SlideShare a Scribd company logo
1 of 31
CRisMac Solution For
     MIS-ADF
Introduction - RBI Requirement
 Flow of data from Individual source system into a Centralized Data Repository

 Need for a common end state covering the dimensions of Process & Technology

 Accurate and timely data without any manual intervention

 Transformation of Data to be submitted to RBI through various layers:

• Data Acquisition Layer

• Data Integration & Submission Layer

• Data Conversion/Validation Layer

• Data Submission Layer
Benefits of Automation:

 Improved Timelines

 Enhanced Data Quality

 Improved Efficiency of Processes

 Reduced Costs

 Use of the CDR for MIS Purposes
CRisMac in Banks

Comprehensive Database (Assets, Liabilities & others)
Interfacing with transaction system
    Existing customers / accounts.
    New customers/ accounts.
Cross validation of parameterized data
 Gen of business & regulatory MIS
Gen of Information of Dash Boards for executives
Gen of monitoring reports on banking ops.
Generation of internal analytical reports.
CRisMac in Banks

Processing engine for granular data output for DSS
 Automated asset classification & provision computation.
MOC incorporation.
Generation of compliance reports (pre/post MOC).
Basel II computation of RWA of loans & generation of XBRL output as per RBI
taxonomy.
Generation of CIBIL outputs
    Commercial & consumer data (new & old formats).
    CIBIL mortgage & CIBIL detect (available).
Credit monitoring reports.
    Potential NPA reports.
    Review / renewal monitoring reports.
    Document / insurance due date monitoring.
    Limit wise, age wise classification reports.
CRisMac in Banks
Facilitating audit process at branch / RO/HO level.
    Closing returns (pre/post MOC ) for loans assets
    Verification of fresh slippages/ upgradation.
    Verification of RW computation for Basel II compliance
    Reconciliation of MOCs and net effect verification.
    Movement of gross / Net NPA / provision at account level.
    Generation of Schlixof BS.
Generation of regulatory returns
    BSR 1A , 1B in ASCII format
    DSB returns
    Priority sector returns.
Work Flow of ADF by RBI
  Bank                             Data                                                                                 Data
 Current                         Acquisition                                                                        Integration &
  State                                                                                                                Storage
            Ensure data
             timeliness                                                        Define standard data
                                                                               structure for storage
                      Ensure data
                        quality
                                                                                           Build a common
                                    Ensure required                                       metadata framework
                                    data is captured
                                                                                                     Ensure data is loaded to
                                                                                                        centralized data
                                                          Build provision for                              repository
                                                       receiving and interpreting
                                                        feedback from Reserve
                                                             Bank systems
                                         Build the return
                                       submission tracking
                                          mechanism                                                     Map target data to
                           Prepare and                                                               repository data structure
                          implement the
                      calendar for returns
                           submission                                                Define the business logic
              Build provision                                                       for mapping and validation
              for generation
               of certificate                                                       Implement the
Common                                                                              business logic
                                          Data
End State                              Submission
                                                                                                                         Data
                                                                                                                       Conversion
Work Flow of CRisMac ADF by D2K
Road-map for implementation
Finalisation of requirement.
Study of data sources for mapping of source data elements with target data elements.
Identification of gap data elements.
Finalisation of business rules for cross validations.
SRS sign off
Designing/ development of ETL routines.
Designing & development of interface.
Designing and development of reports.
UAT sign off.
Pilot run and sign off.
Go live
CRisMac ADF Extraction Process

SOURCE OF FIELDS
USER_DIRECTIONS
CBS TO STG
SQLs
STG TO TEMP_diagram
SQLs STG TO TEMP
TEMP TO MAIN
SQLs TEMP TO MAIN
BRANCH_REALLOCATION
TIMEKEY_CHECK
bg_status
UNIFORM BRCODE
CRisMac ADF Extraction Process - SSIS
CRisMac ADF Extraction Process - SSIS
CRisMac ADF Extraction Process - SSIS
Data Quality & Cleansing through
CRisMac ADF
Data Issues:
  Invalid Data
  Conflicting Data
  Insufficient Data
Quality Data leads to:
  Increased efficiency.
  Enhanced customer satisfaction.
  Drives profitability of organisation.
Poor Quality Data:
  Conflicting reports.
  Flawed business plans.
  Erroneous decisions
Data Quality & Cleansing through
CRisMac ADF

