Business Intelligence at Punjab National Bank

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Business Intelligence at Punjab National Bank

  1. 1. Business Intelligence at Punjab National Bank A Business Intelligence Project Business Intelligence at Punjab National BankGROUP 1ManishArora 201071Neharika Mallick 201086Puneet Arora 201111Raashi Sodhi 201112
  2. 2. A Business Intelligence Project EXECUTIVE SUMMARYIn the past decade, developments in the field of information technology (IT) have stronglysupported the growth and inclusiveness of the banking sector by facilitating inclusive economicgrowth. The industry has come a long way from introduction of credit cards in 90s to newtransaction and analytical systems in 2012.Today banks are storing more information than ever.Bankers must have the right information at the right time helping them making more informedand intelligent decisions.The main objective of the project was to study the implementation of Data Warehouse Systemin PNB (Punjab National Bank). Needs for implementation of Data Warehouse were identified.The CVC deadline to computerize 70 % of its business being the main driver for the initiativeproved to be a blessing in disguise for efficient operations of PNB. Major challenges forimplementing the new system were studied.PNB had certain requirements which were not being fulfilled by the existent systems like aunified view of data, timely compilation, monitoring of weak areas, adherence to statutoryreporting requirements and structured analysis of data for information decision making. TheEnterprise wide Data Warehouse (EDW) project was initiated by the Bank for leveraging theBanks operational data available in multiple source systems to facilitate ready access to datarequired for regulatory, statutory reporting and for various other analytical purposes.During the project PNB faced several issues like data quality, data extraction, data loading, dataloading, CRM. The issues faced during implementation process were successfully overcome.The bank undertook a data cleansing exercise which is an ongoing activity and is beingconducted through concentrated efforts by the Bank. The EDW project implementation wascarried out in a phased manner, with separate timelines for various solutions such as MIS, RiskManagement, Anti Money Laundering, Customer Relationship Management, ALM and FundsTransfer Pricing.The EDW solution successfully provided an integrated solution for RiskManagement, Anti-money laundering, and Customer Relationship management for enterprisewide users. The implementation of the data warehouse has not only given PNB better control andinsight into its operations; it’s also given management the perspective it requires to achieve thebank’s vision. 2
  3. 3. A Business Intelligence Project TABLE OF CONTENTSEXECUTIVE SUMMARY ........................................................................................................... 2TABLE OF FIGURES ................................................................................................................. 4CHAPTER1: BANKING INDUSTRY: INTRODUCTION .................................................................. 5 1.1 Structure Of Indian Banking Industry .........................................................................................5 1.2 Challenges Faced By Indian Banking Industry .............................................................................6 1.3 IT In Banking Sector ..................................................................................................................7 1.4 Data Warehousing In Banking Sector .........................................................................................8CHAPTER 2: PUNJAB NATIONAL BANK: COMPANY PROFILE .................................................. 11CHAPTER 3: PNB: THE BEGINNING OF IT STRATEGY .............................................................. 13 3.1 SWOT Analysis ........................................................................................................................ 13 3.2 IT Strategy .............................................................................................................................. 14 3.2.1 Short Term Goal ......................................................................................................................... 14 3.2.2 Hardware and Training .............................................................................................................. 14 3.2.3 Long-term strategy..................................................................................................................... 15CHAPTER 4: CORE BANKING ARCHITECTURE......................................................................... 15 4.1 Culture and technology issues ................................................................................................. 16 4.2 Systems .................................................................................................................................. 16 4.3 Network design ...................................................................................................................... 16 4.4 Storage systems...................................................................................................................... 17 4.5 Initiatives ............................................................................................................................... 17CHAPTER 5: ENTERPRISE WIDE DATA WAREHOUSE: PLANNING ............................................ 18 5.1 Requirements ......................................................................................................................... 19 5.2 Reasons for choosing EDW ...................................................................................................... 20 5.3 Challenges during Implementation Phase ................................................................................ 