Developing a Sustainability Credit Score System

Abstract

Within the banking community, the argument about sustainability and profitability tends to be inversely related. Our research suggests this does not need to be strictly the case. We present a credit score system based on sustainability issues, which is used as criteria to improve financial institutions’ lending policies. The Sustainability Credit Score System (SCSS) is based on the analytic hierarchy process methodology. Its first implementation is on the agricultural industry in Brazil. Three different firm development paths are identified: business as usual, sustainable business, and future sustainable business. The following six dimensions are present in the SCSS: economic growth, environmental protection, social progress, socio-economic development, eco-efficiency, and socio-environmental development. The results suggest that sustainability is not inversely related to profit either from a short- or long-term perspective. The SCSS is related to the Equator Principles, but its application is not driven to project financing. It also deals with short- and long-term risks and opportunities, instead of short-term sustainability impacts.

Appendices

Appendix 1: Examples of Firms’ Practices in the Brazilian Sugar Industry

BAU	SB	FSB
Geographical occupation
The industry currently carries out geographical occupation according to the Sugarcane Agroecological Zoning and to licenses granted to single firms	The industry complies with the Forest Code and creates its own legal reserves or in association with others	There is a balance between planted and preserved areas, owned by either enterprises or by suppliers, regardless of the biome where they are, ensuring local biodiversity and protecting water springs and hydrographic basins
The industry has not yet expanded as necessary to respond to the current demand for sugar and ethanol	Adequate expansion, in areas large enough to respond to the demand for ethanol and sugar, preserving biomes, water springs, hydraulic basins and biodiversity	The industry does not need to expand anymore, since its productivity is sufficient for responding to the market demand for products
Although new fully mechanized plantations are being developed, the industry still occupies a large area (mainly in the Northeast) where declivity is higher than 12 %, rendering the burning of leaves necessary	All plantations are in areas with declivity below 12 %, fully mechanizable and free from the burning of leaves	The soil of occupied areas is thoroughly researched, as well as water availability, biodiversity and adequate sugar cane varieties, enabling the development of an agriculture of precision
The industry competes with food production in areas where farmers may alternate between sugar cane and other crops, such as leguminous crops, depending on the market value of each crop	The industry occupies areas where it does not compete with food production or, whenever there is competition, crops are alternated in an efficient way	Short cycles of different crops in the same area enable three to four complementary and different crops a year and help improve soil productivity (for instance sugar cane, beans, peanuts and forage)
Climatic changes still do not impact on current plantations and most of the industry seems not to be concerned with anticipating what may happen to its enterprises	The industry invests in research on climatic changes, identifying new and adequate areas for sugar cane cultivation	Occupation of new areas, selected according to climatic changes, without impacting on biomes and biodiversity
Clean energy/new products from ethanol
The sugar and ethanol industry’s carbon footprint increases due to the use of fossil fuel to power sowing and harvesting machines and vehicles that transport goods between farms, mills and points of internal commercialization and exportation	Gradual replacement of vehicles and equipment powered by fossil fuels in favor of biofuels and machines equipped with more efficient engines	Transportation during planting, harvesting and commercialization is carried out with minimal carbon emission (vehicles and machines are powered by biofuels and technologies such as alcohol ducts)
The industry is under the influence of an erratic policy dictated by the Brazilian Government in regard to both taxes and stimulation of the production of ethanol (control over gasoline prices) and bioelectricity (the price of biomass energy does not reach attractive numbers in auctions)	Influence on public policies to stimulate production and commercialization of ethanol and bioelectricity, aiming at the reduction of CO2 emissions	Ethanol and bioelectricity are important components of both Brazilian and global energy matrices, together with public policies and incentives adequate for the society’s high demand for clean and renewable forms of energy
Ethanol from sugar cane is still not competitive with ethanol from corn	Research on second- and third-generation ethanol and on engines powered by biofuels is at an advanced stage, making sugar cane ethanol more competitive and accepted, especially in relation to fossil fuels, which incorporate the mitigation costs of social and environmental damage	Ethanol’s traceability increases its value in the international market
Bioelectricity from sugar cane bagasse makes mills self-sufficient, but only 25 % of the mills sell energy to public utility companies due to the high cost of infrastructure	Incentives for the production and commercialization of bioelectricity by construction of adequate distribution infrastructure	Bioelectricity from sugarcane bagasse has lower production costs and higher market value
Incipient research on alcohol chemistry and bioplastics, as well as on sugar cane fuel for aviation	Alcohol chemistry products, ethanol aviation fuel and bioplastics are commercially available, but still on their way to becoming sustainable products	Expanded portfolio of alcohol-chemical products, bioplastics and fuel for aviation widens the market for the sugar and ethanol industry

Appendix 2: Risks and Opportunities for a Commercial Bank in Relation to the Brazilian Sugar Industry

Credit Risks

• (1) Companies displaying the characteristics, or risk factors, listed below may present credit risks to banking operations:

  • “Non-compliance” with legislation.