Total number of source records:
Percent of missing column values: May be represented by NULL or a
dummy value such as NA, Unknown, or 9999 etc in source data.
Percent of referential integrity errors.
Missing file indicator.
Source system schema change indicator.
Flagging suspicious data values: Exceptionally high or low values.
CRisMac ADF - GAP Data Interface
Inward-Outward Remittances
Unclaimed Deposits
Details of Service Tax Paid
Trade Credit Approvals
BSR-III
Trade Credit Disbursements & Debt Servicing
NHAG Details
Bond Details
Bank Reconciliation
Credit Card Business Details
Sundry Debtors.
Loan Sale Securitization Details
Bullion Import Details
BSR-IV
Mode of Operation
Change Branch Selection




                          Add
                          Edit/Delete
                          View
Reports

 RBI 28- Balance sheet Analysis

 RBI 31- DSB Return no-III report on Quarterly operating results

 RBI 36-Statement of Structural Liquidity

RBI 109–BSR Accounts with Credit Limits of Over Rs 2 lakh

 RBI 110A-

 RBI 110 B –BSR Classification of Term Deposits According to Original Maturity
Reports
 RBI 110 C –BSR Classification of Term Deposits According to Interest Rate

Range

RBI 110D-

RBI 110 E -BSR Classification of Term Deposits According to Residual

Maturity

 RBI 189-SME_IOutstanding Credit to Micro Small and Medium Enterprises

(MSME) Sector

 RBI 197 -Half Yearly Adhoc data on Priority Sector Advances

 RBI 200- State wise Yearly return on Priority Sector Advances (Final)
CRisMac ADF - Key Solution components
Solution/Service Component           Proposed Components

       ADF solution                          CRisMac©

        Data Base                SQL 2008 R2 Enterprise edition

                             SQL Server Integration Services (Built-in
           ETL
                                  with MS SQL Server license)

         Interface                     Visual Studio 2010


                              Compatible servers from recognized
        Hardware
                             vendors as per Hardware requirements
CRisMac ADF Solution Architecture: Physical
CRisMac ADF - High Availability Architecture

Clustering of Database Servers

Clustering of Application servers

Redundant Power, LAN, FC Interfaces

Redundant Boot Disks for Operating systems

ISCSI Based Blade Storage deployment

Remote Management and Proactive Diagnosis of Hardware

SQL DB Mirroring
OUR CREDENCE
CRisMac solution for ADF
CRisMac solution for ADF
CRisMac solution for ADF
CRisMac solution for ADF
CRisMac solution for ADF
CRisMac solution for ADF
CRisMac solution for ADF
CRisMac solution for ADF

More Related Content

What's hot

Good Data: Collaborative Analytics On Demand
Good Data: Collaborative Analytics On DemandGood Data: Collaborative Analytics On Demand
Good Data: Collaborative Analytics On Demandzsvoboda
 
Collaborate 2012-business data transformation and consolidation for a global ...
Collaborate 2012-business data transformation and consolidation for a global ...Collaborate 2012-business data transformation and consolidation for a global ...
Collaborate 2012-business data transformation and consolidation for a global ...Chain Sys Corporation
 
Jim Killian\'s SQL Server 2008 Portfolio
Jim Killian\'s SQL Server 2008 PortfolioJim Killian\'s SQL Server 2008 Portfolio
Jim Killian\'s SQL Server 2008 PortfolioJim Killian
 
Resume for DB2 DBA LUW/AIX
Resume for DB2 DBA LUW/AIXResume for DB2 DBA LUW/AIX
Resume for DB2 DBA LUW/AIXMadan Gupta
 
