Analysing green initiatives effect on operating profit

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Analysing green initiatives effect on operating profit

  1. 1. Business Statistics Project Report Analysing and Forecasting the Impact of Green Initiatives on the Operating Profits of Banks Section A Group 2 Abhishek Verma 3A Akansha Kumari 4A Devansh Doshi 16A Manoj Kumar Yadav 25A Shubham Jain 47A Thomas Chandy 51A
  2. 2. Contents Title Page No. 1. Introduction…………………………………………………………………………………………… 1 2. Key Statistics………………………………………………………………………………………… 2 3. Recent Developments…………………………………………………………………………… 4 4. Government Initiatives and the Road Ahead…………….………………………… 5 5. Mobile Banking……………………………………………………………………………………… 6 6. Green Banking & Other Green Initiatives in Banking. ………………………. 7 7. Analysis of the Impact of Green Initiatives……………….………………………… 9 8. Forecasting using Exponential Smoothing…………………………………………… 15 References
  3. 3. Page 1 Chapter 1 Introduction As per July 2013, India’s banking industry stands at Rs 77 trillion (US$ 1.30 trillion) and is well at par with global standards and norms. Prudent practises and conventional framework adopted by the regulator, Reserve Bank of India (RBI), have insulated Indian banks from the global financial crisis. The country has 87 scheduled commercial banks with deposits worth Rs.71.6 trillion (US$ 1.21 trillion) as on 31 May, 2013. Of this, 26 are public sector banks, which control over 70 per cent of India’s banking sector, 20 are private banks and 41 are foreign banks. Of the total, 41 banks are listed with a total market capitalisation of Rs.9.35 trillion (US$ 158.16 billion) as per the recent statistics. [1] Figure 1.1: The Structure of the Indian Banking Industry
  4. 4. Page 2 Chapter 2 Key Statistics “Quarterly Statistics on Deposits and Credit of Scheduled Commercial Banks – December 2012” provides information on aggregate deposits and gross bank credit of Scheduled Commercial Banks (SCBs) as on December 28, 2012 based on branch-wise data received from all SCBs (including Regional Rural Banks) through Basic Statistical Return (BSR)-7. The number of banked centres of SCBs stood at 37,530 covering 101,567 offices of SCBs. Of these centres, 29,079 were single office centres and 72 centres had 100 or more bank offices. The growth (yoy) in aggregate deposits at 11.3 per cent in December 2012 was lower as compared with 13.6 per cent in September 2012 as well as with 17.3 per cent a year ago. Population group-wise, aggregate deposits of rural, semi-urban, urban and metropolitan branches grew by 16.0 per cent, 16.7 per cent, 16.0 per cent and 7.5 per cent, respectively in December 2012. The growth in gross bank credit at 14.7 per cent in December 2012 was lower than 15.1 per cent in September 2012. The growth in gross bank credit extended by rural branches in December 2012 was influenced by shifting of some large credit accounts from metropolitan to rural branches. Adjusted for such large accounts, growth in gross bank credit for rural and metropolitan branches stood at 13.6 per cent and 13.9 per cent, respectively. Growth in gross bank credit of semi-urban and urban branches was at 21.7 per cent and 14.2 per cent, respectively. The top hundred centres, arranged according to the size of deposits accounted for 68.0 per cent of the aggregate deposits and the top hundred centres arranged according to the size of gross bank credit accounted for 77.1 per cent of gross bank credit. Nationalised Banks accounted for 51.5 per cent of the aggregate deposits, while State Bank of India and its Associates accounted for 22.5 per cent. The share of New Private Sector Banks, Old Private Sector Banks, Foreign Banks, and Regional Rural Banks in aggregate deposits was 13.8 per cent, 5.0 per cent, 4.4 per cent and 2.9 per cent, respectively. Nationalised Banks accounted for the highest share of 49.9 per cent in gross bank credit followed by State Bank of India and its Associates (22.6 per cent) and New Private Sector Banks (14.8 per cent). Foreign Banks, Old Private Sector Banks and Regional Rural Banks had relatively lower shares in the gross bank credit at 5.1 per cent, 4.9 per cent and 2.6 per cent, respectively.
