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Integrating Environmental Risk into Bank Credit Processes: A South

African Context

A.Bimha (Msc)

Proposal to submit a research proposal in fulfilment of the requirements for the degree

of Doctor of Commerce in Business Management at the University of South

Africa

Promotor: Professor H. Mynhardt

June 2013

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Contents 1. Background/Rationale for the study ................................................................................ 4

1.1 The theory of financial intermediation in the context of climate change ........................ 5

1.2 A primer on climate change ......................................................................................... 5

1.3 Climate Change and the role of the banking sector ...................................................... 6

1.4 Research Problem/Context .......................................................................................... 9

2. Preliminary Literature Review .........................................................................................10

2.1 Defining Environmental Risk in the Bank Lending Context ..........................................10

2.2 Comparing and contrasting climate risk, carbon risk and environmental risk ...............12

2.3 Defining Bank Lending Process and its framework .....................................................13

3. Empirical Studies on Climate Change, Environmental risk and Bank Lending ...........17

3.1 Climate Change Issues and Banking in South Africa ..................................................21

4. Research Purpose and Objectives .................................................................................22

4.1 Research Goal ............................................................................................................22

4.2 Research Objectives ...................................................................................................22

4.3 Research Questions ...................................................................................................22

5. Methods of Research .......................................................................................................23

5.1 Research Design ........................................................................................................23

5.2 Qualitative research approach – research instrument and expected data ...................24

5.3 Qualitative Research Approach – Population and Sample ..........................................25

5.4 Qualitative Research Approach – Data Collection Process .........................................27

5.5 Qualitative Research Approach – Targeted Interviewees ............................................27

5.6 Qualitative Research Approach - Reliability and Validity .............................................28

5.7 Qualitative Research Approach - Data Analysis ..........................................................28

5.8 Quantitative Research Approach-Population and Sample ...........................................28

5.9 Quantitative Research Approach – Data Sources and Data Collection Process ..........29

5.10 Quantitative Research Approach – Data Analysis .......................................................29

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5.11 Brief theoretical background of the Z-Score Model......................................................29

5.12 The proposed Credit Environmental-Z-Score Model ...................................................33

6. Contribution of the Study ................................................................................................35

7. Limitations to the research study ...................................................................................35

8. Structure of the dissertation ...........................................................................................36

9. Summary ..........................................................................................................................37

10. Research Timeline ...........................................................................................................37

11. References .......................................................................................................................39

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1. Background/Rationale for the study

South Africa is one of the most industrialised countries in Africa and contributed about

37% of the total emissions in Africa as of 2010 (International Energy Agency (IEA)

2012). It is also noted that 74% of its source of energy is coal which is deemed as one

of the energy sources with highest carbon emissions. In 2010, South Africa generated

94% of its electricity using coal and such a continued reliance on coal would cause a

fourfold increase in carbon emissions between 2003 and 2050 in South Africa (IEA,

2012). Eskom is the sole producer of electricity and energy needed by the household,

manufacturing and industrial sectors of the South African economy. In the Eskom

Intergrated Report (2012), it is shown that Eskom has the second highest CO2 intensity

in coal power plants of 0.96kgCO2/kwh below that of India which is 0.97kgCO2/kwh.

Cavanagh et.al (1993) fore saw the impact of regulating carbon emissions through

carbon taxes and cap-and-trade systems on the present value of carbon emissions

charges being enormously more than the construction of coal fire power plants.

The International Panel on Climate Change (IPCC 2007), stated in their report the

percentages of the global sources of carbon emissions. It was noted that 26% of carbon

emissions come from energy supply, 19% from industry, 17% from forestry, 14% from

agriculture, 13% from transport, 8% from residential and commercial buildings and 3%

from waste and water. Relative to South Africa, there are no updated sectoral carbon

emissions sources, with the last GHG (green gas house) inventory done by the

Department of Environment and Tourism being for the period between 1990 and 2000

(DEAT 2009). The GHG inventory indicates that 78.9% of carbon emissions come from

Energy supply, with 14.1% coming from Industrial processes and product use, 4.9%

from Agriculture and 2.1% from Waste. From these statistics it is foregone that energy

generation supply plays a bigger role in emitting carbon emissions that cause climate

change. These sectoral sources of carbon emissions give a glimpse of where most of

the lending that will aid a low carbon economy in South Africa should go. It is inevitable

that more financing should go into renewable energy and greener industrial processes.

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1.1 The theory of financial intermediation in the context of climate change

The financial intermediation of banks in the economy is hinged on their impetus to

channel money from savers who have excess funds to borrowers who are short of funds

needed for production and consumption purposes (Campbell & Slack 2010). Financial

intermediation of banks can be amplified into four roles (Allen and Carletti 2008) and

these have an implication on this study. The first role is the amelioration of information

between savers and borrowers which ensures that the savers funds are used in the

right way by the borrower. Secondly, the banks provide products to manage risk and

uncertainties that may arise both to the savers and the borrowers. Thirdly they provide

the impetus for economic growth (Levine 1997, Kunt and Levine 2004, Badun 2009).

Fourthly they ensure the monitoring of managers and the enforcement of corporate

governance (Badun 2009, Gillan and Starks 2003, Sheard 1989, Stiglitz 1989). These

four roles have an impact in the embedding of environmental risk into bank credit

process. It is important to understand the rise in the magnitude of environmental risk

and its impact on economic growth given the financial institutions’ role of stimulating

economic growth through lending. On the other hand there is a growing trend by the

financial institutions in appraising the impact of climate change on the loans they make

by looking at the environmental practices of the firms they lend to (Coulson and Monks

1999, Thompson and Cowton 2004).Therefore we need to understand the phenomena

of environmental risk in light of climate change

1.2 A primer on climate change

The UNFCCC (United Nations Framework on Climate Change Conventions), defines

climate change as;

‘a change of climate which is attributed directly or indirectly to human activity that

alters the composition of the global atmosphere and which is in addition to

natural climate variability observed over comparable time periods.’

The Stern review report (2008), indicates that climate change is a result of green house

gas emissions whose origins are from economic activities such as energy, land-use,

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transportation and industry. These economic activities are quite broad; however it

should be known that the economic sectors that primarily and extensively use fossil

fuels in their production activities are the major emitters of carbon dioxide and other

associated toxic gases – termed herewith as green house gases (GHG). The increase

in the GHG has an impact on weather and climate patterns through the raising of

temperatures globally, and this is called global warming. This global warming

phenomenon will lead to extreme weather patterns that are frequent and disastrous to

normal livelihood, through droughts, landslides, heat waves, floods and hurricanes

amongst a host of extreme weather patterns (Cox et.al 2000, Houghton 2001,

Guggenheim et.al 2007).

1.3 Climate Change and the role of the banking sector

There is a wide economic and scientific consensus that a failure to reduce GHG

emissions and stabilisation of extreme weather caused by climate change will have

widespread implications for the world. Studies that have been done by environmental

groups show that there are huge portions of loans and investments in the portfolios of

some major banks that emit large quantities of carbon emissions (GHG) and infringe on

human rights of communities1. These activities range from dam constructions and

agricultural projects to coal fired thermal power stations that disturb the ecosystem and

natural biodiversity. Bowman (2010) contextualises the relationship between the

banking sector and climate change through three key banking functions which are risk

assessment, financing and profiteering.

The origins of environmental risk are cited through the legal obligations which created

lender liability for land contamination. The enactment of the Comprehensive

Environmental Response, Compensation and Liability Act of 1980 (CERCLA) in the

United States, caused a spate of high profile court cases against the Bankers who had

financed contaminated land and were held liable for cleanup costs. However with many

1For more details of the surveys see article by Rainforest Alliance Group (RAN) article entitled Financing

“Global Warming: Canadian Banks and Fossil Fuels” http://ran.org/sites/default/files/financing_global_warming.pdf and Banktrack’s article entitled “ Banks Climate Change and the new coal rush” http://www.banktrack.org/manage/ems_files/download/banks_climate_change_and_the_new_coal_rush/0_banks_climate_change_and_us_coal_rush.pdf

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OECD countries enacting similar liability for land contamination acts the awareness of

environmental risk has been broadened to incorporate climate risk (Bowman 2010).

Therefore the defining, interactions and differentiation of environmental risk and climate

risk are deemed necessary for this study. Brimble et.al (2010) also concurs with

Bowman on that regulation will be essential in fostering the role of financial institutions

as key in combating climate change. However, the global and national climate change

regulation uncertainties are stalling the banking institutions effectiveness in that regard.

The banking sector has not received enough spot light in the matters of exacerbating

the production of carbon emissions (Furrer et.al 2010). For now, it has been held that

banks are at the low end of causing climate change through anthropogenic activities

compared to carbon intensive industries of mining, agriculture, transport and heavy

manufacturing. However, given the fact that the banking sector has a huge influence in

most of the corporate finance and investment decisions of most firms, they in turn

indirectly influence the corporate sector’s business activities of which most are high

emitters of carbon emissions. The process of screening through risk appraisals and

funding investment projects gives the banking sector a huge transformative power,

through their lending and investment products to move the economies of the world

which are highly carbon intensive to being a low (tolerable) carbon intensive or green

economies (Juecken and Booma 2000).