21 5.4 Solution Provided for various Business needs .......................................................................... 23 5.4.1 MIS and Analytics: ............................................................................................................... 23 5.4.2 Customer Relationship Management:................................................................................... 23 5.4.3 Risk Management: ............................................................................................................... 24CHAPTER 6: ENTERPRISE DATA WAREHOUSE SOFTWARE ..................................................... 25 6.1 Scope ..................................................................................................................................... 25 6.2 Benefits .................................................................................................................................. 26 6.3 Salient features of this project: ............................................................................................... 27CHAPTER 7: FUTURE SCOPE ................................................................................................. 28REFERENCES ........................................................................................................................ 30 3
  4. 4. A Business Intelligence Project TABLE OF FIGURESFigure 1.1: Indian Banking Structure.............................................................................................. 5Figure 1.2: Banking industry performance ..................................................................................... 6Figure 1.3: Major banking products and vendors ........................................................................... 7Figure 1.4: Data Warehouse structure ............................................................................................ 9Figure 3.1: SWOT Analysis .......................................................................................................... 13Figure 5.1: Project Specs .............................................................................................................. 21 4
  5. 5. A Business Intelligence Project CHAPTER1: BANKING INDUSTRY: INTRODUCTIONThe banking industry in India has a huge canvas of history, which covers the traditional bankingpractices from the time of Britishers to the reforms period, nationalization to privatization ofbanksand now increasing numbers of foreign banks in India.. Banking in India originated in thelast decades of the 18th century. The first banks were The General Bank of India, which startedin 1786, and Bank of Hindustan, which started in 1770; both are now defunct. The oldest bank inexistence in India is the State Bank of India, which originated in the Bank of Calcutta in June1806. It was one of the three presidency banks, the other two being the Bank of Bombay and theBank of Madras. The three banks merged in 1921 to form the Imperial Bank of India, which,upon Indias independence, became the State Bank of India in 1955.1.1 Structure Of Indian BankingIndustryBanking Industry in India functions under thesunshade of Reserve Bank of India - theregulatory,central bank. Banking Industrymainly consists of:  Commercial Banks  Co-operative BanksThe commercial banking structure in Indiaconsists of:  Scheduled Commercial Banks  Unscheduled Bank.Scheduled commercial Banks constitute thosebanks which have beenincluded in the SecondSchedule of Reserve Bank of India (RBI) Act,1934. Figure 1.1: Indian Banking Structure 5
  6. 6. A Business Intelligence ProjectBanking industry in India has also achieved a new height with the changing times. The useAccording to a Mckinsey report, the Indian banking sector is heading towards being a high-performing sector. Figure 1.2: Banking industry performanceAccording to an IBA-FICCI-BCG report titled ‘Being five star in productivity – road map forexcellence in Indian banking’, India’s gross domestic product (GDP) growth will make theIndian banking industry the third largest in the world by 2025. According to the report, thedomestic banking industry is set for an exponential growth in coming years with its assets sizepoised to touch USD 28,500 billion by the turn of the 2025 from the current asset size of USD1,350 billion (2010)”.1.2 Challenges Faced By Indian Banking IndustryDeveloping countries like India, still has a huge number of people who do not have access tobanking services due to scattered and fragmented locations. But if we talk about those peoplewho are availing banking services, their expectations are raising as the level of services areincreasing due to the emergence of Information Technology and competition. Since, foreignbanks are playing in Indian market, the number of services offered has increased and banks havelaid emphasis on meeting the customer expectations. 6
  7. 7. A Business Intelligence Project1.3 IT In Banking SectorInformation technology is one of the most important facilitators for the transformation of theIndian banking industry in terms of its transactions processing as well as for various otherinternal systems and processes. The various technological platforms used by banks for theconduct of their day to day operations, their manner of reporting and the way in which interbanktransactions and clearing is affected has evolved substantially over the years.1.3.1 Technological Development in Banks:Developments in the field of information technology (IT) strongly supports the growth andinclusiveness of the banking sector by facilitating inclusive economic growth .IT improves thefront end operations with back end and helps in bringing down the transaction costs for thecustomers.Important events in India:  Arrival of card-based payments- Debit, Credit card late 1980s and 1990s  Introduction of Electronic Clearing Services (ECS) in late 1990s  Introduction of Electronic Fund Transfer (EFT) in early 2000s  Introduction of RTGS in March 2004  Introduction of National Electronic Fund  Transfer(NEFT) as a replacement to Electronic Fund  Transfer/Special Electronic Fund Transfer in 2005/2006  Cheque transaction System (CTS) in 2007 Figure 1.3: Major banking products and vendors 7