  5. 5. Page 3 The All-India credit-deposit (C-D) ratio of all SCBs stood at 77.7 per cent in December 2012. Among the States/Union Territories, the highest C-D ratio was observed in Tamil Nadu (124.2 per cent) followed by Chandigarh (123.6 per cent) and Andhra Pradesh (112.6 per cent). At the bank group level, C-D ratios of Foreign Banks (91.4 per cent), New Private Sector Banks (83.6 per cent), and SBI and its Associates (78.2 per cent) were higher than the all-India average. The distribution of the offices of SCBs by size of deposits showed that offices with deposits of Rs.100 million or more accounted for 70.3 per cent of the bank offices, 97.8 per cent of aggregate deposits and 94.7 per cent of gross bank credit. The offices with outstanding gross bank credit of Rs.100 million or more accounted for 48.4 per cent of the offices, 80.0 per cent of deposits and 95.7 per cent of gross bank credit. [2] India's foreign exchange (forex) reserves stood at US$ 280.19 billion for the week ended July 12, 2013, according to data released by the central bank. The value of foreign currency assets (FCA) - the biggest component of the forex reserves – stood at US$ 252.14 billion, according to the weekly statistical supplement released by the RBI. The number of mobile banking transactions doubled to 5.6 million in January 2013 from 2.8 million in January 2012. The value of these transactions increased three-times to Rs 625 crore (US$ 105.73 million) during the month from Rs 191 crore (US$ 32.31 million) in the corresponding month last year. Moreover, non-resident Indians (NRIs) parked deposits aggregating US$ 14.18 billion in the financial year ended March 2013, depicting an increase of 19 per cent over the previous year. [3]
  6. 6. Page 4 Chapter 3 Recent Developments India's leading infrastructure development and finance company Infrastructure Leasing & Financial Services Limited (IL&FS), has inked a Memorandum of Understanding (MoU) with Industrial and Commercial Bank of China (Asia) Limited (ICBC (Asia)), for mutual cooperation in infrastructure project development services and financial services related thereto. The agreement envisages a scope of cooperation between the two financial entities for providing infrastructure project development services, including financial services relating thereto, trade, corporate banking, investment banking and treasury related services, debt raising, advisory and other form of permissible economic cooperation for such projects across Northern and Eastern Asia and is expected to facilitate more business opportunities for both the institutions in these geographies. Meanwhile, Standard Chartered Bank has announced that it will buy US-based Morgan Stanley’s domestic private wealth management business. The deal, to be completed by the end of 2013, would boost Standard Chartered’s private wealth assets under management by 25 per cent or about US$ 750 million. Marking another milestone in achieving financial inclusion, Vodafone India and ICICI Bank have partnered to launch a mobile money transfer and payment service, M- Pesa. The service will allow customers to transfer money to any mobile phone in India, remit funds to bank accounts, deposit and withdraw cash from designated outlets, pay utility bills, and shop at select merchant establishments. The new service will initially be offered in West Bengal, Bihar and Jharkhand through 8,300 authorised agents. It will be made available across India by 2014-15. Public sector lender SBI intends to make a strong position in refinance market in 2013. The bank offers lowest lending rates for buying homes. The fast growing market of ‘home loans transferred from other banks’ consists 25 per cent of the total home loans disbursed by the bank in FY13. SBI made Rs 30,000 crore (US$ 5.08 billion) of home loans in 2012-13. Meanwhile, US-based Customers Bancorp Inc (CUBI) has plans to infuse US$ 51 million in multiple securities of Religare Enterprises Ltd. Religare is currently aspiring for a banking licence to enter the banking industry. The investments will take place through a combination of primary and secondary market transactions. [4]