There are various ways banks are abating climate change effects using their economic

agent role. This has been through corporate social responsibility activities which

promote sustainable use of resources. Most banks have ensured that they become

sustainable and ethical in the way they are operating. There are leading institutions

which provide guidelines to the corporate world to ensure that they are sustainable and

ethical in the way they operate. The popular guidelines to this effect include Climate

Principles, Equator Principles, Dow Jones Sustainability Index and the Carbon

Disclosure Project. These are popular in that they link the activities of the institutions or

corporates to the measured carbon emissions which cause climate change. Further,

they measure how the corporates have been socially responsible by giving back to the

community and how they have contained fraud and corruption through proper

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governance. It should be noted that carbon emission quantities are an indicator of how

much an institution is contributing to the harming of the environment leading to climate

change.

Extensive scholarly work has been done with regards to finding the role of banks in

combating climate change (Doherty 1997, McCarthy et.al 2001, Bouwer 2006) and lot of

it has bordered on, emissions trading systems, carbon markets (Hamilton et.al 2009,

Kosoy and Ambrossi 2010, Yamin 2012) and climate finance (Ballestoros et.al 2010,

Buchner et.al 2011). However, less work has been done in regards to incorporating

environmental risk into lending decisions of banks given the impact of this activity in

funding projects that exacerbate climate change. It envisaged that climate change will

bring with it transformation in ways which institutions operate, due to physical risks,

anticipated government regulations, changing market conditions and new sources of

competition (Lorenz 2008). However, the biggest concern comes from Environmental

NGOs (Banktrack, Friends of the Earth, World Wide Fund, Rainforest Alliance), who

have been in the forefront of criticising the banking sector’s continued funding of

environmentally damaging and also high carbon emitting projects.

This research study sets out to investigate how banks can properly incorporate

environmental risk in the form of climate (carbon) risk into their lending decisions in light

of the transition to low carbon economies. In the backdrop, there is a radical need to

move to low or zero carbon emissions economies whilst dilemmas arise with regards to

economic growth and job losses which might be caused by this transition (Foxon 2011;

Fuller et.al 2009). Issues of retrofit, adaptation, resilience, green jobs, green supply

chains, green buildings, renewable energy, electric cars and numerous green solutions

have been introduced to help reverse and prevent the damage of carbon emissions to

the environment (Frankhauser, 2006; Makower and Pike, 2009; Krugman 2010). How

can all these aspects be modelled into loan decision making processes of banking

institutions in South Africa?

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1.4 Research Problem/Context

The research problem stems from the Carbon Disclosure (CDP) Report of 2008, which

identifies how the financial services sector’s strength in disclosing risks and

opportunities through their expertise of identifying, managing and assessing of business

risks should be used to combat the effects of climate change. The report advocates the

need of the financial services industry to integrate climate change risks and

opportunities into their daily investment, lending and contract decisions in order to

achieve sustainable and excellent business. Further, Hart (2006) confirms that there is

no adequate common framework for systematically analysing climate risks in the

financial services sector. Particularly important on the CDP report of 2008 was the

acknowledgement by the financial services sector respondents to the effect that the

climate change impacts on the investment and loan portfolios, credit risks and other

financial exposures reside in a wide and complex domain which make it difficult to

evaluate them.

As far as in the knowledge available, there is no concrete framework that the financial

institutions are following to incorporate analysis of climate risk in the lending process or

decision makers in South Africa. The only survey done indicates that only three South

African Banks incorporate environmental criteria to their lending practice and not across

their products (Department of Environmental Affairs, 2011). Currently South African

banks are adhering to reporting requirements offered by voluntary institutions such as

Carbon Disclosure Project, Equator Principles and Dow Jones Sustainability Index

amongst a host of climate change and corporate sustainability projects. There are

guiding policies that banks have put in place in order to manage their operations with

regards to climate change. However, there are no integrated and industry wide

accepted guidelines with regards to the incorporation of risk that emanates from climate

change into their overall risk framework and particularly credit risk assessment or policy

(Hart 2006). This situation of a non-existent bank credit climate framework at the South

African level is attributed, to a large extent, by a lack of a national coherent climate

change policy, which is also slow in being developed. Therefore this research will

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attempt to formulate a framework that can be used by banks in South Africa to

incorporate environmental and climate risk in their lending decisions.

2. Preliminary Literature Review

2.1 Defining Environmental Risk in the Bank Lending Context

The way that environmental risk has affected bank lending has been presented in about

two ways in literature. The first view lies in the period when environmental risk was

deemed as the cost of pollution through environmental clean ups. It stemmed from the

regulation of banks being liable for cleanup costs caused by pollution damages of

companies they have financed (Boyer and Laffont, 1996). This notion of banker liability

on environmental damages is more pronounced in the 1980 Comprehensive

Environmental Response Compensation Liability Act in the United States (CERCLA).

Through this law the banker’s liability arises when the bank had been closely involved in

the monitoring of the firm’s activities and the bank is considered as an operator and

hence making them liable for cleaning up the environmental damages. Klotz and

Siakotos (1987) emphasized the need for lenders to be knowledgeable of the

environmental laws given the extensive liability they have on banks that lend. This also

augurs well with the notion of banks being monitors and managers of firms as discussed

above.

The second view is that environmental risk is defined as the risk that corporate activities

exert on the environment through the carbon emissions that they produce and how they

contribute to climate change. However the University of Leeds, Sustainable Research

Institute (2005), examines environmental risk based on the reason that the exact impact

of climate change in environment and economic terms is not well known. They further

argue that since most lenders focus on economic losses due to environmental aspects

they would rather not call this an environmental risk but an economic risk that is caused

by environmental aspects. Figge (1998) also regards environmental effects brought

about by climate change in financial terms as ‘environmentally induced economic risks’.

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Figge goes on to emphasize that the composition of environmental risks is more

important than its scale or probability of occurrence.

Bowman, (2010) indicate how climate risk encompasses credit, investment, reputation

and legal risk. Bowmen classify the corporate world into two segments of the risk they

pose to the banking institutions. The first segment is comprised of organisations that are

climate vulnerable which are real estate, agriculture, forestry and tourism. These are

affected by extreme weather. The second segment contains of corporations that cause

the climate risk by being the highest emitters of GHG, these are the oil, gas, coal, heavy

manufacturing and transport firms who are heavily affected by government policies that

price carbon emissions through carbon tax and thus increasing their production costs

and in turn their earnings.

Bray et.al (2007), support the idea of climate change being caused by anthropogenic

activities that emit green house gases and they illustrate how some businesses will be

made worse or better off by climate change. They reiterate the need to identify and

understand these risks and opportunities of climate change being faced by business. In

their study they identify generic climate risk management measures that will help

businesses ‘acclimatise’ their strategies and activities to the unavoidable climate

change. Some of these generic measures include the addressing of climate risks in

corporate risk management systems by way of identification, assessment and

management. Firstly companies should analyse how climate change can give them a

business a competitive edge, through redesigning climate friendly products. Secondly,

they need to involve and manage climate change positions of the companies’ external

stakeholders. Thirdly to regularly review how vulnerable a business’ sources of raw

material, assets, operations and processes are to changing climate risks. Fourthly, there

is need to use insurance and weather derivatives to hedge against climate risk. Lastly

the building of awareness levels within the company to climate change adaptation. With

this outline banks can be able to use this information in their lending appraisal and

investment analysis of these businesses. This are more of qualitative characteristics of

a company that is implementing climate adaptation strategies.

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From the derived definitions above it can be noted that environmental risk can be

derived from the effects of climate change, that is, carbon emissions being a proxy of

this. The other aspect is the earlier held view of environmental risk being tied to how the

banks were liable for the pollution caused by a firm that they have financed. The

difference in these two views is the aspect of the earlier view being confined to pollution

within the firm affecting natural resources directly and the later view being confined to

how firms’ carbon emissions indirectly affect the natural resources through the effects of

climate change. Latham (2009) however bridges this contrast by showing how the

dynamic evolution climate change issues has vastly proposed the changing

environmental law to include the issues of abating green house gas emissions (another

synonym for carbon emissions). Latham indicated how the Securities Exchange

Commission environmental risk disclosure in United States is going to have an impact

on publicly listed companies’ operations. One of the impacts will be the material issues

of the environmental risk disclosure to potential lenders.

2.2 Comparing and contrasting climate risk, carbon risk and environmental risk

Climate risk is mainly derived from the impacts of climate change caused by adverse

weather (Onischka 2008) and environmental risk is derived from how business through

its operations faces litigation of contaminating the natural environment (Romily 2007).

Onischka postulates climate risk in the financial institutions context posing physical risk,

regulatory risk, liability risk and reputational risk on their operations. Romily argues that

environmental risk is broad and is mostly associated with environmental events such as

oil spills and climate change related risk is part of environmental risk. Busch and

Hoffman (2008) describe carbon risk as a change in the company’s monetary carbon

over a given period of time. In other words the company’s production of carbon

emissions is measured in monetary terms of carbon taxes, and carbon credits prices

through the emissions trading system.