  8. 8. A Business Intelligence ProjectData warehouse and mining: Banks are storing more information than ever before. Decisionmakers must have the right information at the right time to help them make more informed andintelligent decisions. The data in the operational database represents current transactions,however the decisions are based on a different time frame; that is there is no time component. Onthe other hand, data in operational databases are stored with a functional or process orientation,what really decision-makers would like to have is subject orientation of data, which facilitatesmultiple views for data and decision making. Data Warehousing and Data Mining are the rightsolution that makes the above possible. Use of Data Mining tools is being done for customersegmentation and profitability, marketing and customer relationship managementBanks need to optionally leverage technology to increase penetration, improve their productivityand efficiency, deliver cost-effective products and services, provide faster, efficient andconvenient customer service and thereby, contribute to the overall growth and development ofthe country. Technology enables increased penetration of the banking system, increases costeffectiveness and makes small value transactions viable. Besides making banking products andservices affordable and accessible, its simultaneously ensures viability and profitability ofproviders.1.4 Data Warehousing In Banking SectorData warehousing and data mining are relatively new terms for banking sector. These termshave gained significance with the growing sophistication of technology and the need forpredictive analysis with What if simulations. MIS in the present context of high availability ofvoluminous data on electronic media at diverse locations and on diverse platforms, has becomemore pertinent to banks’ decision-making process, thanks to the availability of new tools oftechnology such as data warehousing, data mining.Data warehousing which refers to collection of data from various sources (internal and external)and placing them in a form suitable for further processing which will gain critical importance inthe presence of data mining which refers to the process of extracting hidden information andgenerating several types of analytical reports which are usually not available in the originaltransaction processing systems. 8
  9. 9. A Business Intelligence Project1.4.1 Relevance of Data Warehousing and Data Mining for banks in IndiaBanking being an information intensive industry, building a Management Information Systemwithin a bank or an industry is a gigantic task. It is more so for the public sector banks whichhave a wide network of bank branches spread all over the country. It becomes all the moredifficult due to prevalence of varying degrees of computerisation. At present, banks generateMIS reports largely from periodic paper reports/ statements submitted by the branches andregional/zonal offices. Except for a few banks which have been using technology in a big way,MIS reports are available with a substantial time lag. Reports so generated have also a highmargin of error due to data entry being done at various levels and the likelihood of varyinginterpretations at different levels. Figure 1.4: Data Warehouse structureThe implication of adopting such technology in a bank would be as under: 1) All transactions captured at the branch level would get consolidated at a central location. Such a central location could be called the Data Warehouse of the concerned bank. For 9
  10. 10. A Business Intelligence Project this to happen, one of the requirements would be to establish connectivity between the branches on the one hand and the Data Warehouse platform on the other. 2) For banks with large number of branches, it may not be desirable to consolidate the transaction details at one place only. It can be decentralised by locating the services on regional basis. The regional Data marts as developed can provide mutual back-up and could be linked to the central Data Warehousing server so that for the purpose of MIS at the corporate level, data can be accessed from all the regional Data marts. 3) By way of data mining techniques, data available at various computer systems can be accessed and by a combination of techniques like classification, clustering, segmentation, association rules, sequencing, decision tree. Various ALM reports such as Statement of Structural Liquidity, Statement of Interest Rate Sensitivity etc. or accounting reports like Balance Sheet and Profit & Loss Account can be generated instantaneously for any desired period/date. 4) Significant cost benefits, time savings, productivity gains and process re-engineering opportunities are associated with the use of data warehouse for information processing. Data can easily be accessed and analysed without time consuming manipulation and processing. Decisions can be made more quickly and with confidence that the data are both time-relevant and accurate. Integrated information can be also kept in categories that are meaningful to profitable operation. 5) Trends can be analysed and predicted with the availability of historical data and the data warehouse assures that everyone is using the same data at the same level of extraction, which eliminates conflicting analytical results and arguments over the source and quality of data used for analysis. In short, data warehouse enables information processing to be done in a credible, efficient manner.Some of the data warehouses available in market areExadata (Oracle), TwinFin (Netezza/IBM),DB2 (IBM), SQM (Microsoft) etc. 10
