Analysing green initiatives effect on operating profit

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

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

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

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.

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]

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]

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]

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)

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

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]

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

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 .364a .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 .739a

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

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

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 .990a .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

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

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.

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.

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

Vo

lum

e o

f T

ran

sact

on

s

ATM Debit Card Transactions

Original

Forecasted

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


0

50000

100000

150000

200000

250000

300000

350000

400000

450000

500000

Vo

lum

e o

f T

ran

sact

ion

s NEFT (Outwards)

Original

Forecasted

0

20000

40000

60000

80000

100000

120000

Vo

lum

e o

f T

ran

sact

ion

s

RGTS (Outwards)

Original

Forecasted


0

200

400

600

800

1000

1200

1400

1600

1800

Vo

lum

e o

f T

ran

sact

ion

s Mobile Transactions

Original

Forecasted

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

Analysing green initiatives effect on operating profit

Business

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