Innovest (2007) in their study show that carbon risk should go beyond level of carbon

disclosure and overall quantity of measured carbon emissions. They amplify this notion

of carbon risk by postulating that carbon risk should include the following four variables:

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firstly a company’s overall carbon footprint (total measured carbon emissions from

operations); secondly, measured ability to manage and reduce carbon risk exposure;

thirdly, ability to perceive and take advantage of climate change opportunities; and

fourthly, rate of improvement or deterioration in managing carbon risk.An interlink

between climate risk and environmental risk can be observed as defined in the

economic and financial fields, whilst carbon risk is more of an exposure measurement.

2.3 Defining Bank Lending Process and its framework

Altman (1980), describes the lending process as a series of activities which develop

between the borrower and the lender ranging from loan request to the failure or success

of the loan repayment. Altman further structuralise the bank lending process as shown

in fig.1 and further states that this process involves four steps: firstly, loan application,

secondly credit evaluation, thirdly loan review and fourthly repayment performance.

Greuning and Bratanovic (2008) expound that the bank lending function should fulfil

three important objectives that is of, firstly ensuring that loans are granted soundly and

are collectible; secondly, fund investment should be profitable and benefit shareholders

and protect depositors; and then thirdly to meet the legal credit needs of household and

economic agents.

A compare and contrast of the classical or traditional bank credit process models to the

modern credit process model can be easily illustrated in fig. below. Colquitt (2007)

analyse the differences in the traditional and modern credit processes in aspects of

functions and credit risk management evolving overtime. Colquitt purports that the

traditional credit process only concentrated on originating the loan, capital adequacy,

risk provisioning and credit monitoring which was static - in terms of the created loan

remaining on the balance sheet until maturity. However the modern credit process has

moved further by being dynamic in terms of credit portfolio management. Banks are no

longer keeping non performing loans on their balance sheet; they rather package them

and sell them in the second hand market. Another observation has been the avoidance

of large loan amount exposure to a single borrower under the traditional credit process.

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CONTINUE

Classify?

or

Loan

Request

Loan

Request

Loan

Request

Credit

Analysis

Financial

Requirement

Forecast

(A)

Traditional Ratio, Industry &Flow-of

Funds (B)

Firm Insolvency Analysis (C)

YES

NO

Loan

Review

NO YES

Repayments?

Charge-Off

NO

YES

or

Loan

Work -out

Final Repayments? Yes No

(B)

END

NO Renewal Request

Credit

Analysis

Lending Decision?

YES

(C) (B)

(A)

NO YES

Delin

qu

ency

Renewal Declined

Figure 1: Credit Appraisal Process

(Adapted from Altman, 1980)

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Transaction origination

Preparation of credit request

Structuring/pricing administration

Customer

ORIGINATION Credit Risk

Management

Credit Function

Capital

Structuring

Provisioning

Risk Syndication

Transaction

Transaction origination

Preparation of credit request

Structuring/pricing administration

Credit Assessment

Monitoring Credit Limit and Administration

Credit Limit

Credit Request

Client

ORIGINATION

Credit Function

Credit

Portfolio

Credit Trading

Credit Capital

Capital

Markets

Transaction

Credit Request Credit Limit & Credit Charge

Credit Portfolio

management and

positioning

Credit assessment

Credit portfolio management

Credit capital management

Syndication/Asset Sales

Securitization

Credit derivatives

Traditional Credit Process Model Modern Credit Process Model

Figure 2: Traditional Credit Process compared with Modern Credit Process

(Adapted from Colquitt, 2007)

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In the modern credit process there is a notable practice of reducing loan concentration

and limits to credit events and exposure by borrowers, industries, asset classes, and

geographical regions. Credit portfolio analysis is now being done on total for borrowers,

companies, markets, as well as credit products, which are overall measured against the

expected portfolio’s return.

Credit risk decision for retail and corporate clients are usually different. The retail

customer has no qualified and properly prepared financial statements which the

corporate client has and thus the credit risk assessment methods used differ. There is

more inclination of using quantitative credit risk models for corporate clients and

qualitative credit risk models towards the retail clients.

Sinkey (1986), indicates that the credit system is the centre of the financial system in

which financial institutions decide on the borrower’s credit worthiness. Thus climate

change and its related risk can have an adverse impact on the profitability of banks and

thus there is a need to analyse and quantify the potential of climate risk to impact on

loan portfolios of banks. Rose (2002), broadly classifies loans into real estate loans,

financial institution loans, agricultural loans, commercial and industrial loans, loans to

individuals, miscellaneous loans and lease financing receivables. Having knowledge of

loans that banks make gives an appreciation of what sectors are adversely impacted by

climate change and therefore be able to forecast and quantify possible damages of

climate change to the lending done and strategize mitigations to avoid non performing

loans.

Graddy et.al (1985) consider the lending process to include credit analysis, loan pricing,

overview of borrower’s financial statements, written loan policies and consumer

protection laws. In the formulation of a framework it is imperative to find these aspects

included in the ‘to be proposed’ framework or model of credit risk appraisal that

incorporates climate risk. The important point is to elaborate how climate and

environmental risk will change these aspects of the lending process.

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3. Empirical Studies on Climate Change, Environmental risk and Bank

Lending

This section shows the relatively current studies of how banking institutions are

incorporating environmental risk and climate change issues into bank lending

processes. It can be observed that earlier literature found little evidence of banks

incorporating climate change and environmental issues into their credit processes.

Thompson (1998), examined the lending policies of UK banks with regards to

environmental issues and found out that there was little evidence of banks taking

advantage of opportunities arising in the greening of industry. Thompson cited the

downside risk of lending to environmental issues was more probable than the upside

risk hence a shying away by banks from dwelling on environmental issues.

Maso et.al (2001) did a study in which a loan product was being created to ensure that

SMEs introduce Environmental Management Systems (EMS) in their operations. They

identified that banks were not proactive enough in introducing the environmental

variable in loan appraisals which should prompt the rewarding of eco-efficiency and

reduction of environmental risk. Thus they recommend banks to introduce eco-efficiency

in credit risk assessment, in defining the loan rates on spreads and in orientation of

investment products portfolio mix strategy. Thus overall from their study they

recommended the use by banks of the EMS as an indicator of how companies have

achieved real improvement in reducing environmental risk.

Ecosecurities(2005) did a study where they hypothesised the casual relationship

between climate change related events and loan portfolios of US and Canadian Banks.

One of the outcomes was the need to consider timeframe since there are no

measurable risks associated with climate change in a time period of less than 1 year.

However the problem is that the study was sector specific and not company specific

thus generalising the causality. However the essential aspect from this study was the

fact of being able to outline specific climate change risks that affect loans to various

economic sectors.

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The identified climate change risks in this study that affect loans are policy risk, input

price risk, output price risk and physical risk. Policy risk refers to risk connected to

climate change policy implementation or expected new regulatory actions. The input

and output price risk refers to the link of input and output prices of the product process

of a sector to the emissions cap and trade regime. For instance the coal mining

industry’s input price is the cost of extracting the coal and the output price is the

revenue from the sale of that coal. Thus if the coal industry is mandated to reduce its

emissions through an emissions cap, this will drive them to invest in more better

technology in order to reduce emissions in the production of coal .Physical risk, refers to

how climate change produces extreme weather systems in the form of hurricanes and

floods. This also extends to sporadic changes in the physical environment in the form of

drier climates in various regions, increased carbon emissions in the air, gradual

increase in sea levels and temperatures.

The overall outcome from the study was that climate change risk is low on current bank

loans and leases due to short average maturity of current bank loans whilst the physical

risks of climate change are long. More so policy risks were also of little effect to bank

loans, however it was indicated that it is too complex and tedious forecast the effects of

climate change precisely. The recommendation was that the banks making loans with

long maturities were at exposure to climate variability anticipated regulatory policies.

Cogan (2008), in their study indicate how banks are incorporating climate change into

lending as they see it as a risk management issue. They noted that banks are highly

exposed to operational, credit and political risks in their lending business to extractive

industries such as oil, gas and mining and climate change is exacerbating these risks.

In their study 13 of the 40 banks surveyed had some lending procedures in place that

incorporate climate change and there were two types of incorporation observed and

these are classified and explained in Table 1.

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Table 1: Incorporation of Climate Change related Risk in Bank Lending

Credit Policy Related Loan Pricing Related

Incorporation of expected costs of carbon in

the companies financing of power generation

Financing coal electrical generation when a

firm has effective initiatives to reduce GHG

and pollutants through enhanced technology

Making it mandatory for clients to disclose

their carbon emissions and mitigation

strategies on a regular basis

Employing a carbon analyst to measure the

financial impact of carbon emissions

constraints

Ensure that clients properly provide carbon

mitigation plans

Asking clients to take account of carbon

pricing in their project proposals

Ensuring clients develop carbon accounting

methodologies that take into account GHG

emissions

Incorporating carbon risk into credit and risk

rating methodologies

(Author, Adapted from Cogan, 2008)

There are different factors that need to be considered when using social and

environmental information in bank lending processes (Elsakit and Worthington, 2012).