  11. 11. A Business Intelligence Project CHAPTER 2: PUNJAB NATIONAL BANK: COMPANY PROFILEPunjab National Bank (PNB) is an Indian financial services company based in New Delhi, India.PNB is the third largest bank in India by assets. It was founded in 1894 and opened for businesson 12 April, 1895. It is currently the second largest state-owned commercial bank in India aheadof Bank of Baroda with about 5000 branches across 764 cities. The bank has been ranked 248thbiggest bank in the world by the Bankers Almanac, London. The banks total assets for financialyear 2007 were about US$60 billion. PNB has a banking subsidiary in the UK, as well asbranches in Hong Kong, Dubai and Kabul, and representative offices in Almaty, Dubai, Oslo,and Shanghai. PNB has the distinction of being the first Indian bank to have been started solelywith Indian capital that has survived to the present.With over 72 million satisfied customers and 5697 domestic branches, PNB has continued toretain its leadership position amongst the nationalized banks. The Bank enjoys strongfundamentals, large franchise value and good brand image. Over the years PNB has remainedfully committed to its guiding principles of sound and prudent banking irrespective of conditions.Bank has been earning many laurels and accolades in recognition to its service towards doinggood to society, technology usage and on its overall performance.Vision: "To be a Leading Global Bank with Pan India footprints and become a household brandin the Indo-Gangetic Plains providing entire range of financial products and services under oneroof".Mission:"Banking for the unbanked".Awards: Some of the major awards won by the Bank are the Best Bank Award, Most SociallyResponsive Bank by Business World-PwC, Most Productive Public Sector Bank, GoldenPeacock Awards by Institute of Directors, etc. 11
  12. 12. A Business Intelligence ProjectServices Offered:  Savings Fund Account  Doorstep Banking Services  Current Account  Cards  Fixed Deposit Schemes  Nomination Facilities  AUTO RENEWAL  Deceased claim cases  Credit Schemes  Centralised Banking Solution  Capital Gain Account Scheme-1988  View Your Loan Application StatusGrowth:Profit: Company posted a 12.7 per cent rise in net profit to Rs 1,246 crores during the firstquarter of the 2012-13 fiscal year due to growth in interest income.Business: Total Business of the Bank reached Rs. 673363 crores as against Rs. 5,55,005 croresin March 2011, showing a y-o-y growth of 21.3%.Delivery Channels:  Bank’s branch network stands at 5670 (including 6 extension counters).  Bank has 6009 ATMs and around 169 lakh card holders.  PNB Internet Banking Channels are witnessing a steady increase in usage with about 17 lakh internet banking users.Future Goal: The bank plans to gross a total business of Rs 10 lakh crores by 2013. It aims toincrease its customer base to 150 million by 2013, as per PNB chairman and managing directorK R Kamath (Economic Times, Jan 30, 2011). Company wants to expand its global operationsand has started by upgrading its Norway based office. 12
  13. 13. A Business Intelligence Project CHAPTER 3: PNB: THE BEGINNING OF IT STRATEGYBack in 2003, Punjab National Bank used a two-pronged strategy to IT-enable itself and supportpresent and future business needs. Earlier, Only 35 % of the banks business was computerizedand a number of smallsoftware packages ran on standalone PCs. In March 2000, the penetrationand use of IT was not very high at PNB. The bank used seven different software systems, whichran on 13 different flavors of UNIX, on standalone PCs. The 500-odd branches were notnetworked and only 35 percent of the banks business was computerized. The overall expertise inIT among users was low.The Central Vigilance Commission (CVC) issued a directive to thebank to computerize at least 70 percent of its business by December 2000. This prompted thebank to work out a strategy to tackle the daunting task in the short period of time.3.1 SWOT Analysis STRENGTHS WEAKNESSES 1) The bank personnel would be able to readily embrace 1) Different Unix OS flavors in different branches. the use of IT. 2) Different standalone financial applications on PCs at 2) An existing pool of qualified knowledge-based different branches. personnel would contribute largely to the IT initiatives. 3) Lack of interoperability due to disparity in systems. 3) The financial position of the bank was very sound. 4) Limited expertise on the software packages currently There would not be any constraint of funds to facilitate IT deployed. This increased dependence on vendors. initiatives. 5) Systems audits were pending. 4) The bank wasnt bound to too much legacy systems and equipment. 6) Most branches did not have a proper LAN in place. 7) There was almost no WAN connectivity. SWOT OPPORTUNITIES 1) More control through Dashboard for Senior Management covering all KPIs related to THREATS Deposits, Advances, Profits, NPAs, etc 2) Data Mining Infrastructure Capabilities for 1) Lack of continuous Support from Management mathematical and statistical modelling to determine and 2) Lack of consistent data for implementing the project predict correlation, patterns, and trends among a variety of measures. 3) Lack of support from Managers to go online and use of new technology 3)Compete more effectively with Private players through Customer Analytics covering Customer Profiling, Customer Segmentation, Lead Analysis & Cross Sell Analysis Figure 3.1: SWOT Analysis 13