  7. 7. Page 5 Chapter 4 Government Initiatives and the Road Ahead India’s central bank is about to propose fundamental changes in the structure of Indian banking industry. The suggestions include consolidation of some large banks to create two-three global ones, setting up of smaller banks, separate licenses for specific banking operations instead of a single universal one, continuous licensing for new banks and conversion of some urban cooperative banks into full-fledged commercial banks. Also, the RBI has, for the time being, relaxed the norm that stipulates non- banking finance companies (NBFCs) to have a minimum gap of six months between two non-convertible debentures (NCDs) issues. The move is aimed at streamlining the process of moving into a more robust asset-liability management framework in a non- disruptive manner. In order to boost retail participation in sovereign debt, RBI had allowed direct access to bond holders in the Annual Monetary and Credit Policy for 2012-13. To further enhance the participation, it has launched the web-based platform at www.ndsind.com which is being supported and run by the Clearing Corporation of India Limited (CCIL). Retail participants can now manage their Government bond holdings directly and can also initiate trade in the secondary market through the web portal. Currently, banks and financial institutions are the major investors in Government debt. Furthermore, in order to ensure expansion of ATMs in smaller cities across India, RBI has issued final guidelines allowing non-bank entities to set-up, own and operate ATM. RBI has also made things easier for customers who change jobs or locations. Previously it was difficult for them to shift their bank account to the new location as they were asked to open a fresh account or undergo the full know your customer (KYC) process again. RBI has now made it compulsory for banks to allow easy transfer of accounts from one branch to another by having a central customer ID. It would facilitate portability of accounts and ensure that all customer information is centralised. Over the past few years, Indian banking system has majorly went revamp and modernisation. The new infrastructure adopted by the banking system is mainly comprised of information technology (IT) products and services. Indian banking and securities companies will spend around US$ 422 billion on IT products and services in 2013. That will imply a 13 per cent rise from Rs 37,300 crore (US$ 6.31 billion) spent in 2012. IT services is the largest overall spending category at Rs 13,200 crore (US$ 2.23 billion) in 2013. This ensures that IT service providers lay a strong focus on the financial services sector, according to a study by research and analyst firm Gartner. [5]
  8. 8. Page 6 Chapter 5 Mobile Banking After the success of online banking, mobile banking is the next revolutionary step which has attracted huge attention from all over the country Mobile banking can perform all the banking functions such as money transfer, credit card payment, bill payment, account updates and other transactions The banking industry averages about 3 lakh transactions per day through mobile banking and most big banks have seen 100% growth in mobile banking with more services likely to be introduced in the near future The leading banks in the space are ICICI Bank, HDFC and SBI. Some of the other key players that will join the race in the future include Axis Bank, Syndicate Bank, Canara Bank and Bank of Baroda Many customer segments are clearly getting comfortable with using mobile banking. It is particularly true of the Generation-Y group (18-32-year olds) who are three times more likely to adopt mobile banking than older users Overall the growth in mobile banking that has taken place in the country till date, though at a rapid pace, is yet to reach the critical mass that will enable it to deliver on its promise of taking banking, including payment services, at a cheaper, secure and seamless manner to the existing and potential customers. “Banks providing local offers through their mobile banking apps can be a huge value addition and in the next two years banks are expected to leverage on this trend” –A Krishna Kumar, Managing Director, Group Executive – National Banking, SBI Figure 5.1: Key Mobile Banking Services (Source: PwC)