  • Use of sugar cane varieties inappropriate for the region.

  • Operation in an area where the water supply is compromised.

  • Low productivity.

  • Limited capability to manage the product mix.

  • Sugar cane planted in areas of declivity higher than 12 %.

  • Manual harvesting is not replaced by mechanized harvesting, and burning of leaves is not abandoned.

  • Labor practices inadequate for retaining the agricultural labor force.

  • Inadequate use of water.

  • Contamination of soil and groundwater by fertilizers and agrochemicals.

  • Inadequate fertilization of plantations.

  • Inadequate managerial and governance practices.

  • Use of obsolete equipment throughout the production process.

  • Non-use of technological improvements such as new sugar cane varieties, sorghum, direct planting, precision agriculture, generation of electrical power, etc.

  • Failure to obtain environmental licenses.

  • Inappropriate contracts with sugar cane suppliers.

  • Negligence in tracking the impacts of climatic changes.

  • Co-responsibility in lawsuits filed against companies of the industry with regard to socio-environmental issues.

Reputational Risks

• (1) Pressure (from media, society, non-governmental organizations, etc.) on clients due to incorrect socio-environmental postures, such as

  • Illegal use of transgenic varieties;

  • Contamination of soil and groundwater and failure to preserve water;

  • Uncontrolled product quality and safety during distribution;

  • Dismissal of large numbers of employees without adequate requalification and attempt to reinsert into the labor market;

  • Burning of sugar cane leaves prior to harvest;

  • Use of machines that damage the soil;

  • Production of sugar using toxic elements or contaminants.

• (2) Financing of companies that are

  • Operating illegally;

  • Adopting illegal labor practices and/or committing human-rights abuses;

  • Using new technologies that are illegal according to the current legislation;

  • Distributing adulterated ethanol or evading sales taxes.

• (3) Inappropriate behavior of clients relative to their managerial practices and information transparency.

Opportunities

• (1) Provision of consulting advice to clients (in seminars, workshops, and published papers) on

  • Areas more appropriate for sugar cane cultivation as a consequence of climatic changes;

  • Varieties appropriate for given regions and biomes and new cultivation techniques.

• (2) Financing and investments to help the industry

  • Face productivity challenges related to the use of adequate sugar cane varieties;

  • Expand industrial facilities (construction of new mills, renovation of existing facilities, and introduction of equipment embedding more advanced technologies);

  • Produce second- and third-generation ethanol;

  • Replace the existing fleet by vehicles powered by renewable energy;

  • Mechanize production (purchase of equipment, employees’ qualification program, etc.);

  • Develop more sustainable equipment to manage sugar cane plantations;

  • Tackle the high costs related to compliance with some legal requirements, such as the use and disposal of water;

  • Change the fertilization processes (construction of vinasse ducts, research on soil type, and adequate amounts of fertilizer, etc.);

  • Introduce international governance standards and data transparency;

  • Close the water and natural resources cycles in industrial processes.

• (3) Tracking information on

  • Technologies suitable for trucks, machines, and equipment powered by ethanol;

  • The development of new markets and products from sugar cane;

  • Initiatives to qualify workers, supporting intra-industry programs, institutions, and NGOs;

  • Research on new sugar cane varieties and new cultivation techniques;

  • Climatic changes.

Appendix 3: The Methodology of the Sustainability Credit Score System

The comparison matrix has the following generic format:

$$ A = \left( {a_{ij} } \right)_{1 \le i,j \le n} $$

where

$$ a_{ij} = \left\{ {\begin{array}{ll} {1\;\; {\text{if}}\;i = j} \\ {{\raise0.7ex\hbox{$1$} \!\mathord{\left/ {\vphantom {1 {a_{ji} \;\;{\text{if}}\;i \ne j}}}\right.\kern-0pt} \!\lower0.7ex\hbox{${a_{ji} \;\;{\text{if}}\;i \ne j}$}}} \\ \end{array} } \right. $$

The numerical values in the comparison matrix can be obtained in Saaty’s Relative Importance Table, which follows:

Intensity	Relative importance
1	Equal relative importance
3	Slightly superior relative importance
5	Strong relative importance
7	Very strong relative importance
9	Absolute relative importance

We build a six-dimension comparison matrix. Two premises are assumed before the comparisons are carried out: the first defines that the intersections between two dimensions of sustainability are preferable to singular dimensions, because practices in the first fields tend to balance distinct objectives better. The second premise prescribes that, when compared with each other, the areas of intersection of dimensions and singular dimensions have similar relative importance. This is to avoid focusing on a specific aspect (for instance, prioritization of economic growth).