Summit 2011 ods edw technical
Summit 2011 ods edw technicalSummit 2011 ods edw technical
Summit 2011 ods edw technicalGreg Turmel
 
SAP BW BI ONLINE TRAINING
SAP BW BI ONLINE TRAININGSAP BW BI ONLINE TRAINING
SAP BW BI ONLINE TRAININGTRAINING ICON
 
Gp Installation Presentation
Gp Installation PresentationGp Installation Presentation
Gp Installation Presentationddauphin
 
Scaling your applications with the ims catalog
Scaling your applications with the ims catalogScaling your applications with the ims catalog
Scaling your applications with the ims catalogYuhui Li
 
C8 Whats New In Versions 3 And 4
C8   Whats New In Versions 3 And 4C8   Whats New In Versions 3 And 4
C8 Whats New In Versions 3 And 4dfwcug
 
Data extraction and retraction in bpc bi
Data extraction and retraction in bpc biData extraction and retraction in bpc bi
Data extraction and retraction in bpc bivikram2355
 
Linalis UK introduction
Linalis UK introductionLinalis UK introduction
Linalis UK introductionSteve Adams
 
Resource Advisor Overview
Resource Advisor OverviewResource Advisor Overview
Resource Advisor OverviewRose Shaver
 
Effective Integration of SAP MDM & BODS
Effective Integration of SAP MDM & BODSEffective Integration of SAP MDM & BODS
Effective Integration of SAP MDM & BODSNavneetGiria
 
HCLT Brochure: E-Discovery and Document Review Solutions
HCLT Brochure: E-Discovery and Document Review SolutionsHCLT Brochure: E-Discovery and Document Review Solutions
HCLT Brochure: E-Discovery and Document Review SolutionsHCL Technologies
 
Orders of-magnitude-scale-out-your-sql-server-data-slideshare
Orders of-magnitude-scale-out-your-sql-server-data-slideshareOrders of-magnitude-scale-out-your-sql-server-data-slideshare
Orders of-magnitude-scale-out-your-sql-server-data-slideshareMark Broadbent
 
JDE & Peoplesoft 2 _ Sam Sampathnathan _ Best Practices for Managing Your JD ...
JDE & Peoplesoft 2 _ Sam Sampathnathan _ Best Practices for Managing Your JD ...JDE & Peoplesoft 2 _ Sam Sampathnathan _ Best Practices for Managing Your JD ...
JDE & Peoplesoft 2 _ Sam Sampathnathan _ Best Practices for Managing Your JD ...InSync2011
 

What's hot (18)

Good Data: Collaborative Analytics On Demand
Good Data: Collaborative Analytics On DemandGood Data: Collaborative Analytics On Demand
Good Data: Collaborative Analytics On Demand
 
Collaborate 2012-business data transformation and consolidation for a global ...
Collaborate 2012-business data transformation and consolidation for a global ...Collaborate 2012-business data transformation and consolidation for a global ...
Collaborate 2012-business data transformation and consolidation for a global ...
 
Plm Data Migration
Plm Data MigrationPlm Data Migration
Plm Data Migration
 
Jim Killian\'s SQL Server 2008 Portfolio
Jim Killian\'s SQL Server 2008 PortfolioJim Killian\'s SQL Server 2008 Portfolio
Jim Killian\'s SQL Server 2008 Portfolio
 
Resume for DB2 DBA LUW/AIX
Resume for DB2 DBA LUW/AIXResume for DB2 DBA LUW/AIX
Resume for DB2 DBA LUW/AIX
 
Summit 2011 ods edw technical
Summit 2011 ods edw technicalSummit 2011 ods edw technical
Summit 2011 ods edw technical
 
SAP BW BI ONLINE TRAINING
SAP BW BI ONLINE TRAININGSAP BW BI ONLINE TRAINING
SAP BW BI ONLINE TRAINING
 
Gp Installation Presentation
Gp Installation PresentationGp Installation Presentation
Gp Installation Presentation
 