  9. 9. Page 7 Chapter 6 Green Banking & Other Green Initiatives in Banking While the banking industry is undergoing computerization, networking and offering of online banking is naturally gaining momentum. Besides several benefits of computerization like speed, accuracy, ambience, efficient handling of sizeable business etc., there is a factor like paperless business resulting in waste management, eco friendliness and pollution control. Banks can do much more to help the environment than just promote online banking. A truly green bank can reduce their carbon footprint by building more efficient branches implementing more energy- efficient operational procedures, offering transportation services for their employees and carefully screening their lending in environment-sensitive industries. Banks can also support eco-friendly groups, offer green lending and raise money for local environment initiatives. Banks that go to these significant lengths to be eco-friendly are a little more difficult to find than the banks that claim to be green by merely offering online services. Banks that offer rate incentives on CDs, money market accounts, online savings accounts and checking accounts for online banking also help the green banking cause by rewarding online banking customers. It takes a little bit of an incentive to convert some people away from paper statements and branch banking. Pravakar Sahoo and Bibhu Prasad Nayak (2008) have stated that since banking sector is one of the major stake holders in the Industrial sector, it can find itself faced with credit risk and liability risks. Further, environmental impact might affect the quality of assets and also rate of return of banks in the long-run. Thus the banks should go green and play a pro-active role to take environmental and ecological aspects as part of their lending principle, which would force industries to go for mandated investment for environmental management, use of appropriate technologies and management systems. The authors suggested that possible policy measures and initiative to promote green banking in India. Suresh Chandra Bihari (2011) explained that Green Banking involves promoting environmental and social responsibility. It starts with the aim of protecting the environment where banks consider before financing a project whether it is environment friendly and has any implications for the future. A company will be awarded a loan only when all the environmental safety standards are followed. Nigamananda Biswas (2011) interpreted Green Banking as combining operational improvements, technology and changing client habits in market place. Adoption of greener banking practices will not only be useful for environment, but also benefit in greater operational efficiencies, a
  10. 10. Page 8 lower vulnerability to manual errors and fraud, and cost reductions in banking activities. Alice Mani (2011) indicated that as Socially Responsible Corporate Citizens (SRCC), banks have a major role and responsibility in supplementing governmental efforts towards substantial reduction in carbon emission. Bank’s participation in sustainable development takes the form of Green Banking. Indian Banks can adopt green banking as business model for sustainable banking. Some of following strategies little reflected in their banking business must be adopted by banks. 1. Carbon Credit Business: Under the Kyoto Protocol, all nations must reduce greenhouse gases emission and reduce carbon to protect our environment. These emissions must be certified by Certified Emission Reductions (CERs), commonly known as carbon credit. The Indian Bank may start this business as in London the business of carbon credit is around 30 billion Euro. 2. Green Banking Financial Products: Banks can develop innovative green based products or may offer green loans on low rate of interest. As Housing and Car loan segments are the main portfolio of all banks so they adopt green loans facility. SME loans on the basis of National Environmental Policy and its certification ISO 14000 3. Green Mortgages: Green mortgages allow home buyers to add as much as an additional 15% of the price of your house into your loan for upgrades including energy-efficient windows, solar panels, or water heaters 4. Green Credit Cards: A green credit card allows cardholders to earn rewards or points which can be redeemed for contributions to eco- friendly charitable organizations. These cards offer an excellent incentive for consumers to use their green card for their expensive purchases 5. Paperless Banking: All banks are shifting on CBS or ATM platform, also providing electronic banking products and services. So there is ample scope for banks to adopt paperless or lee-paper banking. Private and foreign banks are using electronics for their office correspondence but still in PSU banks they are using huge paper quantity 6. Energy Consciousness: Banks have to install energy efficient equipment in their office, use CFL and avoid wrong utilization of these equipment. Banks have to transform this green banking in Hardware, waste Management in office, Energy efficient Technology products. Banks can Donate Energy Saving Equipment to school, hospitals etc. 7. Using Mass Transportations Systems: Banks have to provide common transport for groups of officials posted at one office 8. Green Buildings: Banks have their residential houses, branches or ATMs, so bank may adopt green building to protect our environment 9. Plantation: Most of the banks are conducting plantation program in the rainy season to save our environment. They plant trees, grass etc. at local gardens, schools or colleges and shows that banks are very careful about environment. [6]
