-38

5 Manage Graphs

Create Graphs ......................................................................................................................................... 5-39

6 Manage Templates

Create Template ...................................................................................................................................... 6-43

Update Template ..................................................................................................................................... 6-44

Apply Template to Notebook ................................................................................................................. 6-44

v

A Create Event API

................................................................................................................................................................... A-47

vii

Document Control

Version Number Revision Date Changes Done

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

8.0.7.1.0 Updated: October 2019

Updated the guide for 8.0.7.1.0 release.

8.0.7.2.0 Updated: February 2020

Updated the guide for 8.0.7.2.0 release.

ix

Preface

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

AudienceThis guide is intended for end-users such as Data Analysts and Data Scientists.

The basic knowledge of the following is recommended:

• UNIX commands

• Database concepts

• Big Data

• Python

• Scala

• Spark

• R

• SQL

• Groovy

• Markdown

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/

1

About Oracle Financial Services Crime and Compliance Studio 1-1

1About Oracle Financial Services Crime and Compliance Studio

This chapter provides complete functional details about Oracle Financial Services Crime and Compliance Studio application.

This chapter 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 StudioIn order to effectively monitor anti-money laundering and anti-fraud programs in financial institutions, the most challenging need 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 Studio to interactively explore financial crime data and gain insights into new and emerging financial crime patterns and trends.

The key features of Studio include the following:

• Provide an integrated and comprehensive analytics toolkit designed to rapidly discover and model new financial crime patterns.

• Interact 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 pre-defined 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, in order 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

• Engineered to work with Apache Spark, the most prevalent analytics engine on Big Data

• Engineered to work 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

The Architecture of Crime and Compliance Studio

1-2 Oracle Financial Services Crime and Compliance Studio User Guide

• Embedded with highly scalable in-memory Graph Analytics Engine (PGX)

• Enterprise-ready with underlying OFSAA frameworks

• Engineered to work 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 mash-up Studio data with third-party data for discovery and modeling

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

Figure 1–1 Crime and Compliance Studio Architecture

Oracle Financial Crime Graph ModelThe 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.

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

Oracle Financial Crime Graph Model

About Oracle Financial Services Crime and Compliance Studio 1-3

Figure 1–2 Oracle Financial Crime Graph Model

For information on the node and edge properties of the Oracle Financial Crime Graph Model, see Data Model Guides.

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

Oracle Financial Crime Graph Model


2

Getting Started 2-5

2Getting Started

This section includes the following topics:

• Accessing Crime and Compliance Studio Application

• FCC Studio Interface

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

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

https://<Host_Name>:<Port_Number>

Here <Port_Number> is,

• 7008 for Studio installed on-premise.

• 30078 for Studio deployed on the Kubernetes cluster.

The Crime and Compliance Studio application login page is displayed.

Figure 2–1 Crime and Compliance Studio Login Page

2. Log in with the Username and Password.

FCC Studio Interface


3. Click Login.

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

Figure 2–2 Crime and Compliance Studio Landing Page

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

• Studio Workspace: The landing page that is displayed after logging into the FCC Studio application. 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 2–3 Menu Items

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


Getting Started 2-7

• Notebook Search Filter: Enter the required 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 operation, such as delete notebooks.

Upon clicking this icon, check boxes are displayed for 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.

Clicking the button opens a dialog with the following iframe 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 settings dialog is opened. This behavior can be disabled as well by un-checking the 'Save Settings' check box on the dialog.

3

Managing Notebooks 3-9

3Managing Notebooks

A 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 languages, 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 Notebook

• Importing Notebook

• Exporting Notebook

• Deleting Notebook

• Common Screen Elements in Notebook

• Creating Paragraph

• Interpreter Toolbar

• Paragraph Settings Bar

• Publishing a Notebook

• Manage Results

Creating NotebookTo create a notebook:

1. Navigate to the Studio workspace.

2. Click Create in the upper-right corner.

The Create Notebook dialog box is displayed.

3. Enter the following details:

Table 3–1 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.

Description Enter a description for the Notebook.

Tags Enter keywords for the Notebook. These keywords act as search tags using which a Notebook can be searched.

Type Select the type for the notebook.

The type of notebooks 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 parameters.

Importing Notebook


4. Click Create.

A new Notebook is created and listed in the Studio Workspace.

Figure 3–1 Notebook Page

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

After creating Notebook, you can create Paragraphs in a Notebook. For information on creating paragraphs, see Creating Paragraph.