Scaling your applications with the ims catalog
Scaling your applications with the ims catalogScaling your applications with the ims catalog
Scaling your applications with the ims catalog
 
C8 Whats New In Versions 3 And 4
C8   Whats New In Versions 3 And 4C8   Whats New In Versions 3 And 4
C8 Whats New In Versions 3 And 4
 
Data extraction and retraction in bpc bi
Data extraction and retraction in bpc biData extraction and retraction in bpc bi
Data extraction and retraction in bpc bi
 
Linalis UK introduction
Linalis UK introductionLinalis UK introduction
Linalis UK introduction
 
Resource Advisor Overview
Resource Advisor OverviewResource Advisor Overview
Resource Advisor Overview
 
Effective Integration of SAP MDM & BODS
Effective Integration of SAP MDM & BODSEffective Integration of SAP MDM & BODS
Effective Integration of SAP MDM & BODS
 
Larocca
LaroccaLarocca
Larocca
 
HCLT Brochure: E-Discovery and Document Review Solutions
HCLT Brochure: E-Discovery and Document Review SolutionsHCLT Brochure: E-Discovery and Document Review Solutions
HCLT Brochure: E-Discovery and Document Review Solutions
 
Orders of-magnitude-scale-out-your-sql-server-data-slideshare
Orders of-magnitude-scale-out-your-sql-server-data-slideshareOrders of-magnitude-scale-out-your-sql-server-data-slideshare
Orders of-magnitude-scale-out-your-sql-server-data-slideshare
 
JDE & Peoplesoft 2 _ Sam Sampathnathan _ Best Practices for Managing Your JD ...
JDE & Peoplesoft 2 _ Sam Sampathnathan _ Best Practices for Managing Your JD ...JDE & Peoplesoft 2 _ Sam Sampathnathan _ Best Practices for Managing Your JD ...
JDE & Peoplesoft 2 _ Sam Sampathnathan _ Best Practices for Managing Your JD ...
 

Viewers also liked

Bd04 statistikdesktiptif
Bd04 statistikdesktiptifBd04 statistikdesktiptif
Bd04 statistikdesktiptifAnan Nur
 
เรื่อง เครื่องใช้ไฟฟ้าในปัจจุบัน
เรื่อง เครื่องใช้ไฟฟ้าในปัจจุบันเรื่อง เครื่องใช้ไฟฟ้าในปัจจุบัน
เรื่อง เครื่องใช้ไฟฟ้าในปัจจุบันpatipansata
 

Viewers also liked (6)

Acenza villas
Acenza villasAcenza villas
Acenza villas
 
Bd04 statistikdesktiptif
Bd04 statistikdesktiptifBd04 statistikdesktiptif
Bd04 statistikdesktiptif
 
Relationships
RelationshipsRelationships
Relationships
 
Pgsm preview (topup 20)
Pgsm preview (topup 20)Pgsm preview (topup 20)
Pgsm preview (topup 20)
 
เรื่อง เครื่องใช้ไฟฟ้าในปัจจุบัน
เรื่อง เครื่องใช้ไฟฟ้าในปัจจุบันเรื่อง เครื่องใช้ไฟฟ้าในปัจจุบัน
เรื่อง เครื่องใช้ไฟฟ้าในปัจจุบัน
 
Wisdom
WisdomWisdom
Wisdom
 

Similar to CRisMac solution for ADF

CRis Mac Solution for MIS-ADF
CRis Mac Solution for MIS-ADFCRis Mac Solution for MIS-ADF
CRis Mac Solution for MIS-ADFD2K Technologies
 
Tideway Foundation 7.2 Cmdb Population
Tideway Foundation 7.2 Cmdb PopulationTideway Foundation 7.2 Cmdb Population
Tideway Foundation 7.2 Cmdb PopulationPeter Grant
 
Clincial Data Management
Clincial Data ManagementClincial Data Management
Clincial Data ManagementDeepak Yadav
 