  11. 11. Page 9 Chapter 7 Analysis of the Impact of Green Initiatives In analysing the impact of one of the key green initiative of e- Governance, volume of transactions is a very important consideration over the Value of the transactions since it is volume of transaction which gives clarity on how effectively the initiative is working towards reducing the consumption of papers in day-to-day functioning of the banks. Also, the banks need not have to trade off their operating profits while following the green initiative practices since, the implementation of Green practices are actually contributing positively to the operating profits of the banks. Let us analyse how the initiatives are impacting the business across the banks – Nationalized Banks, Private Banks and Foreign Banks. Here State bank group haven’t been considered for the analysis since the State Bank group falls under outlier category due to its sheer volume of business linked to the huge number of branches with very high market penetration. In order to understand the relationship between the operating profit and the volume of transactions from RTGS, NEFT, Mobile banking and ATM, multiple regression could be used considering the operating profit in Rs.Crore as dependent variable and the other variables as independent variables. Ideally the transaction value would be used as independent variables from the business perspective but the volume of the transactions need to be used for analysing the impact of green initiative. The data has been taken from the RBI website. Refer references 8, 9, and 10 for the links. The data is for the fiscal year 2012-13. (A) Nationalized Banks ATM Credit Card Transactions RGTS (Outwar ds) Mobile Transactions NEFT (Outwa rds) Operating Profit in INR Lakhs Allahabad Bank 0 2280 14656 3320180 376392 Andhra Bank 91667 76740 168453 2111342 276723 Bank of Baroda 13011 1445 368843 5364281 907378 Bank of India 109547 7116 7642 4452515 274900 Bank of Maharashtra 42445 1445 2430 1897095 214871 Canara Bank 105947 58484 68542 5743693 599900 Central Bank of India 3128 95402 4027 3297572 3172570 Corporation Bank 14947 101914 48554 3791892 303701
  12. 12. Page 10 Dena Bank 0 41427 1260 947656 173886 Indian Bank 29081 81372 25241 3577430 306063 Indian Overseas Bank 33684 111 10873 6310218 381701 Oriental Bank of Commerce 0 134121 22195 2422114 369069 Punjab and Sind Bank 0 2058 49278 216237 93885 Punjab National Bank 25744 265346 103984 7162681 1090737 Syndicate Bank 21414 7953 459476 2955310 344958 UCO Bank 0 5562933 61649 1694578 335708 Union Bank of India 9759 61922 61649 7074423 558270 Vijaya Bank 47158 5562933 51597 1447351 112230 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change 1 .364 a .132 -.135 7.48884E5 .132 .496 4 13 .739 ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression 1.113E12 4 2.782E11 .496 .739 a Residual 7.291E12 13 5.608E11 Total 8.404E12 17 Coefficients Model Unstandardized Coefficients Standardized Coefficients t Sig. 95% Confidence Interval for B B Std. Error Beta Lower Bound Upper Bound 1 (Constant) 401984.919 419785.964 .958 .356 -504907.521 1308877.359 RGTS -.033 .108 -.084 -.307 .764 -.267 .201 NEFT .097 .094 .287 1.024 .325 -.107 .300 Mobile -.328 1.434 -.060 -.229 .822 -3.426 2.770 ATM -4.749 5.095 -.246 -.932 .368 -15.756 6.259