These factors are connected to legal environment, pressure groups (stakeholders),

bank’s customers, and the bank’s operations. Elsakit and Worthington cite the lack of

laws to enforce the incorporation of social and environmental risk in bank lending

processes making it difficult to measure how irresponsible the banks have been in

financing irresponsible damage to the environment. Bauer and Hann (2010) indicate

that the credit standing of borrowing firms is influenced by legal, reputational and

regulatory risks associated with environmental incidents. In other words environmental

risk shares the same subsets of climate risk though not all as per the outcomes of the

study by Bauer and Hann. However Bauer and Hann make interesting conclusions in

their studies were they found that environmental concerns are associated with a higher

cost of debt financing and lower credit standings.

Erina and Lace (2012), concluded in their studies that were the environment factor

assessment is being done byLatvian banks surveyed it was only of formal nature. In

other words the environment assessment is not thorough and is a base look at whether

a borrowing company is applying the minimum required standards of addressing

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environmental issues. Roddewig and Keitter (2001) also proposed the

institutionalisation and normalisation of environmental risk into lending criteria but

mainly tailored to the mortgage lending. Their emphasis was on how environmental risk

affects house prices in the market place and how this impact should be reflected in the

appraisal process. Thomas (2009) also looks at the impact of environmental risk on real

estate and mortgage lending with environmental risk being defined in the context of

clean-up costs. The main finding is how environmental risk is high when the demand for

real estate is low and high when real estate demand is low. This is alluded to the

decision by real estate lenders who are not willing to make a loan before the clean-up2

has been done.

Recent studies show considerable incorporation of climate change issues and

environmental risk into bank lending processes. Weber et.al (2006) indicate that banks

are only incorporating environmental risk in the rating phase only and there are

disparities in the incorporation of environmental risk amongst the banks that are

signatories to UNEP statement3 and those that are not. A latter study by Webber (2010)

found out that there is considerable correlation between the firm’s economic

performance and environmental performance. The study also concluded that the

sustainability criteria can be used successfully to predict the financial performance of

the debtor and improve the predictive validity of the credit rating process. It can be seen

that recent studies are showing the closer interlink between financial or economic

performance of a form with its environmental performance and its relevancy to the credit

standing of firms.

2 Clean-up costs emanate from CERCLA which is a commonly used acronym for the Comprehensive Environmental

Response, Compensation, and Liability Act. CERCLA gives power to the government of United States to enforce the cleaning up of hazardous waste particularly on disused industrial sites. 3 The UNEP Statement is a commitment by Financial Institutions on Sustainable Development The act of signing up

to the Statement, financial institutions openly accent to the role of the financial services sector in making the global economy and human lifestyles sustainable and commit to the integration of environmental and social considerations into all aspects of their operations.

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3.1 Climate Change Issues and Banking in South Africa

EIRIS (2011) in the survey of climate change performance of JSE Top 40 companies

found out that 95% of the surveyed companies are disclosing absolute carbon

emissions and 85% are reporting normalised carbon emissions. Further mining and

banking sectors had high quality response in on overall climate change issues. This

gives a good indicator of how the banking sector is incorporating climate change issues

into their bank lending processes. However the survey was generic and did not bring

out details of the incorporation especially on the operations side, it mainly focused on

the strategic level.

There is limited study with regards to bank lending and environmental risk in South

Africa. Most of the research done covers mainly issues to do with climate change and

banking operations. Abrahams (2010) shows in the study done that South African

Banks are not particularly taking advantage of the climate change opportunities in

having a competitive advantage. Oduro-Kwateng (2010) shows how the King III

reporting requirements involuntarily forced banks in South Africa to disclose their

environment material issues that affect their operations. Dlamini (2010) studied the

environmental responses of banks in South Africa and the major finding was that

currently banks are mainly focusing on internal management of their operations impact

on the environment and much less on the external or indirect impact.

The National Climate Change Response White Paper (2011) emphasises the

importance of the financial institutions with regards to aiding government’s efforts of

combating climate change effects in South Africa. The report acknowledges the need of

South African Banks incorporating climate change and environmental issues in the

decision making frameworks. Further the white paper proposes the introduction of new

market based instruments, as well as environmental related financial reforms in the

pursuit of an economy and society that is resilient to climate change effects. Therefore

there is insinuation of banks being legally persuaded by the government to support in

climate change response initiatives. This notion is amplified on point 11.1.4d of the

section titled ‘financing the national climate change response’ and reads:

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‘Identify opportunities in the existing financial regulations governing the domestic finance

sector to enhance the financial sector’s capacity to mainstream climate change in risk

and investment decisions.’

Thus a basis is set by the white paper that might have repercussions to banks risk

management processes in South Africa.

4. Research Purpose and Objectives

4.1 Research Goal

Formulation of a credit appraisal model that incorporates environmental and climate risk

for South African banks

4.2 Research Objectives

a. To investigate the overall engagement of banks in South Africa with regards to

mitigating climate change through lending.

b. To establish theoretical concepts of environmental risk and climate risk in bank

lending.

c. To investigate the state of environmental and climate risk incorporation by banks

into their lending decisions.

d. To identify and evaluate the best practice amongst the banking institutions of

incorporating climate and environmental risk in lending decisions.

e. To formulate a credit appraisal model that banks can utilise to incorporate

environmental and climate risk in their lending operations

4.3 Research Questions

a. What are the issues that emanate from adverse conditions of climate change that

are of concern to the banking sector?

b. Why is environmental and climate risk of significance to the banking sector?

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c. What are the current trends in the South African banking sector of climate change

mitigation?

d. How should a proper credit appraisal model which incorporates environmental and

climate riskbe formulated in view of economic sectors, government policy on Climate

Change, financial sector regulation and international standards on environmental

and climate risk management?

5. Methods of Research

5.1 Research Design

The research approach that will be pursued in achieving the research objectives is a

mixed methods approach that combines both qualitative and quantitative approach.

Within this mixed methods approach we will pursue the exploratory mixed method

design that allows one to build a quantitative study using the results of a qualitative

research (Cresswell & Clark 2007). The qualitative approach is targeted at ensuring that

the state of South African bank’s incorporation of environmental and climate risk is

established. The results of the qualitative research will inform the conceptualisation and

structuring of appraisallending model that can be used to incorporate climate risk by

banks in South Africa. The qualitative results are expected to identify the essential

variables required to inform and adjust a pre-constructed credit appraisal model. The

quantitative approach aims at constructing and testing aproposed environmental and

climate risk-credit scoring model.

The information required from the research approach is essential in establishing a

robust and comprehensive model to predict scenarios of how company’s inability to curb

carbon emissions increases their default rates. Therefore we adopt the default predictor

model – Z Scores model proposed by Altman (1968) for the quantitative research

approach that will measure the credit risk and probability of default; however the

variables will be modified to include climate and environmental risk factors.

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In analysing our data we will use a sequential mixed analysis as proposed by Tashakori

and Teddlie (1998). We adopt the sequential qualitative and quantitative analysis

strategy. As explained by Onwuegbuzie and Teddlie (2003) the analysis involves the

qualitative study which identifies individuals (in our case banks) with similar

characteristics. These identified groups would be compared to each other using existing

quantitative data or data to be collected after the qualitative study.

5.2 Qualitative research approach – research instrument and expected data

This approach will endeavour to use semi structured interviewsand desktop review to

collect and document the aspects of climate risk and environmental risk that banks are

incorporating into their credit processes. We will employ the questionnaire structure

used by Harte et.al (1991) and Cowton and Thompson (2000) and develop it further to

suit the context of South African banks. The full questionnaire is expected to collect the

following information:

a. The motivation of South African Banks incorporating climate change and

environmental issues into their bank credit processes.

b. The most important environmental issues to South African Banks with regards to

lending.

c. The main sources and types of corporate environmental information used by

banks to make credit appraisal for their corporate clients.

d. To solicit the value of environmental sustainability reports of companies in

providing information on corporate environmental performance to South African

banks lending decision processes.

e. To find ways in which the lender’s practice of evaluating climate change issues

and environmental risk in the South African context can be improved.

The questionnaire will be piloted tested by sending draft copies to two prominent

academics in the field of environmental risk in South Africa, two senior bank executives

in the areas of corporate sustainability. The feedback will be used to restructure the

questions.

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5.3 Qualitative Research Approach – Population and Sample

The targeted population will be all banks that engage in corporate lending in South

Africa. The South African reserve bank Institutional Sector Classification Guide

(2011:12) classifies the banking sector as having South African registered banks which

are locally controlled and foreign controlled, South African Banks, South African

branches of foreign banks, post bank and the land bank. However we add the Land

Bank, Development Bank of South Africa (DBSA) and the Industrial Development

Corporation since they are involved in large scale corporate lending that transcend the

South African borders and thus material environmental issues should arise in such

lending transactions. Table 2 shows the list of all the banks as recognised by the South

African Reserve Bank (SARB) excluding the foreign bank representatives.