5. iED Cloud Services.pdf
5. iED Cloud Services.pdf5. iED Cloud Services.pdf
5. iED Cloud Services.pdfssuser905b17
 
110823 data fed_solta11
110823 data fed_solta11110823 data fed_solta11
110823 data fed_solta11Rudolf Husar
 
Sap bi training with bo integrations
Sap bi training with bo integrationsSap bi training with bo integrations
Sap bi training with bo integrationspjraosapbi
 
Qué hay de nuevo en sql azure
Qué hay de nuevo en sql azureQué hay de nuevo en sql azure
Qué hay de nuevo en sql azureEduardo Castro
 
Centralizing sequence analysis
Centralizing sequence analysisCentralizing sequence analysis
Centralizing sequence analysisDenis C. Bauer
 
Talk IT_ Oracle_김태완_110831
Talk IT_ Oracle_김태완_110831Talk IT_ Oracle_김태완_110831
Talk IT_ Oracle_김태완_110831Cana Ko
 
Denny Lee\'s Data Camp v1.0 talk on SSRS Best Practices for IT
Denny Lee\'s Data Camp v1.0 talk on SSRS Best Practices for ITDenny Lee\'s Data Camp v1.0 talk on SSRS Best Practices for IT
Denny Lee\'s Data Camp v1.0 talk on SSRS Best Practices for ITBala Subra
 
Veritas vision for cloud providers (screenshots)
Veritas vision for cloud providers (screenshots)Veritas vision for cloud providers (screenshots)
Veritas vision for cloud providers (screenshots)Alexschoone
 
Dcom be-en-data-assessment-approach
Dcom be-en-data-assessment-approachDcom be-en-data-assessment-approach
Dcom be-en-data-assessment-approachfwathelet
 
Dynamic Data Center Toolkit - Darryl Chantry
Dynamic Data Center Toolkit - Darryl ChantryDynamic Data Center Toolkit - Darryl Chantry
Dynamic Data Center Toolkit - Darryl ChantrySpiffy
 
Segue Capabilities Briefing Winter 2010
Segue Capabilities Briefing Winter 2010Segue Capabilities Briefing Winter 2010
Segue Capabilities Briefing Winter 2010DavidHart
 
Enterprise GIS Implementation for Public Infrastructure and Integration with ...
Enterprise GIS Implementation for Public Infrastructure and Integration with ...Enterprise GIS Implementation for Public Infrastructure and Integration with ...
Enterprise GIS Implementation for Public Infrastructure and Integration with ...Michael Baker Jr., Inc.
 
Ct 10 S3 Anthony Feliciano
Ct 10 S3 Anthony FelicianoCt 10 S3 Anthony Feliciano
Ct 10 S3 Anthony Felicianoanthonyfeliciano
 
Accel Partners New Data Workshop 7-14-10
Accel Partners New Data Workshop 7-14-10Accel Partners New Data Workshop 7-14-10
Accel Partners New Data Workshop 7-14-10keirdo1
 
IBM consolidation and relocation webinar
IBM consolidation and relocation webinarIBM consolidation and relocation webinar
IBM consolidation and relocation webinarHerb Hernandez
 

Similar to CRisMac solution for ADF (20)

CRis Mac Solution for MIS-ADF
CRis Mac Solution for MIS-ADFCRis Mac Solution for MIS-ADF
CRis Mac Solution for MIS-ADF
 
Tideway Foundation 7.2 Cmdb Population
Tideway Foundation 7.2 Cmdb PopulationTideway Foundation 7.2 Cmdb Population
Tideway Foundation 7.2 Cmdb Population
 
Clincial Data Management
Clincial Data ManagementClincial Data Management
Clincial Data Management
 
5. iED Cloud Services.pdf
5. iED Cloud Services.pdf5. iED Cloud Services.pdf
5. iED Cloud Services.pdf
 
110823 data fed_solta11
110823 data fed_solta11110823 data fed_solta11
110823 data fed_solta11
 