  14. 14. A Business Intelligence Project3.2 IT StrategyIn 2000, to tackle the problem, PNB hired a consultant and devised a two-pronged plan of action.The plan comprised: 1. A short term goal - To meet the CVC deadline of 70 percent computerization. 2. A long term goal - To create a dependable core banking infrastructure and build a nationwide network to connect different branches to the core infrastructure.3.2.1Short Term GoalIn order to meet the CVC deadline the bank decided to deploy simple IT infrastructure so that itcould computerize 70 percent of its business within the deadline. The IT team decided toimplement an application, which could run on standalone PCs across its nationwide branches.The application vendor would have to provide nationwide support since the in-house IT teamcould not provide support at all branches.PNB chose a product from a company called Nelito. It was a DOS-based, Partial BranchAutomation application. Standalone versions were chosen since there werent LANs in place,and deployment of LANs at branches would take so long that the CVC deadline couldnt be met.The interface was simple in design, and thus easy for the bank personnel to use.3.2.2Hardware and TrainingThe bank selected two hardware vendors and the application software was embedded into thehardware to make them plug-and-play capable. Nelitos package was deployed at one branch ata time. And after each successful implementation at a branch, it was replicated at a newerbranch.Internal training sessions for the bank personnel were conducted with the help of 14 traininginstitutes. The source code of the product was tweaked to facilitate deployment. The IT team wasspecially trained to re-architect the source code, and make any modifications, improvements,value additions, and enhancements. Deployment at the selected branches was over by December2000. 14
  15. 15. A Business Intelligence ProjectThe bank requested CVC for an extension of the deadline and was granted time till March 2001.By March 2001, 70.60 percent of the banks business was computerized.3.2.3Long-term strategyIn the long-term, PNB wanted a technology that would consolidate all its business resources andsustain the banks future growth. It also wanted to create its own network, which would play avital role in its success. Three consultants were appointed to review technology options for long-term adoption. The verdict of the consultants was to deploy a centralized core bankingarchitecture. CHAPTER 4:CORE BANKING ARCHITECTUREOn 30 March 2001, the bank used the services of Infosys for the deployment ofFinnacle.Finnacle is a software package consisting of universal banking products which aredesigned to address the core banking, e-banking, Islamic banking, treasury, wealthmanagement and CRM requirements of retail, corporate and universal banks. It is developedby Infosys, and is one of the major players in the arena of core banking in Indian and Asianbanking domains.PNBselected a core team, which would be the heart of the project. Infosys trained 200-oddpersonnel from a core team over six months. The core team modified and customized thepackage according to its specific needs.It was then time to procure hardware. PNB purchased servers, security infrastructure, and storageequipment and decided to house it in its own central data center in New Delhi. A lot ofinfrastructure from Cisco has been used to build the data center.In April 2002 the bank rolled-out Finnacle in seven branches as a pilot venture. This was donebecause the bank had seven different application packages, and it wanted to ensure smooth 15
  16. 16. A Business Intelligence Projectmigration of the data into Finnacle. By mid May 2002, all data from other software wassuccessfully migrated into Finnacle.4.1 Culture and technology issuesPNB faced issues which were mostly cultural. Most staffers were used to working in a manualenvironment, and some had worked in standalone environments. In the new networkedenvironment, personnel at the node/counter didnt actually see the transactions updating in thevarious account books.This gave rise to a number of queries and suggestions from personnel. The bank consultedIDRBT(Institute for Development & Research in Banking Technology) and RBI to verify theimplementation success and it was reported that the deployment was absolutely correct. Aroundsix months later, the personnel felt that the environment change had done them good, and wasused to working on the systems.There were a few integration issues when migrating to Finnacle, but the in-house IT team wasable to resolve them all. The pilot for the initial seven branches was a test-bed for PNB. Theknowledge we gained from the pilot deployments helped it overcome the future issues.4.2 SystemsBefore deploying the core banking architecture, PNB used servers which were NT-based, fromIBM, and from other vendors. The bank conducted benchmarking tests for Finnacle on variousserver platforms. And it was satisfied with the performance of Suns hardware on Solaris. SunsFire servers, Solaris OS, and Oracles RDBMS are now in use.4.3Network designCisco tied up with PNB to evolve the network design and implement a nationwide networkbackbone to connect all its offices. Cisco assisted the bank in understanding and implementingthe various technologies associated with the project. The converged network infrastructure 16
  17. 17. A Business Intelligence Projectallowed PNB to standardize the applications and software needed to provide the bankingservices.4.4 Storage systemsThe bank has followed RBIs storage requirement guidelines. Provisions have been made to storetransaction data for around 10 years. In some cases, data is stored permanently. Around 164 Sunenterprise class servers are used in DAS architecture. The total capacity is of multiple TBs.4.5 InitiativesThese are some initiatives the bank decided to undertake in future:  Set up a data warehouse and a data mart. IDRBT has been involved as a consultant.  It may need to set up a NAS and SAN to consolidate its storage.  Disaster Recovery site may be built at Mumbai to create a replica of its data center. It will take around six months to be functional.  A call center will be set up as a CRM initiative, which uses information from the data warehouse with the help of the Base24 switch 17