Table 2: List of authorised and licensed Banks operating in South Africa

Locally controlled Banks Branches of Foreign Banks Foreign controlled Banks

1. African Bank Limited 2. Bidvest Bank Limited 3. Capitec Bank 4. FirstRand Bank Limited 5. Grindrod Bank Limited 6. Investec Bank Limited 7. Nedbank Limited 8. Sasfin Bank Limited 9. The Standard Bank of

South Africa Limited 10. UBANK limited

1. Bank of Baroda 2. Bank of China –

Johannesburg 3. Bank of India 4. Bank of Taiwan South

African Branch 5. BNP Paribas SA 6. China Construction Bank

Corporation – Johannesburg

7. Citibank N.A 8. Deutsche Bank A.G 9. JP Morgan Chase Bank

N.A ( Johannesburg branch)

10. Societe Generale 11. Standard Chartered

Bank – Johannesburg Branch

12. State Bank of India 13. The Hong Kong and

Shanghai Banking Corporation Limited (HSBC)

1. ABSA Bank 2. Albaraka Bank Limted 3. Habib Overseas Bank

Limited 4. HBZ Bank Limited 5. Mercantile Bank

Limited 6. The South African

Bank of Athens Limited

(SARB, 2013)

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It is intended to use stratified sampling technique for the banks that are into corporate

lending and purposive sampling technique for the interviewing of corporate lenders. The

reason for choosing a stratified sampling is to ensure that we concentrate and get

maximum information from a group of banks that have high business and loan

transactions in corporate banking and weed out those that have less of this.

The procedure for choosing the stratified sample is as follows:

1. Collect total assets for each bank from the SARB Bank Supervision Annual

reports ranging from 2008 to 2011. The year 2012 report is not yet out.

See appendix A for details of the 31 Banks total assets values

2. Rank the banks per each year based on total asset value from highest to lowest.

3. Divide the banks into 3 categories of 10 banks in each category per each year.

4. Select the top 10 banks with the highest ranked total asset values per each year

and these will be considered for the sample to be interviewed.

After going through the steps above the following banks have been sampledand

targeted for interviews. However African Bank Limited was removed since it is mainly a

credit provider for retail credit and DBSA, Land Bank and IDC were included given their

immense involvement in corporate lending.

Table 3: Banks Targeted for Interviews

Sample of Banks to be interviewed.

1. ABSA Bank

2. Citibank

3. Credit Agricole Corporate and Investment bank

4. Duetsche Bank NA

5. FNB Bank

6. Investec

7. JP Morgan Chase Bank, NA Johannesburg Branch

8. Nedbank

9. Standard Bank of South Africa

10. Standard Chartered Bank Johannesburg Branch

11. The Hong Kong and Shanghai Banking Corporation Limited

12. Land Bank

13. Development Bank of Southern Africa

14. Industrial Development Corporation

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The sample is deemed adequate in that the chosen banks hold about 90% of the total

assets of all South African banks for the period 2008 to 2011. Therefore the interviews

to be conducted on the corporate lenders will provide robust information than can be

used to inform a proper integration of environmental risk into bank credit appraisal in

South Africa. More so, there is an adequate representation of banks operating in South

Africa based on being locally owned, foreign controlled or branches of foreign banks.

This will adequately capture all perspectives of environmental risk and its impact on

credit processes form both the views of foreign banks operating in South Africa and

local South African banks.

5.4 Qualitative Research Approach – Data Collection Process

Given the cumbersome process of scheduling interviews for the corporate banking

executives it is planned that the services of the Bureau Market Research (BMR) –

UNISA (University of South Africa will be employed. These services will include the

structuring and formatting of the semi-structured interview in line with research

objectives, the briefing of the interview questions and the expected answers and the

method of conducting of the interviews to the targeted corporate banking executives in

the sample. From brief ground work and consulting the BMR it is possible to do semi-

structured interviews using the telephone and then transcribe the answers which then

can be analysed by thematic - content analysis.The funds from MDSP (Masters and

Doctorate Support Programme) will be used to finance the process of conducting this

data collection process through the BMR.

5.5 Qualitative Research Approach – Targeted Interviewees

The aim is to target Sustainability Executives and Corporate Banking Executives in

each bank. It envisaged that these are well versed in issues of both corporate lending

and environmental risk in the context of South African Banking sector.

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5.6 Qualitative Research Approach - Reliability and Validity

A pilot test will be done on the drafted semi structured interview questionnaire with

Auditors who are versed in environmental sustainability issues of Banks in South Africa

and Independent Research Consultants who deal with banks in issues of environmental

sustainability. A debriefing session will be done with the allocated interviewer from BMR

to indicate the desired information to be extracted from the respondents inorder to

capture as much as possible the desired information. The fact that BMR has been doing

this kind of work for quite a long time gives the assurance of having data easily and

accurately collected given their huge expertise in questionnaire design, data collection

through various means which include telephone interviews and administered online

questionnaires.

5.7 Qualitative Research Approach - Data Analysis

For analysis the main aim is to have a thematic -content analysis of the information to

be collected and be able to deduce the environmental and climatic aspects that banks

consider when doing credit appraisals. These themes will inform the formulation of

robust and adequate proxies of climatic and environmental risks that can be used to

modify and reformulate the Z-scores model in the quantitative part of the study.

5.8 Quantitative Research Approach-Population and Sample

The Johannesburg Stock Exchange Top 100 companies (JSE 100) will be considered

for testing the proposed modified Z-Score model to be termed the Credit Environment-

Z-Score model. These have been chosen on the basis that their annual reports are

readily available and contain all the needed information for the Z-Score Model. More so

their huge market capitalisation makes it an appropriate sample of companies that are

targeted for lending by the banks sampled above, thus it will be appropriate to test

Credit Environment-Z-Score model on them. The JSE100 also has a wide array of

companies from different industrial and economical sectors and thus capturing the

different impacts these companies have on the environment. More so almost all of the

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JSE100 companies report the carbon emissions in the Carbon Disclosure report

annually.

5.9 Quantitative Research Approach – Data Sources and Data Collection

Process

The most important data to feed into the proposed Credit Environmental-Z-Score Model

is the financial statements found in the annual reports and the environmental

sustainability information for carbon emissions found in the intergrated sustainability

report and the carbon disclosure report.

5.10 Quantitative Research Approach – Data Analysis

In analysing the data for quantitative research approach the aim is to use the Z-Score

and modify it to incorporate the environmental performance of companies in financial

terms. We will embark on reviewing the theoretical background of the Z-Score model

and the justification of why it was found suitable for analysis.

5.11 Brief theoretical background of the Z-Score Model

The Altman’s Z-Score Model (Altman, 1968) was a seminal work on company

bankruptcy prediction of using accounting information. There was prior work by Beaver

(1966) were the use of univariate analysis was done to predict the failure of the

company whereas Altman used the multivariate analysis.Beaver indicated that the

univariate analysis examined the predictability of ratios in isolation of each other, and

proposed a future research that will promulgate a multivariate analysis that uses

different and several ratios and/or their rate of change over time to predict more

accurately the bankruptcy of these firms analysed. Altman developed his model starting

from this point and used the same research design as done by Beaver which involved

the grouping of firms into two categories, one of non failed firms and the other of failed

firms. Beaver conjured two useful arguments that are seen to be captured well in his

analysis. The first argument being the ability of financial ratios being able to detect

financial illness of firms before they fail. However the analysis could not tell which firms

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in the sample of non-failed firms had the ratios successfully detect bankruptcy and have

remedial measures done for them to come out of their solvency. Thus could this be an

underestimation of the predictive ability of the ratios? The second argument was based

on ratios being used to determine the creditworthiness of firms by lenders and using a

ratio as a benchmark for a firm’s inability to reach a certain desired level. Therefore, can

the prediction ability be overstated in such a case?

The argument of the inability of ratios to predict failure before financial difficulties appear

inspired Altman to propose a multiple discriminant analysis (MDA) to the predicting of

bankruptcy. Since the univariate analysis proved indeterminable on which ratios were

important in using to predict bankruptcy, Altman suggested the MDA as the appropriate

fit tool for this. Klecka (1980) describes discriminant analysis as a statistical technique

which facilitates the study of differences between two or more groups of objects with

respect to several variables simultaneously. Altman (1969) describes MDA as a tool

used primarily to classify and make predictions in problems where the dependent

variable appears in quality form, as an example male or female, and in Altman’s

example non bankrupt and bankrupt. Altman adopted the MDA for its ability produce a

linear combination which best discriminates between the established groups. In this

instance a company has characteristics (financial ratios) and these can be quantified for

all the companies in the groups to facilitate the analysis and therefore the MDA assigns

discriminant coefficients. These discriminate coefficients assigned to each ratio will

assist separating the companies into one of the mutually exclusive groupings –bankrupt

or non-bankrupt.