Sap bi training with bo integrations
Sap bi training with bo integrationsSap bi training with bo integrations
Sap bi training with bo integrations
 
Qué hay de nuevo en sql azure
Qué hay de nuevo en sql azureQué hay de nuevo en sql azure
Qué hay de nuevo en sql azure
 
Centralizing sequence analysis
Centralizing sequence analysisCentralizing sequence analysis
Centralizing sequence analysis
 
Talk IT_ Oracle_김태완_110831
Talk IT_ Oracle_김태완_110831Talk IT_ Oracle_김태완_110831
Talk IT_ Oracle_김태완_110831
 
Denny Lee\'s Data Camp v1.0 talk on SSRS Best Practices for IT
Denny Lee\'s Data Camp v1.0 talk on SSRS Best Practices for ITDenny Lee\'s Data Camp v1.0 talk on SSRS Best Practices for IT
Denny Lee\'s Data Camp v1.0 talk on SSRS Best Practices for IT
 
Veritas vision for cloud providers (screenshots)
Veritas vision for cloud providers (screenshots)Veritas vision for cloud providers (screenshots)
Veritas vision for cloud providers (screenshots)
 
Dcom be-en-data-assessment-approach
Dcom be-en-data-assessment-approachDcom be-en-data-assessment-approach
Dcom be-en-data-assessment-approach
 
Dynamic Data Center Toolkit - Darryl Chantry
Dynamic Data Center Toolkit - Darryl ChantryDynamic Data Center Toolkit - Darryl Chantry
Dynamic Data Center Toolkit - Darryl Chantry
 
Segue Capabilities Briefing Winter 2010
Segue Capabilities Briefing Winter 2010Segue Capabilities Briefing Winter 2010
Segue Capabilities Briefing Winter 2010
 
Enterprise GIS Implementation for Public Infrastructure and Integration with ...
Enterprise GIS Implementation for Public Infrastructure and Integration with ...Enterprise GIS Implementation for Public Infrastructure and Integration with ...
Enterprise GIS Implementation for Public Infrastructure and Integration with ...
 
v9.1.2 update
 v9.1.2 update v9.1.2 update
v9.1.2 update
 
Microsoft Dynamics GP 2013 - Mejoras
Microsoft Dynamics GP 2013 - MejorasMicrosoft Dynamics GP 2013 - Mejoras
Microsoft Dynamics GP 2013 - Mejoras
 
Ct 10 S3 Anthony Feliciano
Ct 10 S3 Anthony FelicianoCt 10 S3 Anthony Feliciano
Ct 10 S3 Anthony Feliciano
 
Accel Partners New Data Workshop 7-14-10
Accel Partners New Data Workshop 7-14-10Accel Partners New Data Workshop 7-14-10
Accel Partners New Data Workshop 7-14-10
 
IBM consolidation and relocation webinar
IBM consolidation and relocation webinarIBM consolidation and relocation webinar
IBM consolidation and relocation webinar
 

Recently uploaded

Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions
 
Bluetooth Controlled Car with Arduino.pdf
Bluetooth Controlled Car with Arduino.pdfBluetooth Controlled Car with Arduino.pdf
Bluetooth Controlled Car with Arduino.pdfngoud9212
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr LapshynFwdays
 
Science&tech:THE INFORMATION AGE STS.pdf
Science&tech:THE INFORMATION AGE STS.pdfScience&tech:THE INFORMATION AGE STS.pdf
Science&tech:THE INFORMATION AGE STS.pdfjimielynbastida
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024Scott Keck-Warren
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):comworks
 
Artificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraArtificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraDeakin University
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsMiki Katsuragi
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 3652toLead Limited
 
APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April  Automation LPDGAPIForce Zurich 5 April  Automation LPDG
APIForce Zurich 5 April Automation LPDGMarianaLemus7
 