  13. 13. Page 11 Analysis: A low R square value indicates that there is weak correlation between operating profit and RGTS, NEFT, ATM credit cards, and mobile banking. The independent variable can explain a meagre 13.2% variation in the dependent variable. Anova test indicates that there is no statistically significant relationship between profit and green initiatives. The null hypothesis is rejected outright. The standardized coefficients indicate low and negative correlation between profits and green initiatives such as mobile banking and ATM credit cards. A near zero correlation of operating profits and mobile banking indicates that mobile banking is yet to contribute to profits. This can be perhaps due to low penetration of mobile phones and also their low usage as an banking medium. Most nationalized banks tend to have a rural bias when it comes to areas of operations. They are guided by the governments to increase reach in rural areas. The Indian attitude towards debt is inclined towards avoidance. And hence, acceptance of credit cards is lower in rural areas. This impacts the profits accrued due to credit cards. (B) Private Banks ATM Credit Card Transactions RGTS (Outwards) transaction Mobile Transactions NEFT (Outwards) transactions Operating Profit in INR Lakhs Catholic Syrian Bank Ltd. 0 8584 832 285087 3275 City Union Bank Ltd 0 355 28901 2155591 37420 Dhanalaxmi Bank Ltd. 80 41 6192 426581 5140 Federal Bank Limited 0 41 245777 3976239 145956 ING Vysya Bank 0 111 37276 4485230 99270 Karnataka Bank Ltd. 0 2055 98018 988008 63533 Karur Vysya Bank 0 1689 34754 1445523 84883
  14. 14. Page 12 Ltd Lakshmi Vilas Bank Ltd. 0 50784 5319 642258 25115 Ratnakar Bank Ltd. 0 20 101061 94666 9253 South Indian Bank Ltd 0 437 271074 1326816 88848 Tamilnadu Mercantile Bank Ltd. 0 6637 31802 813178 69000 Developme nt Credit Bank Ltd. 1225 4 6192 426581 12600 HDFC Bank Ltd. 896620 26 841816 57253380 15440 ICICI Bank Ltd. 96980 265656 6554067 39608929 1319900 IndusInd Bank Ltd 5805 81372 37276 4870557 191289 Kotak Mahindra Bank Ltd 31325 96964 5319 7550902 332734 Axis Bank Ltd. 97402 312236 4410330 34075642 930300 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change 1 .990 a .980 .974 57002.08786 .980 160.362 4 13 .000 ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression 2.084E12 4 5.211E11 160.362 .000 Residual 4.224E10 13 3.249E9 Total 2.126E12 17 Coefficients Model Unstandardized Coefficients Standardized Coefficients t Sig. 95% Confidence Interval for B B Std. Error Beta Lower Bound Upper Bound 1 (Constant) 17126.890 19336.829 .886 .392 -24647.789 58901.569 RGTS .026 .011 .096 2.320 .037 .002 .050 NEFT .032 .007 1.505 4.606 .000 .017 .047 Mobile .025 .038 .125 .656 .523 -.057 .106
  15. 15. Page 13 ATM -2.072 .405 -1.230 -5.119 .000 -2.946 -1.197 Analysis: A high R square value indicates that there is strong correlation between operating profit and RGTS, NEFT, ATM credit cards, and mobile banking. The independent variables can explain 98% variation in the dependent variable. Anova test indicates that there is statistically significant relationship between profit and green initiatives. The null hypothesis is not rejected outright. The standardized coefficient of mobile banking is positive. This indicates that mobile banking is positively contributing to operating profits. The standardized coefficient for ATM credit card transactions is negative. This indicates that credit card ATM banking service isn’t positively contributing to profits. We can see that there are very few banks that provide credit card ATM services. If we observe similar data for debit card transactions at the RBI website, we will find that debit card transactions are huge in volumes. This confirms that people largely prefer debit over credit cards. There are numerous reasons for it. The private banks are really notorious about late charges, other processing fees, and high rate of interests in case of delays in payments. Also, the general attitude towards debt is not favourable. People would rather spend their own money rather than money on credit. Comparison of Nationalized and Private Sector banks: Legacy Costs Data shows that private banks that propped up after liberalization already started building up their banking services using technology and ATMs. Hence, they didn’t have to make a transition into technology. On the other hand, you have the nationalized banks that were under government control for a long time. Also, they had recruited a lot of people. So, they already have to bear the burden of huge salary costs. And then a transition to technology in general added to a lot of costs. They also didn’t have the liberty to lay off staff. Hence, the workforce increased. This increased the operational costs, and hence affected the
  16. 16. Page 14 operational profits. Hence, nationalized banks have to bear the brunt of this legacy costs. The reference to legacy cost is in terms of continuing to pay employees irrespective of their need at work. Also, there is a general perception that makes people feel that private banks connect more with their tech savvy consumers and they are better suited for its needs.