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

To import notebook(s) into Studio workspace:

1. Navigate to the Studio Workspace.

Exporting Notebook


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

The Import Notebook(s) dialog box is displayed

3. Click the Choose Files field to browse and select files from your local machine, or drag and drop 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 Studio workspace.

Exporting NotebookExport notebook feature enables you to export notebooks in Studio workspace to your local machine. Notebooks are exported in Data Studio Notebook (*.dsnb) format and are downloaded 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

Exporting All NotebooksExport All Notebooks enables you to export all the notebooks in the Studio workspace to your local machine.

To export all notebooks:


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

The Export Notebooks dialog box is displayed.

Deleting Notebook


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

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

Exporting Individual NotebooksTo export individual notebooks:


2. Click the required notebook to export.

The selected notebook is opened.

3. Click the Export Notebook icon.

The notebook is exported to your computer.

Deleting Notebook1. Navigate to the Studio workspace.

2. Click the Select Notebooks icon.

The check boxes are displayed for notebooks.

3. Select the required notebooks, and click the delete icon.

The selected notebooks are deleted.

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

Table 3–2 Common Screen Elements in Notebook

Button Icon Action/Description

Modify Notebook

Click this button to modify the details of a notebook such as the name, description and/or tags.

Hide Code Click this button to hide or show the Code Section in all the paragraphs in a notebook.

Common Screen Elements in Notebook


Hide Result Click this button to hide or show the Results Section in all the paragraphs in a Notebook.

Read Only Click this button to set the notebook to Read-only mode.

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

Write Click this button to set the notebook to Write mode.

Run Paragraphs Click this button to execute all the paragraphs in a notebook in sequential order. For more information, see Running All Notebook Paragraphs.

You can view the results in various formats. For more information, see Manage Results.

Reset Session Click this button to reset any connection or code executed in a notebook.

Delete Notebook Click this button to delete a notebook.

Clear Result Click this button to clear results for all the paragraphs in a notebook.

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

Clear Paragraph Dependencies

Click this button to remove all defined paragraph dependencies.

Open as Iframe Click this button to open a notebook in iFrame. This allows a notebook to be embedded inside another webpage.

Share Notebook Click this button to share a notebook with another user, user group, or role.

Clone Notebook Click this button to create 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 Notebook

Click this button to export a notebook to your computer as a DNSB file. For more information, see Exporting Individual Notebooks.

Click this button to set the preferred layout, Zeppelin or Jupyter.

Default Template

Click this button to apply the overall look and feel of the notebook using the default template. For more information, see Apply Template to Notebook.



Creating Paragraph


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 various interpreter friendly scripting languages supported in Studio.

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

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

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

Default View Click this button to switch between Default, Simple, and Report views.

Show Panel Click this button to show or hide the Paragraph Settings Bar Commands, Results Toolbar and Settings Dialog for a selected paragraph in a panel to the right of the notebook.



Interpreter Toolbar


Each paragraph contains the following sections:

• Title Section: Contains the user entered the 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 for modularized code to be executed and examined independently of each other and the notebook as a whole. As the complexity increases in a notebook and workflow, this code modularity and independence are crucial.

For information on interpreters, see Interpreter Toolbar.

Interpreter ToolbarThe Interpreter Toolbar appears when the mouse is hovered above or below an existing paragraph. The toolbar contains icons associated with various OOB 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

FCC PythonUse this icon to create a paragraph with an FCC Python interpreter. It is considered 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

Interpreter Toolbar


SparkUse this icon to create a paragraph with Spark interpreter.


%spark

println("Hello, world")

FCC JDBCUse 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 obtains 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 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");

Interpreter Toolbar


PGX-JavaUse 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);

FCC PysparkUse this icon to create a paragraph with an FCC Pyspark interpreter. It is a Python code modified to work with Big Data. A Spark is a tool for performing parallel computation with large datasets and it integrates well with Python.


%fcc-pyspark

PGQLUse 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), refer the following links:

http://pgql-lang.org/


%pgql

FCC OREUse 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 Oracle Database. The FCC ORE is integrated with Oracle Database, Oracle R Enterprise 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 statisticians and data miners for statistical and data analysis use cases.


%fcc-ore

http://pgql-lang.org/

Interpreter Toolbar


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

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


%jdbc

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

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


%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()

Interpreter Toolbar


• 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()

FCC Spark SQLUse this icon to create a paragraph with the FCC Spark SQL interpreter. It executes individual SQL queries 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

PysparkUse this icon to create a paragraph with a Pyspark interpreter.


