Regulatory Reporting

Introduction

Maintainer: regardt_jacobs@bmc.com

In the banking, financial services, and insurance (BFSI) industry, regulatory reporting is a critical compliance function that involves the orchestration of multiple data pipeline steps. Control-M can be used to orchestrate the steps of data source retrieval, data collection, data storage, data processing, and data consumption.

Use Case Overview

The BFSI industry must adhere to strict regulatory requirements, necessitating accurate and timely reporting. For regulatory reporting, managing, processing, and automating the flow of data is crucial to ensure accuracy, compliance, and timely submission of reports. Using Control-M, you can streamline the entire process, from data collection and staging to processing and final reporting.

This use case involves orchestrating the following data pipeline steps using Control-M:

Data Source Retrieval
Data Collection, Processing, Storage
Data Consumption

The Consensus Recording for this use case can be found here: Watch this video!

Use Case Technical Explanation

Data Source Retrieval

Control-M schedules and automates the extraction of data from multiple data sources, like:

Core banking systems (e.g., Oracle FLEXCUBE)
Financial market data providers (e.g., Bloomberg, Reuters)
CRM systems (e.g., Salesforce)
Financial databases (e.g., Oracle, Microsoft SQL Server)

In the zzz-regulatory-reporting use case, there are 3 sub folders relevant to this Data Source Retrieval step; Commercial_Data which includes jobs designed to demonstrate an export of Incident Response data for a timeframe set out as per regulatory standard through a custom application script, Digital_Banking which includes a job designed to demonstrate an export of all service performance related data aggregated on a centralized database using the Control-M Database plug-in integrating into a MSSQL DB, and Global_Banking_Markets_Data which includes a job designed to demonstrate the watch and transfer of certification files critical in reporting to auditors around valid platform and system certifications including HR Systems and Databases onces uploaded.

Data Collection, Data Processing, and Data Storage

Once data is retrieved, Control-M orchestrates data consolidation process which consists of the collection, storage, and processing of data.

In the zzz-regulatory-reporting use case, there is 1 sub folder relevant to this Data Collection, Data Processing, and Data Storage step; Corporate_Functions_Consolidation which includes jobs designed to demonstrate the triggering and monitoring of the Business Continuity processing on GCP Batch, Data Processing on AWS Batch, and Threat Intelligence processing on Azure Batch.

Data Consumption

Finally, Control-M orchestrates the delivery of processed data to end-users and regulatory bodies by:

Generating and distributing regulatory reports (e.g., financial statements, risk assessments)
Feeding data into business intelligence (BI) tools (e.g., Tableau, Power BI) for visualization and insights
Automating the submission of reports to regulatory authorities (e.g., U.S. SEC, European Central Bank)

In the zzz-regulatory-reporting use case, there is 2 subfolders relevant to the Data Consumption step; External_Reporting which includes a job designed to demonstrate using aggregated data to populate Tableau dashboards viewable by external users like auditors, and Internal_Reporitng which includes a job designed to demonstrate using aggregated data to populate PowerBI dashboards on the Azure Cloud platform viewable by internal business users.

Audit, Compliance, and SLA Reporting

Control-M includes comprehensive features for audit compliance and SLA reporting, essential for the BFSI industry:

Audit Trails: Maintain detailed logs of all job executions, user actions, and data changes. This meets regulatory requirements for transparency and accountability.
Compliance Reporting: Generate reports to demonstrate adherence to regulations and internal policies. SLA Reporting
Real-Time Monitoring: Continuously monitor job performance against predefined SLAs to ensure timely execution.
Alerts and Notifications: Send alerts and notifications in case of SLA breaches or job failures, enabling quick resolution.
Performance Dashboards: Visualize SLA metrics and job performance through customizable dashboards

In the zzz-regulatory-reporting use case there is a job zzz-audit-compliance-SLA designed to demonstrate the features listed above.

To view the demo flow code-base, and all artifacts, please navigate to the Regulatory Reporting Git Repository

Job Types Included

Control-M OS
Control-M Databases
Control-M Managed File Transfer
Control-M for GCP Dataflow
Control-M for AWS Batch
Control-M for Azure Batch Functions
Control-M for Tableau
Control-M for PowerBI
Control-M SLA Management

Demo Environment Information

Environment	Status	Folder
Helix Production	Available	zzz-regulatory-reporting
Helix Pre-Production	Available	zzz-regulatory-reporting
VSE CTM PROD	Available	zzz-regulatory-reporting
VSE CTM QA	Available	zzz-regulatory-reporting