  17. 17. Page 15 Chapter 8 Forecasting using Exponential Smoothing Exponential smoothing is a technique that can be applied to time series data, either to produce smoothed data for presentation, or to make forecasts. The time series data themselves are a sequence of observations. The observed phenomenon may be an essentially random process, or it may be an orderly, but noisy, process. Whereas in the simple moving average the past observations are weighted equally, exponential smoothing assigns exponentially decreasing weights over time. Also, as the name suggests it smoothens the data over time, removes any major cyclic variations and random spikes and dips. Exponential smoothing is commonly applied to financial market and economic data, but it can be used with any discrete set of repeated measurements. The raw data sequence is often represented by {xt}, and the output of the exponential smoothing algorithm is commonly written as {st}, which may be regarded as a best estimate of what the next value of x will be. When the sequence of observations begins at time t = 0, the simplest form of exponential smoothing is given by the formulae: Where α is the smoothing factor, and 0 < α < 1. Allahabad Bank has been considered for the demonstration purpose for forecasting the transactions that can be expected for the key green initiatives – eGovernance. Here based on the past trends in the monthly data, volumetric data for the month of June has been forecasted for NEFT, RTGS, Mobile transactions, and ATM Debit card transactions. Exponential Smoothing method has been followed for the forecasting with a smoothing coefficient of 0.4. A low coefficient is chosen to remove the random spikes and dips. This is in line with the service sector industries especially banking where the industry scenario is not that dynamic and a lot of future issues are dependent on the past performances. The data is from December 2012 to May 2013.
  18. 18. Page 16 The same forecasting method could be applied to any banks and this forecasting method helps in scheduling the operational process well in advance. Table 8.1: Forecasting of ATM Debit Card and NEFT transactions ATM Debit Card Transactions NEFT (Outwards) Original Forecasted Original Forecasted December 2617816 2617816 328658 328658 January 2727510 2661693.6 372594 346232 February 2527755 2608118.16 347737 346834 March 3089665 2800736.9 468087 395335 April 3028020 2891650.13 319527 365012 May 3039185 2950664.08 422001 387808 June(F) 2986072.45 401485 Figure 8.1: Forecasting ATM Debit Card Transactions using exponential smoothing (α=0.4) 0 500000 1000000 1500000 2000000 2500000 3000000 3500000 VolumeofTransactons ATM Debit Card Transactions Original Forecasted
  19. 19. Page 17 Figure 8.2: Forecasting NEFT Transactions using exponential smoothing (α=0.4) Table 8.2: Forecasting of RGTS and Mobile Transactions RGTS (Outwards) Mobile Transactions Original Forecasted Original Forecasted December 80863 80863 1466 1466 January 85664 82783.4 1344 1417.2 February 78692 81146.84 1272 1359.12 March 101038 89103.304 1524 1425.072 April 92975 90651.982 1295 1373.043 May 96790 93107.189 1167 1290.626 June(F) 94580.314 1241.176 Figure 8.3: Forecasting ATM Debit Card Transactions using exponential smoothing (α=0.4) 0 50000 100000 150000 200000 250000 300000 350000 400000 450000 500000 VolumeofTransactions NEFT (Outwards) Original Forecasted 0 20000 40000 60000 80000 100000 120000 VolumeofTransactions RGTS (Outwards) Original Forecasted
  20. 20. Page 18 Figure 8.4: Forecasting ATM Debit Card Transactions using exponential smoothing (α=0.4) 0 200 400 600 800 1000 1200 1400 1600 1800 VolumeofTransactions Mobile Transactions Original Forecasted
  21. 21. Page 19 References [1] http://www.ibef.org/industry/banking-india.aspx [2] http://rbidocs.rbi.org.in/rdocs/Publications/PDFs/HIGH _02072013.pdf [3] http://www.dinodiacapital.com/pdfs/Indian%20Bankin g%20Industry%20- %20Rising%20Above%20the%20Waves,%20January% 202013.pdf [4] http://greenbankreport.com/ [5] http://www.mbaskool.com/business- articles/finance/899-banks-going-green.html [6] http://gogreenindia.co.in/special-reports.php [7] http://dbie.rbi.org.in/DBIE [8] http://www.rbi.org.in/scripts/NEFTView.aspx [9] http://www.rbi.org.in/scripts/ATMView.aspx [10] http://www.rbi.org.in/scripts/statistics.aspx

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