how cognizant's zdlc solution is helping data lineage for compliance to basel iii
DESCRIPTION
A solution powered by Cognizant ZDLC framework to accelerate the process of data extraction and improve the precision of the end to end data lineage of systems using automation techniques. A solution designed for the BCBS 239 Initiative.TRANSCRIPT
POWERED BY ZDLC
Cognizant BCBS Solution
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OVERVIEW OF THECognizant BCBS Solution
By automating the process, the Cognizant BCBS Solution accelerates and increases the precision of providing compliant data to auditors. This, in turn, reduces risks and costs associated with the compliance process, diminishing the overhead on banking operations.
One of the Basel III regulations requires banks to trace data used to calculate risk exposure back to their original sources in a way that is auditable at any step of the process. This is complex because of the number of intermediate calculations, databases systems, spreadsheets, and departments that have handled the data. Manually tracing this data lineage is arduous, time-consuming, and prone to error; however, without it, banks will face fines and other sanctions.
The Cognizant BCBS Solution automates the data lineage challenge. It first creates an index of the current state of reporting, then traces back each element in the report through the rules, transformation logic, and intermediate calculations that were applied. Next, a reporting system collects data from existing and new sources, such as live feeds from front-office, middle-office, and back-office systems to demonstrate compliance on an ongoing basis. Auditors are able to examine for themselves the original sources of data.
PROBLEM
SOLUTION
BENEFITS
CONTENTS
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An overview of the Cognizant BCBS solution 1
The business challenges of implementing Basel 2
The process of implementing BCBS 3
Our proposed BCBS solution 4
How does the solution work? 5
Benefits of using Cognizant BCBS Solution 6
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AN OVERVIEW OF THECognizant BCBS Solution
The solution is an Integrated approach for data Consolidation & employs analytics for dashboards and regulatory reporting.
We are proposing a solution targeted specifically to the implementation of the BCBS by any banks.
Cognizant has devised a solution, that accelerates the implementation of BCBS whilst maximising precision and compliance to regulatory reporting.
The solution employs techniques of automation for data extraction & data lineage of existing reports.
The solution uses social collaboration techniques to enhance the process of data certification.
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BCBS (BASEL Committee for Banking Supervision).
The solution automates the validation and reconciliation activities to ensure that the generated data lineage documents aligns with the input files.
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Managing the Data
Taking an Integrated ApproachA New Risk and Finance Management Culture
Managing Basel III: Different Geographies, Different Issues
Auditing the Data
Stress testing—the ability to understand the impact of significant market events on the key ratios.
THE BUSINESS CHALLENGES OF IMPLEMENTING BASEL
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Basel III is part of the BCBS Initiative to enhance the banking regulatory framework. It is a comprehensive set of reform measures designed to improve the regulation, supervision and risk management within the banking sector. It seeks to improve the banking sector's ability to deal with financial and economic stress and strengthen the banks' transparency on reporting. The focus of Basel III is to foster greater resilience at the individual bank level in order to reduce the risk of system wide shocks
THE BUSINESS CHALLENGES
Moody’s Analytics, September 2011
Pillar 1• Enhanced
Minimum Capital & Liquidity Requirements
Pillar 2• Enhanced
Supervisory Review for firm wide risk & capital planning
Pillar 3• Enhanced Risk
Disclosure and Market Discipline
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THE COMPREHENSIVERegulatory Compliance Reporting
The following depicts the Delivery Mechanism of Regulatory Compliance Reporting, Moody’s Analytics, September 2011,
• Risk Framework
• Risk Culture• Risk
Infrastructure• Data Gap
Analysis
• Customer information
• Risk drivers• Assets• Liabilities• Off Balance
Exposures• Repos• Derivatives• General Ledger• Gross income
• Cleanse• Consolidate• Reconcile• Built-in Data• Quality Checks• Drill-down• OLAP
Technology• Comprehensive• Audit Trail
Credit, Market,Operational, Liquidityand Concentration Risks• Tier 1 and 2 Capital• Own Funds
Deductions• Risk Weighted
Assets• Expected Loss• Capital Ratios • Liquidity Coverage
Ratio• Net Stable Funding
Ratio
Regulatory:• Multi-jurisdiction• (over 2000
reports for• over 50
countries)• Multi-format:
XBRL,• MS Excel ,XML• Internal:• Dashboard of
Key• Risk Indicators
• Risk Based• Decision-
making• Performance• Management• Capital
Optimization
Understand firm wide regulations
data needInput Data Manage Data
Quality Calculate Report Refine Strategy
Data Extraction Data Lineage Data Certification Data Integration Report
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Data Extraction Data Lineage Data Certification Data Integration Report