My INSURER PTE LTD - Insurtech Innovation Award 2024
My INSURER PTE LTD - Insurtech Innovation Award 2024My INSURER PTE LTD - Insurtech Innovation Award 2024
My INSURER PTE LTD - Insurtech Innovation Award 2024The Digital Insurer
 
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024BookNet Canada
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 

Recently uploaded (20)

Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food Manufacturing
 
Bluetooth Controlled Car with Arduino.pdf
Bluetooth Controlled Car with Arduino.pdfBluetooth Controlled Car with Arduino.pdf
Bluetooth Controlled Car with Arduino.pdf
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
 
Science&tech:THE INFORMATION AGE STS.pdf
Science&tech:THE INFORMATION AGE STS.pdfScience&tech:THE INFORMATION AGE STS.pdf
Science&tech:THE INFORMATION AGE STS.pdf
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):
 
Artificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraArtificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning era
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering Tips
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
 
Hot Sexy call girls in Panjabi Bagh 🔝 9953056974 🔝 Delhi escort Service
Hot Sexy call girls in Panjabi Bagh 🔝 9953056974 🔝 Delhi escort ServiceHot Sexy call girls in Panjabi Bagh 🔝 9953056974 🔝 Delhi escort Service
Hot Sexy call girls in Panjabi Bagh 🔝 9953056974 🔝 Delhi escort Service
 
Vulnerability_Management_GRC_by Sohang Sengupta.pptx
Vulnerability_Management_GRC_by Sohang Sengupta.pptxVulnerability_Management_GRC_by Sohang Sengupta.pptx
Vulnerability_Management_GRC_by Sohang Sengupta.pptx
 
APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April  Automation LPDGAPIForce Zurich 5 April  Automation LPDG
APIForce Zurich 5 April Automation LPDG
 
My INSURER PTE LTD - Insurtech Innovation Award 2024
My INSURER PTE LTD - Insurtech Innovation Award 2024My INSURER PTE LTD - Insurtech Innovation Award 2024
My INSURER PTE LTD - Insurtech Innovation Award 2024
 