The form of the linear equation adopted by Altman is:

Where Z = Discriminate score

V = the discrimination coefficient or weight for that variable

X = Independent variable i

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Therefore the MDA computes the discriminant coefficients viwhile the independent

variablesXiare the actual values.

The Altman’s Z-Score model was derived from a sample of sixty six companies with

thirty three firms classified into each of the two groups .The bankrupt group of

companies were derived from manufacturers who had filed a bankruptcy under Chapter

X of the National Bankruptcy Act during 1946 to 1965. Companies in the non bankrupt

group were still in operating in the time the study was conducted. With the groups

properly defined and selected all the relevant financial statement information was

collected. Altman used a wide pool of variables (ratios) proposed as important indicators

of corporate problems in past studies and these were about twenty two. These variables

were further classified into five standard categories of ratios namely liquidity,

profitability, leverage, solvency and activity ratios.

In order to remain with five significant ratios for the analysis, Altman chose them based

on:

1. Observation of the statistical significance of various alternative functions

including the determination of the relative contributions of each independent

variable.

2. Evaluation of the inter-correlations between the relevant variables.

3. Observation of the predictive accuracy of the various profiles.

4. Judgement of the analyst.

After a host of iterative processes and multiple computer runs Altman proposed the

following discriminant function as best predictor of company default or bankruptcy:

Where X1 = Working Capital/Total Assets

X2 = Retained Earnings/Total Assets

X3 = Earnings before Interest and Taxes/Total Assets

X4 = Market Value Equity/Book Value of Total Debt

X5 = Sales/Total Assets

Z = Overall Index

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Given that this study was done in the sixties it might seem not in sync with current

developments in bankruptcy or default prediction. In a study done by Altman et.al (1977)

they did a review of the ZETA analysis which was being used in investment analysis by

Wood, Struthers and Winthrop (WSW). This new model was built on the Altman’s Z-

Score and Altman supported the evolvement and promulgation of new default prediction

models. The support is based on changes in the size and financial profile of bankrupt

companies, the temporal nature of the data, the failure by past models to analyse

companies in different sectors on an equal basis, latest financial and accounting

reporting standards and to incorporate the recent advances and still controversial

aspects of discriminant analysis. From these considerations a new seven variable

model for predicting business was suggested with the following variables being used:

X1: Return on assets measured by the earnings before interest and taxes/total assets

X2: Stability of Earnings measured by a normalised measure of the standard error of

estimate around a ten-year trend in X1

X3: Debt Service measured by the familiar interest coverage ratio, which is earnings

before interest and taxes/total interest payments

X4: Cumulative Probability measured by the firm’s retained earnings (balance sheet)/

total assets

X5: Liquidity measured by the familiar current ratio. In this case the working capital to

total assets ratio is dropped and the reason was that the current ratio is more

informative.

X6: Capitalisation measured by ordinary shares/total capital

X7: Size measured by the firm’s total assets. This variable was adjusted for recent

changes in financial reporting changes and this is in regard to capitalisation of

leasehold rights.

In the test statistic observed the most important variable in the discriminant analysis

was cumulative profitability ratio is X4 and using the scaled vector analysis the ratio

contributed 25% of the total discrimination. The second and third in importance were the

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stability of earnings ratio (X2) and capitalisation variable (X6) respectively which were

total consistent across tests done.

5.12 The proposed Credit Environmental-Z-Score Model

In constructing the Credit Environmental Z-Score Model it will be advisable to adapt the

discriminant analysis method of Altman and come up with default predicting coefficients

that represent the South African firms. In that regard we will collect information for

bankrupt firms and non bankrupt firms in South Africa for the past 10 years. (2003 to

2013). Furthermore since this information will be ideal for testing the bankruptcy

possibility of South African firms in the context of climate risk and environmental risk an

eighth and ninth variable will be added to the ZETA analysis equation reviewed above

as X8 representing the impact of carbon tax costs on total incomeand X9being

environmental performance measured by the carbon emissions emitted against the total

assets of the company. We employ the implementation of carbon tax regulation to be

implemented in South Africa as contained in the 2013 budget speech. A proposal was

made that carbon should be taxed at a rate of R120 per ton of CO2 equivalent.

Furthermore it was proposed that any adverse impact may be softened by introducing a

tax-free exemption threshold of 60 percent, with some additional allowances for

emission intensive and trade-exposed industries.The rationale is that these are the two

measures that we can use to link the impact of the companies activities to the

environment and inturn the impact of going beyond the government regulations on

emissions on their revenues.

This eighth and ninth variable will use an all inclusive measure of the environmental

performance of institutions which is based on the carbon emissions they produced

against their total assets and total revenues. From the literature review carbon

emissions are directly linked to material use,production hours, material type and

production activities (Busch, 2010). Therefore we propose the environmental

performance measure that indicates the cost of carbon emissions with the proxy being

carbon tax as a ratio of total revenue. It should be noted that the scope of this research

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relies on the quantitative aspect of measuring environmental performance; the quality

aspects to be considered in full credit appraisal are not dealt with here.

Therefore the resultant Credit Environmental Z-Score Model will be as follows:

X1: Return on assets measured by the earnings before interest and taxes/total assets

X2: Stability of Earnings measured by a normalised measure of the standard error of

estimate around a ten-year trend in X1

X3: Debt Service measured by the familiar interest coverage ratio, which is earnings

before interest and taxes/total interest payments

X4: Cumulative Probability measured by the firm’s retained earnings (balance sheet)/

total assets

X5: Liquidity measured by the familiar current ratio. In this case the working capital to

total assets ratio is dropped and the reason was that the current ratio is more

informative.

X6: Capitalisation measured by ordinary shares/total capital

X7: Size measured by the firm’s total assets. This variable was adjusted for recent

changes in financial reporting changes and this is in regard to capitalisation of

leasehold rights.

X8: Climate risk regulation impact on business performance. This will be measured

by carbon tax on company’s carbon emissions to total revenue.

X9: Environmental performance will be measured by carbon emissions to the total

assets of the company.

The task ahead comprises the process of contextualizing the variables X1 to X7tothe

South African setting by following the iterative processes by Altman et.al (1977), Altman

(2000) which will change the weight measures in Altman’s Z-Score variables. A similar

work has been done by Merkevicius et.al (2006), Bandyopadhyay (2006) in which they

re-estimate the weights or coeffecients in the Z-Score Model to suit the Lithuanian and

Indian economic context in their studies respectively. In the case of Bandyopadhyay

used data of long term bonds of companies whilst Merkevicius used a hybrid between

the self-organizing model (SOM) and Altman’s Z-Score modified to change the weights

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of the Z-Score model variables suited to the Lithuanian economic context. In this study it

is proposed to find first the data for companies in insolvency to make up our sample that

we can use to re-estimate the weights suited to the South African economic context for

our analysis. The data in this regard will be solicited from the Companies and

Intellectual Property Commission (CIPC), Bloomberg financial data stream and the

Thompson Financial data stream.If enough data is not found in that regard we employ

the long term bonds of companies and extract the information from the bond exchange

of South Africa. In this research, E-Views 7 will be used for statistical analysis for the

quantitative part of this study and Atlas.ti will be used for content analysis for the

qualitative part of the study.

6. Contribution of the Study

The major contribution that the research will intend to make will be the incorporation of

environmental risk and climate risk into credit appraisal process of banks. This

contribution augurs well with the intention of the South African government to move to a

low carbon economy. Furthermore there is intention to add to the body of knowledge

with regards to the theory of lending decision making in the context of environmental

risk. The other expected contribution is of opening up corporate delinquency studies in a

South African context which to the best of the researcher’s knowledge is not extensive.

7. Limitations to the research study

It is anticipated that the outcomes or results of the research will to a certain extent be

generalised to the bank credit appraisal processes in the South African Banking Sector.

The main challenge will be the fear of banks to divulge sensitive issues on how they are

dealing with environmental issues in their lending processes. This might be seen as a

reputational issue, however it will be made sure that the banks are anonymous and no

names will be included in the presentation and analysis of data collected. The research

design has been selected in such a way that the collection of the data is credible,

affordable and reliable and hence overcoming a lot of preconceived limitations.

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8. Structure of the dissertation

Author 2013

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9. Summary

The research proposal has presented the introduction of the intended study and the

outline of the same. It has been emphasized how incorporating climate and

environmental risk in the lending appraisal systems can lead to the reducing of carbon

emissions which cause climate change. The problem statement is premised on the role

of the banking sector as an agent of economic development. Therefore the attributes of

risk management, financial advisory and financial provision are instrumental in changing

the economic activities of firms from high carbon emitters to low carbon emitters. In the

same vein we have crafted research objectives and research questions that will guide

the research process of solving the research problem. The research problem is how the

aspects of climate and environmental risk can be embedded in bank credit processes.

The South African banking sector has been selected for this study mainly based on its

central position to the financial markets in Africa and the quality of its banking

infrastructure and activities. The mixed methods of qualitative and quantitative research

study will be used to solve the problem. The qualitative research method will benchmark

the current treatment of climate and environmental risk in the South African banking

context. The quantitative research method will use the qualitative research method

results to craft a modified Z-Score model to predict company default based on financial

ratios and environmental and climate risk ratios. The details of the sources of data,

research methodology and method of analysis have been fully presented.