1. Identify System of Records (SOR)
2. Identify each data element from the existing report,
3. Identify internal and external data sets of reports
4. Validate data inputs
• Acceleration• Precision• Reliable Validation
1. Show the association between source data elements and target data elements.
2. Identify the business rules and calculations used on the data elements
3. Generate & Validate data lineage doc.
• Completeness• Precision• Reliable Validation
1. Each core data element & the their SOR are to be certified.
2. Rules and/or transformation logic to be certified for derived data elements.
3. Define appropriate certification process for future
• Collaborative• Precision• Reliable Validation
1. Extract the data elements post certification from source
2. Map and transform data to the format of target platform
3. Migrate data and validate
4. Deploy target platform
• Acceleration• Data Integrity• Reliable Validation
1. Regulatory Reporting should be generated according to the Basel protocol and validated prior to submission
2. Reporting which should be accessible to external auditor
• Compliance• Completeness• Reliable Validation
THE PROCESS OF Implementing BCBS
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Data Extraction Data Lineage Data Certification Data Integration Report
• Acceleration• Precision• Reliable Validation
• Completeness• Precision• Reliable Validation
• Collaborative• Precision• Reliable Validation
• Acceleration• Data Integrity• Reliable Validation
• Compliance• Completeness• Reliable Validation
OUR PROPOSEDBCBS Solution
Cognizant ZDLC’s Smart Process Discovery (SPD) Automation tool engaged in Reverse Engineering of existing Input data, & Reports into Data models (ERDs)
Provides a Validation Engine to check Input files for inconsistencies
Cognizant ZDLC’s Smart Process Discovery Automation tool to generate a comprehensive data lineage documents
Provides a Reconciliation Engine to check output against the existing reports
Cognizant ZDLC’s Smart Process Discovery provides a collaborative framework for users to annotate the data elements, which have been reverse engineered, with Rules and/or transformation logic that are to be certified for derived data elements.
Cognizant Data Integration Workbench (DIW) is tool for automated generation of ETL code driven through functional inputs
DIW is integrated with Informatica (and others) to automatically create the mappings in the repository by taking inputs from ZDLC SPD tool and other sources
Generate Regulatory Reporting for each of the Pillar requirements of Basel from a consolidated data warehouse.
Manual Process
Automated Process
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BENEFITS OF USINGCognizant BCBS Solution
Measure Cognizant ZDLC Approach Classical ApproachNo of Files Processed 150 per person per day 5 – 6 per person per day
Measure Cognizant ZDLC Approach Classical Approach No of Data lineage document validated 15 per person per day 3 per person per day
Measure Cognizant ZDLC Approach Classical ApproachNo of data lineage document certified 30 per person per day 10 Per person per day
Measure Cognizant ZDLC Approach Classical ApproachEffort reduction in the Data Integration activities for consolidated Regulatory Reporting system 30% N/A
Data Extraction
Data Lineage
Data Certification
Data Integration
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HOW DOES THESolution works? (Part 1)
OutputReverse Engineering Core Module
AdaptersSystem Behaviour
SQL
Oracle PL/SQL
Excel Sheets
Java
Configuration Matrix
Crawler
Generic Parser
Analyser
SAS, PL SQL, Excels and others
System Logs, DB Logs
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• ZDLC is a suite of tools that accelerates the process of extracting and modelling a precise picture of AS-IS IT applications
• ZDLC does so, by automatically reverse engineering the existing database logs and existing reporting scripts.
• A precise picture and definition of the existing reports , database schemas and data lineage documents
• A single point of authoring and managing the system documents• A collaborative way of annotating the existing reports.
Features of Smart Process Discovery Outcome of using the tool
SAS
… Others
.NET
Cognizant Smart Process Discovery Tools (SPD)
Data Extraction Data Lineage Data Certification
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HOW DOES THESolution works? (Part 2)
Cognizant Data Integration Workbench (DIW)
XML Binding
<xml>
Structural Validation
Semantic Validation
Efficiency Validation
Software Development Kit
Automated Code
Generation
Deploy Code to ETL Tool Repository
Updates & Code
Completion
DESIGN
ETL Design
Specification
Coding Standards
Metadata Repositor
y
Base Code
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DDL File
DDL
1. Upload the design specification (source-to-target data mapping) in XML format.
2. DIW validates the uploaded design specification for structural and semantic correctness.
3. Generate code based on the design specification (Some manual updates may be necessary for completing the code generation)
4. Update data lineage and transformation lineage into Metadata Repository and Deploy the code generated into Repository.
5. Archive the based code generated with automation.
Data Integration