  18. 18. A Business Intelligence Project CHAPTER 5:ENTERPRISE WIDE “Operational efficiency has been one of DATA WAREHOUSE: the key benefits of this implementation.” The project has plugged revenue leaks in PLANNING PNB’s system which Misra conservatively estimates in the range of Rs 10 Crore.Punjab National Bank (PNB) is thethird largest bank in India with apresence in nine countries. PNB hasmore than 5,200 Service outletsconnected through a Centralized Core Banking solution. It has global business of more than Rs4, 50,000 crores and serves over 37 million customers. PNB has continued to retain its leadershipposition among the nationalized banks. The bank enjoys strong fundamentals, large franchisevalue and good brand image. Besides being ranked as one of Indias top service brands, PNB hasremained fully committed to its guiding principles of sound and prudent banking. 18
  19. 19. A Business Intelligence Project5.1 RequirementsPunjab National Bank (PNB) had certain requirements which were not being fulfilled by theexistent system:  A unified view of business-related data.  Timely data compilation.  Timely monitoring and reporting of compliance.  Adherence to statutory reporting requirements.  Steps to prevent money laundering as per BASEL committee specifications.  Structured analysis of data for informed decision-making.  Monitoring of weak performance areas.  Improved customer service.  CRM with customer profiling and segmentation.  Support of the launch of new products and services.  An integrated source to feed in various downstream point solutions which require complex data processing. 19
  20. 20. A Business Intelligence Project5.2 Reasons for choosing EDWThe Enterprise wide Data Warehouse (EDW) project was initiated by the Bank for leveraging theBanks operational data available in multiple source systems to facilitate ready access to datarequired for regulatory, statutory reporting and for various other analytical purposes. This alsohelped in achieving operational efficiency and enhanced business decision support at variouslevels of the Bank. The EDW project also aimed at enabling PNB to meet business challengessuch as Basel II compliance for Risk Management, increase profitability through CustomerRelationship Management solution and implementation of Anti Money Laundering safeguards asper the regulatory guidelines.The project was implemented by Tata Consultancy Services Ltd. (TCS) on turnkey basis. Inorder to ensure smooth implementation of the project, it was being implemented in a phasedmanner. There was no impact on the functioning of the Bank during the implementation of theproject.The scale and complexity of the EDW project, which involved addressing the MIS and analyticalrequirements of 39 divisions and in addition to implementing complex analytical solutions madeit extremely challenging. 20
  21. 21. A Business Intelligence Project Project Specs Deployment Location: NewDelhi Team Size: 32 Tech Used: DB2 UDB, M1(Data Modeling), Data Stage, IBM-AIX, SAP-Business Objects, IBM Websphere, IBM p5 Series Servers on AIX, IBM 3800 Series & 3900 series Windows Servers Expected life: 8 years Figure 5.1: Project Specs5.3 Challenges during Implementation PhaseSince its humble beginnings in 1895 with the distinction of being the first Indian bank to havebeen started with Indian capital, PNB has achieved significant growth in business. PNB iscurrently ranked as the 3 largest bank in the country (after SBI and ICICI Bank) and has the2ndlargest network of branches.The technical challenges faced by PNB were as follows: 1) Addressing issue of data quality: A bank wide drive for cleansing of MIS master data, as well as the mapping of EDW master codes with the corresponding asset class, was initiated at branch level in a time bound manner. The data received from source systems often had unwanted characters or junk records, for which special Reject Handling routines have been implemented. 2) Data extraction challenges: Since data was extracted from various sources system, with their respective servers located at multiple locations, it required complex coordination with various divisions, for ensuring availability of various operational source systems was a challenge - in order to ensure that there is no disruption, data extraction needs to be carried out in a very small time window. The extraction of CBS data was done on daily 21
  22. 22. A Business Intelligence Project basis from designated CBS server which is used for MIS purpose by the Bank. Since this server was accessed by about Bank. Since this server was accessed by about 2000+ branches for generating various MIS reports, apart from testing of new/customized CBS as such there was considerable load on the server. The situation worsened during the month/quarter ends when there was heavy utilization of servers. The available time window during such situation was few hours during which data for EDW solution was extracted. Data was extracted from multiple, disparate source system which had different data extraction frequency. Maintaining account level details for data coming from two different source systems at different time interval was also a challenge.3) Data Loading challenges: Data transformation and loading is performed through IBM DataStage. Data loading of daily incremental data is done in three stages, taking about 8 hours. Ensuring smooth and timely loading of data, so as not to affect the business users, required concentrated effort by the data loading team. Pipeline parallelism and partition parallelism features of DataStage were implemented successfully for processing massive volume of data. Also at database level, Distributed Partitioning Feature (DFP) of DB2 has been implemented for meeting performance challenges. The use of LOAD utility instead of WRITE Utility improved the performance 11 folds for Bulk Load activities (especially during Historical Data Load). Special care was taken to handle Job Aborts in Bulk Load activities, to ensure that data load did not start afresh. During Bulk Load and Historical Data Load, Server overload due to limitations of Number of connections to DataStage was addressed as Data loading was being carried out 24x74) Integration of Customer Data Quality tool with the daily ETL Load: The challenge was in ensuring bi-way data flow between the ETL subsystem and the Customer Data Quality tool, to ensure that no time was lost in data transfer from one system to another. This has been achieved by integrating windows scripts with the ETL jobs through event driven synchronization5) Point Solutions Integration: Format of data requirements of point solutions vary from flat files, tables to xml files. Challenges in meeting size limitations of xml files have been met by using Parallelism. 22