%pyspark

print('Hello World')

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


%md

Paragraph Settings Bar


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


%pgx-algorithm

import oracle.pgx.algorithm.PgxGraph;

import oracle.pgx.algorithm.annotations.GraphAlgorithm;

@GraphAlgorithm

public class MyAlgorithm {

public void myAlgorithm(PgxGraph g) {

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

}

}

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

Table 3–3 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 information, see Manage 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.

Paragraph Settings Bar


Paragraph DependenciesThe 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 paragraphs. The number indicates the order in which the dependent paragraphs will be executed.

3. Click Save.

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 may be viewed by the author and other users who have access to the 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 3–3 Elements in Paragraph Settings Bar


Publishing a Notebook


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

Running All Notebook ParagraphsYou can run all the paragraphs in 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.

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 created.

• The published notebook is in a read-only format.

• The published notebook can be run in a batch pipeline.

Publishing a Non-Scenario NotebookThe non-scenario notebook is of Notebook Type, Default or Jupyter. Upon publishing an original notebook, 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.

Publishing 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.

Publishing a Notebook


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

Publishing a Scenario NotebookThe scenario notebook is of Notebook Type, Scenario. For scenario notebooks, the publish functionality 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 notebook.

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" "thresholdsetID" "null"

This section includes the following

• Publish Notebook

• Approve Notebook

Publish 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 corresponding Parameter values added to the paragraphs.

Note: Ensure parameters with the same name must have the same values.

3. Click Publish.

Manage Results


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 DSBATCHGRP group in OFSAA, with the tag, "For Approval".

Approve NotebookTo approve a notebook, follow these steps:

1. Log in to 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 columns 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

Manage Results• Paragraph Results

• Graph Results

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

Manage Results


This section contains the following topics:

• Result Toolbar

• Results Search Filter

• Customizing Paragraph Result Settings

Result ToolbarThe details of the various result formats supported in Studio are given in Table 3–4.

Table 3–4 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.

Manage Results


Results Search FilterAvailable only in Table Format. Instantly searches for an entered value in the results.

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:

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 format.

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

Sunburst Click this button to view the result in the sunburst chart format.

Tag Cloud Click this button to view the result in the tag cloud chart format.

Box Plot Click this button to view the result in the box plot chart format.

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 format:

• Raw: Available for all formats.

• SVG Format: Available for Graph and Visualization formats.

Table 3–4 Result Formats in Studio


Manage Results


The Settings window is displayed and contains the following category:

• General

• Visualization

• Text

Manage Results


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

The result is customized as per the entered values.

Graph ResultsThis section contains the following topics:

• Customizing Graph Result Settings

• Graph Manipulation

• Manipulation ToolBar

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

Manage Results


Manage Results


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

The result is customized as per the entered values.

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

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

Table 3–5 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 everything 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.

Manage Results


4

Manage Out of the Box Notebooks 4-33

4Manage Out of the Box Notebooks

Out of the Box NotebooksCrime and Compliance Studio application comes with the following default Notebooks:

Table 4–1

Notebook Name Description

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 scenario. 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> The scenario logic is defined in Scala and Spark SQL.

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


• Scenario Objective

• Alert Generation

• Sample JDBC Scenario

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 both 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 scenario can take into account the amount or velocity of funds through the account relative to the account balance or net worth.

Out of the Box Notebooks


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 thresholds may be applied to new accounts and seasoned accounts for alert generation. A defined threshold, Open Days, may 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.

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 A, "Create Event API". The alerts are populated in the event tables. For information on the event tables, see Event Tables.


• Data Elements

• Tips to Create Temporary Tables

• List of Temporary Tables

• Table 1 Details

• Table 2 Details

• Event Tables

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 and Threshold values respectively.

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 scenarios.



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

List of Temporary Tables

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

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

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

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

4. RMF_MI_TRXN: This temporary table holds 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 holds 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 holds the consolidated data obtained from the transactions performed in step 2, Step 3, step 4, and step 5.

The wired transaction is categorized into originator, secondary originator, beneficiary, and secondary 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 is used to store 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: The combined data from the RMF_TRXN_ACT and RMF_ACCT tables are inserted into this table. This table stores mandatory data elements such as data origin, focus type, jurisdiction, business domain, and scenario ID.

9. RMF_FINAL_TRXN_ACT_DS: This table is used to store 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 information, see Appendix A, "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.

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 4–2 Column Details for Table 1

Column NameSample 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 customer 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_CREATED_DATE

3/11/2019 15:02

Event creation date.