10. Research Timeline

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Task Name

Start Date End

Date

Assigned To

Chapter 1 Write up (Introduction, Problem Statement, Research Problem, research Objectives) 10-01-13 12-18-13 Alfred Bimha

Refining of Introduction, Rationale for the Study 10-01-13 10-30-13 Alfred Bimha

Refining of Objectives, Research Problem & Research Questions 10-31-13 11-29-13 Alfred Bimha

Editing and Corrections to chapter 1 12-02-13 12-20-13 Alfred Bimha

Chapter 2 & 3 Write Up (Literature Review) 01-03-14 05-01-14 Alfred Bimha

Literature Review on Bank Credit processes 01-02-14 01-31-14 Alfred Bimha

Literature Review on Environmental and Climate Risk in Bank Lending 02-03-14 02-28-14 Alfred Bimha

Literature Review on Default Prediction Models 03-03-14 03-31-14 Alfred Bimha

Refining Chapter 2 & 3 04-01-14 04-30-14 Alfred Bimha

Chapter 4 Write up (Methodology Review, Data Collection, Research Methods) 05-01-14 05-01-15 Alfred Bimha

Methodology Review of the Altman -Z-Score Model, Mixed Methods Literature 05-01-14 05-30-14 Alfred Bimha

Questionnaire Design with BMR 06-02-14 06-30-14 BMR (UNISA)

Pilot testing Questionnaire 07-01-14 07-31-14 Alfred Bimha

Feedback from Questionnaire and refining Questionnaire 08-01-14 08-29-14 Alfred Bimha

Incorporate Pilot test feedback into Questionnaire 09-01-14 09-30-14 Alfred Bimha

Engage BMR to Conduct Telephonic Interviews with targeted Banking Executives from Sampled Banks 10-01-14 12-16-14 BMR (UNISA)

Collect Data of Bankrupt Companies for use in Z-Score tailored Model for South Africa 07-01-14 08-30-14 Alfred Bimha/Librarian

Collect data JSE100 companies for use in the Credit Environment Z-Score Models 07-01-14 08-30-14 Alfred Bimha/Librarian

Incorporate Data from telephonic interviews in the proposed Credit Environmental Z-Score Model 01-03-15 03-31-15 Alfred Bimha

Final Write up and refining of Chapter 4 04-01-15 05-01-15 Alfred Bimha

Chapter 5 Write up (Results and Discussion) 05-02-15 07-31-15 Alfred Bimha

Mixed Methodology Results Presentation 05-02-15 05-20-15 Alfred Bimha

Model Construction of the Credit - Environmental -Z-Score Model (Computer variable feed and analysis

run)

05-21-15 06-20-15 Alfred Bimha

Results Interpretation and presentation of the Credit Environmental Z-Scores model 06-21-15 07-20-15 Alfred Bimha

Finalisation of Chapter 5 07-21-15 07-31-15 Alfred Bimha

Chapter 6 Conclusions and Recommendations 08-01-15 10-15-15 Alfred Bimha

Language Editing, Finalisation, Presentation of first draft 10-16-15 10-31-15 Alfred Bimha / Langauge

Editor

Corrections of first draft and final Submission 11-01-15 11-30-15 Alfred Bimha

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11. References

1. Abrahams, D 2010, Climate change and the South African banking sector : the

potential for competitive advantage, MBA dissertation, University of Pretoria,

Pretoria, viewed 130505 < http://upetd.up.ac.za/thesis/available/etd-04042011-

133345/ >

2. Allen, F. & Carletti, E. 2008, "The Roles of Banks in Financial Systems", Oxford

Handbook of Banking, forthcoming, .

3. Altman, E.I., Haldeman, R.G. & Narayanan, P. 1977, "ZETA TM analysis A new

model to identify bankruptcy risk of corporations", Journal of Banking & Finance, vol.

1, no. 1, pp. 29-54.

4. Ballesteros, A., Nakhooda, S., Werksman, J. & Hurlburt, K. 2010, "Power,

responsibility, and accountability: rethinking the legitimacy of institutions for climate

finance", Climate law, vol. 1, no. 2, pp. 261-312.

5. Bandyopadhyay, A. 2006, "Predicting probability of default of Indian corporate

bonds: logistic and Z-score model approaches", Journal of Risk Finance, The, vol. 7,

no. 3, pp. 255-272.

6. Bauer, R. & Hann, D. 2010, "Corporate environmental management and credit risk",

Available at SSRN 1660470, .

7. Beaver, W.H. 1966, "Financial ratios as predictors of failure", Journal of accounting

research, , pp. 71-111.

8. BenDor, T.K., Riggsbee, J.A. & Doyle, M. 2011, "Risk and Markets for Ecosystem

Services", Environmental science & technology, vol. 45, no. 24.

9. Bowman, M. 2010, "The role of the banking industry in facilitating climate change

mitigation and the transition to a low-carbon global economy", Environment and

Planning Law Journal, vol. 27, pp. 448.

10. Boyer, M. & Laffont, J.J. 1997, "Environmental risks and bank liability", European

Economic Review, vol. 41, no. 8.

11. Brooks, N. 2003, "Vulnerability, risk and adaptation: A conceptual framework",

Tyndall Centre for Climate Change Research Working Paper, vol. 38, pp. 1-16.

12. Buchner, B., Falconer, A., Hervé-Mignucci, M., Trabacchi, C. & Brinkman, M. 2011,

"The Landscape of Climate Finance", Climate Policy Initiative: Venice, vol. 27.

40 | P a g e

13. Busch, T. 2010, "Corporate carbon performance indicators revisited", Journal of

Industrial Ecology, vol. 14, no. 3, pp. 374-377.

14. Campbell, D. & Slack, R. 2011, "Environmental disclosure and environmental risk:

Sceptical attitudes of UK sell-side bank analysts", The British Accounting Review,

vol. 43, no. 1, pp. 54-64.

15. Cavanagh, R., Gupta, A., Lashof, D. & Tatsutani, M. 1993, "Utilities and CO2

emissions: Who bears the risks of future regulation?", The Electricity Journal, vol. 6,

no. 2, pp. 64-75.

16. Chirinko, B., van Ees, H., Garretsen, H. & Sterken, E. 1999, Firm performance,

financial institutions and corporate governance in the Netherlands, University of

Groningen.

17. Cogan, D.G. 2008, Corporate Governance and Climate Change: The Banking

Sector: a Ceres Report, Ceres.

18. Colquitt, J. 2007, Credit risk management : How to avoid lending disasters and

maximize earnings, McGraw-Hill, New York.

19. Conley, J.M. & Williams, C.A. 2011, "Global Banks as Global Sustainability

Regulators?: The Equator Principles", Law & Policy, vol. 33, no. 4.

20. CDP (2008). Carbon disclosure project report 2008: Global 500, on behalf of 385

investors with assets of $57 trillion. Carbon Disclosure Project, available online at

http://www.cdproject.net/reports.asp.

21. Coulson, A.B. & Monks, V. 1999, "Corporate environmental performance

considerations within bank lending decisions", Eco‐Management and Auditing, vol.

6, no. 1, pp. 1-10.

22. Cowton, C.J. & Thompson, P. 2000, "Do codes make a difference? The case of

bank lending and the environment", Journal of Business Ethics, vol. 24, no. 2, pp.

165-178.

23. Cox, P.M., Betts, R.A., Jones, C.D., Spall, S.A. & Totterdell, I.J. 2000, "Acceleration

of global warming due to carbon-cycle feedbacks in a coupled climate model",

Nature, vol. 408, no. 6809, pp. 184-187.

24. Creswell, J.W. & Clark, V.L.P. 2007, Designing and conducting mixed methods

research, Wiley Online Library.

25. Demirgüç-Kunt, A. & Levine, R. 2004, Financial structure and economic growth: A

cross-country comparison of banks, markets, and development, the MIT press.

41 | P a g e

26. Dlamini, T.H 2010, The banking sectors response to environmental sustainability,

MBA dissertation, University of Pretoria, Pretoria

27. Doherty, N.A. 1997, "Innovations in managing catastrophe risk", The Journal of risk

and insurance, vol. 64, no. 4, pp. 713-718.

28. EcoSecurities, (2006). Global Climate Change: Risk to Bank Loans. United Nations

Environment Programme Finance Initiative (UNEP FI) and its North American Task

Force (NATF). (e.g. 2), pp.80

29. Eidleman, Gregory J. (1995-02-01). Z-Scores – A Guide to Failure Prediction.The

CPA Journal Online.

30. EIRIS (Ethical Investment Research Services (EIRIS) (2011). To what extent are

leading South African companies tackling climate change? . [ONLINE] Available at:

http://www.eiris.org/files/research%20publications/JSETop40ClimateChange2011.pd

f. [Last Accessed 01 May 2013].

31. Elsakit, O.M. & Worthington, A.C. 2012, "Using Environmental and Social

Information in Lending Decisions", International Journal of Economics and Finance,

vol. 5, no. 1, pp. p112.