  23. 23. A Business Intelligence Project 6) Customer Relationship Management (CRM): Information of prospective customers was not captured hence the possibility of converting such leads into actual business was very marginal.The issues faced during implementation process were successfully overcome. Ensuring cleandata in source systems is critical to the success of the EDW solution. The bank undertook a datacleansing exercise which is an ongoing activity and is being conducted through concentratedefforts by the Bank.The EDW project implementation was carried out in a phased manner, withseparate timelines for various solutions such as MIS, Risk Management, Anti MoneyLaundering, Customer Relationship Management, ALM and Funds Transfer Pricing.5.4 Solution Provided for various Business needs5.4.1MIS and Analytics:  Enterprise-wide Logical Data Model spanning Financial and Non-Financial Data Elements of the Bank to cover all MIS and DSS needs  MIS and DSS Requirements covering Retail Banking, International Banking, Credit Administration, Special Assets Management, Priority Sector and Lead Banking, Inspection and Audit, Merchant Banking, HR and Others  Financial Consolidation – Balance Sheet, Profit/Loss, Revenue  Dashboard for Senior Management covering all KPIs related to Deposits, Advances, Profits, NPAs, Priority Sector, Branch Profitability, Employee Performance across dimensions like Product, Industrial Sector, Customer, Organisation and Time  Data Mining Infrastructure Capabilities for mathematical and statistical modeling to determine and predict correlation, patterns, and trends among a variety of measures.5.4.2 Customer Relationship Management:  Transactional CRM covering Lead Management,  Activity Management, Campaign Management, Mass Business Partner Generation, Complaints Management, Integration with Alternate Delivery Channels like Call Centre & ATMs 23
  24. 24. A Business Intelligence Project  Customer Analytics covering Customer Profiling, Customer Segmentation, Lead Analysis & Cross Sell Analysis5.4.3 Risk Management:  Credit Risk, Market Risk, Operational Risk  Asset Liability Management and Funds Transfer Pricing  Anti-Money Laundering  Alerts, Cases, Statutory and Regulatory Reporting. 24
  25. 25. A Business Intelligence Project CHAPTER 6:ENTERPRISE DATA WAREHOUSE SOFTWAREPNB implemented Enterprise Data Warehouse and point solutions to meet these requirements.The software uses included  IBM DB2 Universal Data Enterprise – Server Edition – Version 9.1  IBM DB2 Data Warehouse – Enterprise Edition  IBM Tivoli Storage Manager – Extended Edition  IBM Tivoli Storage Manager – Storage Area Networks  IBM WebSphere DataStage Version 4.5.2  IBM WebSphere Application Server.PNB’s Date warehouse solution had capabilities such as data extraction from source systems,data modeling, data transformation and loading, reporting tools (queries and reports), and dataanalytics mining. The data warehouse hardware operating system was IBM – AIX (Unixoperating systems).6.1 Scope  2 million transactions processed through the data warehouse daily.  More than 10 source systems have been integrated and data is extracted and loaded on a daily basis. More than 20 lakh transactions are processed, loaded in base tables and summarized per day.  More than 350 reports have been published with drill down features for HO, circles and branches.  More than 40 dashboard reports are available for focussed monitoring and decision support of low-performing branches and circles. The reports feature convenient tools such as growth graphs, growth comparisons in percentage terms, traffic lights and pie charts.  The anti-money laundering solution has been implemented. More than 15 lakh transactions are monitored and around 6,000 alerts have been generated for further scrutiny. Suspicious transactions and cash transactions beyond the threshold limit are 25
  26. 26. A Business Intelligence Project monitored and reported to statutory agencies as required. The system also facilitates follow-up and closure of alerts.  A CRM system has been implemented in 1,024 branches.  An Operational Risk Management Solution (Operations Risk, Credit Risk and Market Risk) has been implemented and operational risk data from all the branches and offices is captured here. Risk assessment surveys are conducted online through the system. Advanced approach for Operational Risk as per BASEL guidelines has been implemented.6.2 BenefitsThe EDW project was a large and Compleximplementation. It has been a mammothexercise from many perspectives, be it thevolume of data , areas/user requirementscovered under the enterprise wideimplementation, or the number of users. Theenterprise wide implementation of EDW projectin a large PSU bank like Punjab National Bankwas unprecedented. The EDW solutionsuccessfully provided an integrated solution forRisk Management, Anti-money laundering, andCustomer Relationship management forenterprise wide users. EDW provided an end toend solution for Basel compliance for RiskManagement Division, covering OperationalRisk, Credit Risk and Market Risk. The RiskManagement solutions include solutions forCredit Risk (Standardized Approach), FIRB, AIRB (for Operational Risk), BIA, TSA and AMA,and for Market Risk (Standard Duration approach). Apart from this, Solutions for Transferpricing mechanism and Asset Liability Management is also being implemented. 26