V_JURISDICTION_CD AMEA Jurisdiction

V_BUSINESS_DOMAIN_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 ACMLTERRORFINFAC-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 customer 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 scenarios.

TOT_TRXN_AMT 10500 Specific for an account. This column can be ignored for other scenarios.

TOT_TRXN_CNT 2 Specific for an account. This column can be ignored for other scenarios.

EFFECTIVERISK 9 Specific for an account. This column can be ignored for other scenarios.

ACTIVITYRISK 10 Specific for an account. This column can be ignored for other scenarios.

RISK_CATEGORY HR Specific for an account. This column can be ignored for other scenarios.

ACCT_TYPE Seasoned Specific for an account. This column can be ignored for other scenarios.

TRUSTED_PRCTG 0 Specific for an account. This column can be ignored for other scenarios.

PASS_THRU_PRCTG 0 Specific for an account. This column can be ignored for other scenarios.

LRF_PRCTG 0 Specific for an account. This column can be ignored for other scenarios.



Table 2 Details

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

HR_PRCTG 0 Specific for an account. This column can be ignored for other scenarios.

ACT_TOT_CREDIT_TRXN_AMT

5400 Actual Threshold, Specific for an account. It can be different for other scenarios.

TH_TOT_MIN_CREDIT_TRXN_AMT

50 Threshold, Specific for an account. It can be different for other scenarios.

TH_TOT_MAX_CREDIT_TRXN_AMT


ACT_TOT_CREDIT_TRXNCT


TH_TOT_MIN_CREDIT_TRXNCT


TH_TOT_MAX_CREDIT_TRXNCT


ACT_TOT_DEBIT_TRXNCT


TH_TOT_MIN__DEBIT_TRXNCT


TH_TOT_MAX_DEBIT_TRXNCT


ACT_TOT_DEBIT_TRXN_AMT


TH_MIN_DEBIT_TRXN_AMT


REMARK Remark for a scenario.

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 publishing.

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 The Create Event API automatically creates this value.

V_ENTITY_CD 25291 Transaction sequence ID.

V_FOCUS_CD ACMLNOAAC-302

Account Internal ID in case of account focus.

N_ENTITY_ID FOMLNOAAC-301

Transaction Internal ID.

TRXN_DATADUMP_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.


Column NameSample Values Description


Columns Sample Values Description

V_ENTITY_CD 25291 Transaction sequence ID.

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

N_ENTITY_ID FOMLNOAAC-301 Transaction Internal ID.

TRXN_DATADUMP_DT

12/10/2015 Transaction data dump date

TRXN_PRDCT_TYPE

WIRE_TRXN Transaction Product type. The value can be taken from the kdd_dataset_base table.



Event Tables

The Create Event API is run successfully to generate alerts. These alerts are populated in the following event tables:

• fcc_am_events

• fcc_am_event_binding

• fcc_am_event_details

• fcc_am_event_entity_map

5

Manage Graphs 5-39

5Manage Graphs

In Studio, you can either 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.

Create GraphsTo create graphs, 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.

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



Create Graphs


Figure 5–1 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"

},

{

Create Graphs

Manage Graphs 5-41

"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": [

Create Graphs


{

"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 notebook for the following:

• Load a graph using the pgx interpreter.

To load a graph, create a notebook and create 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.

6

Manage Templates 6-43

6Manage Templates

The Studio offers various formats in which you can 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:

• Create Template

• Update Template

• Apply Template to Notebook

Create 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.

Update Template

6-44 Oracle Financial Services Crime and Compliancet Studio User Guide

Figure 6–1 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. Click the required result format icon on the RHS to define parameter values for that format.

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

8. Enter the required values.

9. Click Update.

A template is created with the defined parameters.

Update TemplateTo update an existing Template:

1. Navigate to the Templates page.

2. Click 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.

4. Click Update.

The template is updated.

Apply Template to NotebookTo apply a template to a Notebook:

Apply Template to Notebook

Manage Templates 6-45

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. Click the required template that you want to apply to the notebook.

The selected template is applied to the notebook.

Apply Template to Notebook

6-46 Oracle Financial Services Crime and Compliancet Studio User Guide

A

Create Event API A-47

ACreate Event API

The Create Event API is a collection of DB program units. This API uses 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 and Table 1 Details and Table 2 Details.

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

Oracle® Financial Services Crime and Compliance Studio · 2020-02-17 · 2 Getting Started...

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Transcript of Oracle® Financial Services Crime and Compliance Studio · 2020-02-17 · 2 Getting Started...