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 

CRisMac solution for ADF

  • 2. Introduction - RBI Requirement  Flow of data from Individual source system into a Centralized Data Repository  Need for a common end state covering the dimensions of Process & Technology  Accurate and timely data without any manual intervention  Transformation of Data to be submitted to RBI through various layers: • Data Acquisition Layer • Data Integration & Submission Layer • Data Conversion/Validation Layer • Data Submission Layer
  • 3. Benefits of Automation:  Improved Timelines  Enhanced Data Quality  Improved Efficiency of Processes  Reduced Costs  Use of the CDR for MIS Purposes
  • 4. CRisMac in Banks Comprehensive Database (Assets, Liabilities & others) Interfacing with transaction system Existing customers / accounts. New customers/ accounts. Cross validation of parameterized data  Gen of business & regulatory MIS Gen of Information of Dash Boards for executives Gen of monitoring reports on banking ops. Generation of internal analytical reports.
  • 5. CRisMac in Banks Processing engine for granular data output for DSS  Automated asset classification & provision computation. MOC incorporation. Generation of compliance reports (pre/post MOC). Basel II computation of RWA of loans & generation of XBRL output as per RBI taxonomy. Generation of CIBIL outputs Commercial & consumer data (new & old formats). CIBIL mortgage & CIBIL detect (available). Credit monitoring reports. Potential NPA reports. Review / renewal monitoring reports. Document / insurance due date monitoring. Limit wise, age wise classification reports.
  • 6. CRisMac in Banks Facilitating audit process at branch / RO/HO level. Closing returns (pre/post MOC ) for loans assets Verification of fresh slippages/ upgradation. Verification of RW computation for Basel II compliance Reconciliation of MOCs and net effect verification. Movement of gross / Net NPA / provision at account level. Generation of Schlixof BS. Generation of regulatory returns BSR 1A , 1B in ASCII format DSB returns Priority sector returns.
  • 7. Work Flow of ADF by RBI Bank Data Data Current Acquisition Integration & State Storage Ensure data timeliness Define standard data structure for storage Ensure data quality Build a common Ensure required metadata framework data is captured Ensure data is loaded to centralized data Build provision for repository receiving and interpreting feedback from Reserve Bank systems Build the return submission tracking mechanism Map target data to Prepare and repository data structure implement the calendar for returns submission Define the business logic Build provision for mapping and validation for generation of certificate Implement the Common business logic Data End State Submission Data Conversion
  • 8. Work Flow of CRisMac ADF by D2K
  • 9. Road-map for implementation Finalisation of requirement. Study of data sources for mapping of source data elements with target data elements. Identification of gap data elements. Finalisation of business rules for cross validations. SRS sign off Designing/ development of ETL routines. Designing & development of interface. Designing and development of reports. UAT sign off. Pilot run and sign off. Go live
  • 10. CRisMac ADF Extraction Process SOURCE OF FIELDS USER_DIRECTIONS CBS TO STG SQLs STG TO TEMP_diagram SQLs STG TO TEMP TEMP TO MAIN SQLs TEMP TO MAIN BRANCH_REALLOCATION TIMEKEY_CHECK bg_status UNIFORM BRCODE
  • 11. CRisMac ADF Extraction Process - SSIS
  • 12. CRisMac ADF Extraction Process - SSIS
  • 13. CRisMac ADF Extraction Process - SSIS
  • 14. Data Quality & Cleansing through CRisMac ADF Data Issues: Invalid Data Conflicting Data Insufficient Data Quality Data leads to: Increased efficiency. Enhanced customer satisfaction. Drives profitability of organisation. Poor Quality Data: Conflicting reports. Flawed business plans. Erroneous decisions
  • 15. Data Quality & Cleansing through CRisMac ADF Total number of source records: Percent of missing column values: May be represented by NULL or a dummy value such as NA, Unknown, or 9999 etc in source data. Percent of referential integrity errors. Missing file indicator. Source system schema change indicator. Flagging suspicious data values: Exceptionally high or low values.
  • 16. CRisMac ADF - GAP Data Interface Inward-Outward Remittances Unclaimed Deposits Details of Service Tax Paid Trade Credit Approvals BSR-III Trade Credit Disbursements & Debt Servicing NHAG Details Bond Details Bank Reconciliation Credit Card Business Details Sundry Debtors. Loan Sale Securitization Details Bullion Import Details BSR-IV
  • 17. Mode of Operation Change Branch Selection Add Edit/Delete View
  • 18. Reports  RBI 28- Balance sheet Analysis  RBI 31- DSB Return no-III report on Quarterly operating results  RBI 36-Statement of Structural Liquidity RBI 109–BSR Accounts with Credit Limits of Over Rs 2 lakh  RBI 110A-  RBI 110 B –BSR Classification of Term Deposits According to Original Maturity
  • 19. Reports  RBI 110 C –BSR Classification of Term Deposits According to Interest Rate Range RBI 110D- RBI 110 E -BSR Classification of Term Deposits According to Residual Maturity  RBI 189-SME_IOutstanding Credit to Micro Small and Medium Enterprises (MSME) Sector  RBI 197 -Half Yearly Adhoc data on Priority Sector Advances  RBI 200- State wise Yearly return on Priority Sector Advances (Final)
  • 20. CRisMac ADF - Key Solution components Solution/Service Component Proposed Components ADF solution CRisMac© Data Base SQL 2008 R2 Enterprise edition SQL Server Integration Services (Built-in ETL with MS SQL Server license) Interface Visual Studio 2010 Compatible servers from recognized Hardware vendors as per Hardware requirements
  • 21. CRisMac ADF Solution Architecture: Physical
  • 22. CRisMac ADF - High Availability Architecture Clustering of Database Servers Clustering of Application servers Redundant Power, LAN, FC Interfaces Redundant Boot Disks for Operating systems ISCSI Based Blade Storage deployment Remote Management and Proactive Diagnosis of Hardware SQL DB Mirroring