32. Erina, J. & Lace, N. 2012, "ENVIRONMENTAL QUESTION IMPACT FOR

LENDERS AND THE RISK MANAGEMENT PROCESS", Economics and

Management, vol. 17, no. 2, pp. 733-739.

33. Fankhauser, S. 2006, "The Economics of Adaptation", Available at www.hm-

treasury.gov.uk/d/stern_review_supporting_technical_material_sam_fankhauser_23

100, vol. 6.

34. Foxon, T.J. 2011, "A coevolutionary framework for analysing a transition to a

sustainable low carbon economy", Ecological Economics, vol. 70, no. 12, pp. 2258-

2267.

35. Fuller, M.C., Portis, S.C. & Kammen, D.M. 2009, "Toward a low-carbon economy:

municipal financing for energy efficiency and solar power", Environment: Science

and Policy for Sustainable Development, vol. 51, no. 1, pp. 22-33.

36. Furrer, B., Hamprecht, J. & Hoffmann, V.H. 2012, "Much Ado About Nothing? How

Banks Respond to Climate Change", Business & Society, vol. 51, no. 1.

37. Graddy, D.B., Spencer, A.H. & Brunsen, W.H. 1985, Commercial banking and the

financial services industry, Reston Publishing Company.

42 | P a g e

38. Government of South Africa (2011). National Climate Change Response White

Paper . [ONLINE] Available at:

http://www.info.gov.za/view/DynamicAction?pageid=623&myID=315009. [Last

Accessed 06 May 2013].

39. Guggenheim, D., Gore, A., Bender, L., Burns, S.Z., David, L., Pictures, P. &

Documentary, G.W. 2007, An inconvenient truth, Paramount Home Entertainment.

40. Hamilton, K., Sjardin, M., Shapiro, A. & Marcello, T. 2009, "Fortifying the foundation:

state of the voluntary carbon markets 2009.", Fortifying the foundation: state of the

voluntary carbon markets 2009, .

41. Hart, C. 2007, "Financial Risks and Climate Change" in Mapping Sustainability

Springer, , pp. 367-377.

42. Hart, C.A. 2006, The private sector's capacity to manage climate risks and finance

carbon neutral energy infrastructure, .

43. Hassan, M.K., Sanchez, B. & Yu, J. 2011, "Financial development and economic

growth: New evidence from panel data", The Quarterly Review of Economics and

Finance, vol. 51, no. 1, pp. 88-104.

44. Hoffmann, V.H. & Busch, T. 2008, "Corporate carbon performance indicators",

Journal of Industrial Ecology, vol. 12, no. 4, pp. 505-520.

45. Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der LINDEN, Paul J, Dai, X.,

Maskell, K. & Johnson, C. 2001, Climate change 2001: the scientific basis,

Cambridge University Press Cambridge.

46. Jeucken, M.H. & Bouma, J.J. 1999, "The changing environment of banks", Greener

Management International, vol. 1999, no. 27, pp. 20-35.

47. Khan, M.S. & Semlali, A.S. 2000, Financial development and economic growth: An

overview, International Monetary Fund.

48. Kim, K. & Kim, Y. 2012, "International comparison of industrial CO2 emission trends

and the energy efficiency paradox utilizing production-based decomposition", Energy

Economics, vol. 34, no. 5, pp. 1724-1741.

49. Klecka, W.R. 1980, Discriminant analysis, SAGE Publications, Incorporated.

50. Kousky, C. & Cooke, R.M. 2009, "Climate change and risk management: challenges

for insurance, adaptation, and loss estimation",

43 | P a g e

51. Krugman, P. 2010, Building a green economy. The New York Times Magazine,

vol.5.

52. Levine, R. 1997, "Financial development and economic growth: views and agenda",

Journal of economic literature, vol. 35, no. 2, pp. 688-726.

53. Lorenz, D. 2008, "Prudence, profit and the perfect storm: climate change risk and

fiduciary duty of directors" in Economics and Management of Climate Change

Springer, , pp. 271-292.

54. Lucas, R.E. 1988, "On the mechanics of economic development", Journal of

Monetary Economics, vol. 22, no. 1, pp. 3-42.

55. Makower, J. & Pike, C. 2009, Strategies for the green economy: Opportunities and

challenges in the new world of business, McGraw-Hill columbus, OH.

56. Maso, D.D., Marini, C. & Perin, P. 2001, "A green package to promote environmental

management systems among SMEs", Sustainable Banking: The Greening of

Finance, vol. 1, no. 86, pp. 56-65.

57. McCarthy, J.J., Canziani, O.F., Leary, N.A., Dokken, D.J. & White, K.S. 2001,

Climate change 2001: impacts, adaptation, and vulnerability: contribution of Working

Group II to the third assessment report of the Intergovernmental Panel on Climate

Change, Cambridge University Press.

58. Merkevicius, E., Garšva, G. & Girdzijauskas, S. 2006, "A hybrid SOM-Altman model

for bankruptcy prediction" in Computational Science–ICCS 2006 Springer, , pp. 364-

371.

59. Metz, B. 2007, Climate Change 2007-Mitigation of Climate Change: Working Group

III Contribution to the Fourth Assessment Report of the IPCC, Cambridge University

Press.

60. Mohsin, K. & Senhadji, A. 2000, Financial Development and Economic Growth: An

Overview, .

61. Mortimer, N., Ashley, A., Moody, C., Rix, J. & Moss, S. 1998, "Carbon dioxide

savings in the commercial building sector", Energy Policy, vol. 26, no. 8, pp. 615-

624.

62. Odedokun, M.O. 1996, "Alternative econometric approaches for analysing the role of

the financial sector in economic growth: Time-series evidence from LDCs", Journal

of Development Economics, vol. 50, no. 1, pp. 119-146.

44 | P a g e

63. Oduro-Kwateng, George (2010) The evaluation of environmental reporting by

publicly listed South African banks. Masters thesis, Rhodes University.

64. Onwuegbuzie, A.J. & Teddlie, C. 2003, "A framework for analyzing data in mixed

methods research", Handbook of mixed methods in social and behavioral research, ,

pp. 351-383.

65. Peter, S.R. 2002, "Commercial bank management", McGraw-Hill Irwin, Boston, .

66. Roddewig, R.J. & Keiter, A.C. 2001, "Mortgage lenders and the institutionalization

and normalization of environmental risk analysis", Appraisal Journal, vol. 69, no. 2,

pp. 119-125.

67. Romilly, P. 2007, "Business and climate change risk: a regional time series

analysis", Journal of International Business Studies, vol. 38, no. 3, pp. 474-480.

68. Rose, P.S. 1999, "Commercial bank management", .

69. Russo, M.V. & Fouts, P.A. 1997, "A Resource-Based Perspective on Corporate

Environmental Performance and Profitability.", Academy of management Journal,

vol. 40, no. 3, pp. 534-559.

70. Sheard, P. 1989, "The main bank system and corporate monitoring and control in

Japan", Journal of Economic Behavior & Organization, vol. 11, no. 3, pp. 399-422.

71. Tashakkori, A. & Teddlie, C. 2002, Handbook of mixed methods in social &

behavioral research, SAGE Publications, Incorporated.

72. Thomas, J.O. 2001, "Environment risk perceptions of commercial and industrial real

estate lenders", Journal of Real Estate Research, vol. 22, no. 3, pp. 271-288.

73. Thompson, P. 1998, "Bank lending and the environment: policies and opportunities",

International Journal of Bank Marketing, vol. 16, no. 6, pp. 243-252.

74. Thompson, P. & Cowton, C.J. 2004, "Bringing the environment into bank lending:

implications for environmental reporting", The British Accounting Review, vol. 36, no.

2, pp. 197-218.

75. Van Greuning, H. & Bratanovic, S.B. 2009, Analyzing banking risk: a framework for

assessing corporate governance and risk management, World Bank Publications.

76. Van Greuning, H. & Bratanovic, S.B. 2009, Analyzing banking risk: a framework for

assessing corporate governance and risk management, World Bank Publications.

45 | P a g e

77. Weber, O., Fenchel, M. & Scholz, R.W. 2008, "Empirical analysis of the integration

of environmental risks into the credit risk management process of European banks",

Business Strategy and the Environment, vol. 17, no. 3, pp. 149-159.

78. Weber, O., Scholz, R.W. & Michalik, G. 2010, "Incorporating sustainability criteria

into credit risk management", Business Strategy and the Environment, vol. 19, no. 1,

pp. 39-50.

79. Wolde-Rufael, Y. 2009, "Re-examining the financial development and economic

growth nexus in Kenya", Economic Modelling, vol. 26, no. 6, pp. 1140-1146.

80. Wright, C. 2012, "Global Banks, the Environment, and Human Rights: The Impact of

the Equator Principles on Lending Policies and Practices", Global Environmental

Politics, vol. 12, no. 1.

81. Yamin, F. 2005, Climate change and carbon markets: a handbook of emission

reduction mechanisms, Earthscan.