  27. 27. A Business Intelligence Project6.3 Salient features of this project: 1) Unique Collaborative and Participative approach between PNB, IBM and TCS: A unique participative model between PNB, TCS and IBM has been setup to ensure successful implementation at PNB. 2) Customized BDW usage for Indian Banking industry: The BDW model provided by IBM has undergone customization in terms of adapting it to the Indian Banking scenario. The process of such a customization involving Indian Banking uniqueness has been done the first time in PNB. 3) Highly tuned and Scalable Infosphere DataStage Process: The InfosphereDataStage implementation includes the best practices involved in tuning the job and sequences to ensure load within the available window. 4) The implementation of the data warehouse has not only given PNB better control and insight into its operations, it’s also given management the perspective it requires to achieve the bank’s vision of 15 crores customers and business of Rs 10,00,000 crores by 2013. 5) Other benefits are: • 12 lakh man days saved per year. • 45,000 leads have been converted into B 1,050 crores of business. • Provided the support PNB required to focus on customized products and services to a specific segment of customers. 27
  28. 28. A Business Intelligence Project CHAPTER 7: FUTURE SCOPEThere are many factors which will continue to influence and shape of the banking industry,These include data quality, rising storage and network requirements, IT capabilities and businessrequirements. Keeping these factors in mind, we suggest use of upcoming trends in businessintelligence which if adopted can bring about a radical change in information management. 1) BI in the Cloud The data can be transferred to the cloud and once data has been transferred to the Cloud, there are numerous cost-effective BI and big data tools available for organisations to take advantage of, along with the obtaining the desired reach. 2) Mobile BI Mobile business intelligence offers huge advantages for banking organisations, particularly those with increasingly mobile and remote workforces. It means that staff and management are never disconnected from the tools that help them make business decisions. 3) Analytics It uses algorithms to search for patterns and explanations. It looks at historical data to predict future activity for better business decision making. Analytics will help companies differentiate themselves, it will allow them to run more efficiently, make the most of their customers and increase profitability. Analytics provides organisations with actionable intelligence. While BI has traditionally been hard to create a business case for, analytics has a direct correlation to an organisation’s top or bottom line. The three biggest trends surrounding analytics the industry are: Optimisation—the combination of business rules for optimised decision management; consumable analytics—the visual presentation of increasingly complex data; and new data analytics—the analysis of new types of data, such as social media, location information, etc. 28
  29. 29. A Business Intelligence Project 4) In-memory analytics In-memory analytics tools—such as Qlikview, Spofire and Tableau—allow for the querying and analysing of data from a computer’s RAM, resulting in quick and simple data exploration for BI and analytic applications. Rather than relying on centrally controlled, monolithic data warehouses, users are able to download large amounts (up to 1 terabyte) of data onto their own computer and explore that information for proving theories and making business decisions throughout an organisation. Given the speed, ease and affordability with which these tools can put power back into the hands of the users. 5) The Agile approach to BI An Agile approach can be used to incrementally remove operational costs and if deployed, can return great benefits to any organisation. Agile provides a streamlined framework for building business intelligence/data warehousing (BIDW) applications that regularly delivers faster results using just a quarter of the developer hours of a traditional waterfall approach. 6) Anti-Money Laundering Software linked with Data Warehouse Transaction monitoring systems help fight money laundering by identifying uncharacteristic deposits or withdrawals, identification of suspicious transactions can help businesses file Suspicious Activity Reports, or SARs.. 29
  30. 30. A Business Intelligence Project REFERENCEShttps://www.pnbindia.in/new/Upload/English/Financials/PDFs/Microsoft%20Word%20-%20Draft%20Press%20Release%20Q4-%202011-12%20_2_.pdfhttp://articles.economictimes.indiatimes.com/2012-07-27/news/32889510_1_net-profit-pnb-q1-net-npahttp://articles.economictimes.indiatimes.com/2011-01-30/news/28425595_1_deposit-rates-dana-bank-credit-growthhttps://www.pnbindia.in/En/ui/Profile.aspxhttp://www.thoughtwareworldwide.com/downloads/BoI_F.pdfhttp://www.tomsitpro.com/articles/data_warehouse-business_intelligence-ibm_netezza-oracle_exadata-twinfin,2-249.htmlhttp://www.rbi.org.in/SCRIPTS/PublicationReportDetails.aspx?UrlPage=&ID=27http://ijcta.com/documents/volumes/vol2issue4/ijcta2011020425.pdfhttp://www.ijcst.com/vol22/1/vivek.pdfhttp://www.isrj.net/Sep/2011/Sep/Sawanth.pdfhttp://www.dnb.co.in/bfsisectorinindia/BankC6.asphttp://cscjournals.org/csc/manuscript/Journals/IJBRM/volume3/Issue1/IJBRM-64.pdfhttp://stockshastra.moneyworks4me.com/learn/indian-banking-industry-future-prospects-and-sector-overview/http://en.wikipedia.org/wiki/Banking_in_Indiahttp://www.cio.in/case-study/pnb-deploys-enterprise-wide-data-warehousehttp://202.138.100.134/cio100-2011/ajay-misra-chief-information-officer-punjab-national-bankhttp://pcquest.ciol.com/content/implementation2010/2010/110070118.asphttp://pcquest.ciol.com/content/implementation2010/2010/110060104.asphttp://www.networkmagazineindia.com/200305/tech4.shtml 30

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