We obtain the following six-dimension comparison matrix:

	EE	SA	SE	EP	EG	SP
EE	1	1	1	3	3	3
SA	1	1	1	3	3	3
SE	1	1	1	3	3	3
EP	1/3	1/3	1/3	1	1	1
EG	1/3	1/3	1/3	1	1	1
SP	1/3	1/3	1/3	1	1	1

For the comparison matrix above, in line with the AHP, the normalized relative-weight vector may be obtained as follows:

SP	0.25
SE	0.25
EG	0.25
EE	0.08
OS	0.08
AS	0.08

The inconsistency level is 0 % (below the usual 10 % level, which is the maximum accepted level in the AHP methodology).

The next phase requires the preparation of comparison matrices for the indicators associated with each dimension considered. For each indicator, four relative degrees—relative to nBAU, BAU, SB, and FSB—are assigned, as well as the relationship to GRI. The last step, not presented here, is the development of the questionnaire based on each issue and that is used to determine each firm’s sustainability credit score.

The comparison matrices and their weights for the sugar industry are

• (1) Eco-efficiency

  • (a) Use of water (EN9)

  • (b) Improvements to cultivation and production equipment (EN18)

  • (c) Productivity and sugar cane variety (EN14)

The comparison matrix is

	a	b	c
a	1	3	1
b	1/3	1	1/3
c	1	3	1

The normalized relative-weight vector is

a	42.86 %
b	14.29 %
c	42.86 %

The level of inconsistency for this last comparison matrix is 0.00 %.

• (2) Socio-environmental

  • (a) Environmental impacts on the community (SO1)

  • (b) Reduction in fossil fuel use (EN17 and EN29)

  • (c) Elimination of burning practices (EN16)

The comparison matrix is

	a	b	c
a	1	3	1
b	1/3	1	1/3
c	1	3	1

The normalized relative-weight vector is

a	42.86 %
b	14.29 %
c	42.86 %

The level of inconsistency for this last comparison matrix is 0.00 %.

• (3) Socio-economics

  • (a) Compliance (PR9)

  • (b) Requalification of workers (LA11)

  • (c) Influence over public policies (SO5)

The comparison matrix is

	a	b	c
a	1	1	3
b	1	1	3
c	1/3	1/3	1

The normalized relative-weight vector is

a	42.86 %
b	42.86 %
c	14.29 %

The level of inconsistency for this last comparison matrix is 0.00 %.

• (4) Environmental Protection

  • (a) Reduction in the use of chemical inputs such as fertilizer and agrochemicals (EN22)

  • (b) Compliance with natural resources and biodiversity protection legislation (EN28)

  • (c) Production expansion without an increase in environmental impacts (EN11 to EN13)

The comparison matrix is

	a	b	c
a	1	1	3
b	1	1	3
c	1/3	1/3	1

The normalized relative-weight vector is

a	42.86 %
b	42.86 %
c	14.29 %

The level of inconsistency for this last comparison matrix is 0.00 %.

• (5) Economic growth

  • (a) Company governance/information transparency (LA13)

  • (b) Product development and evolution (EC1)

  • (c) Economic development of the community (EC7)

The comparison matrix is

	a	b	c
a	1	1	3
b	1	1	3
c	1/3	1/3	1

The normalized relative-weight vector is

a	42.86 %
b	42.86 %
c	14.29 %

The level of inconsistency for this last comparison matrix is 12.32 %.

• (6) Social progress

  • (a) Adherence to the National Good Labor Practices Commitment (HR7)

  • (b) Human-rights-related policies and procedures (HR8)

  • (c) Investments in the development of communities (EC8 and EC9)

The comparison matrix is

	a	b	c
a	1	1	3
b	1	1	3
c	1/3	1/3	1

The normalized relative-weight vector is

a	42.86 %
b	42.86 %
c	14.29 %

The level of inconsistency for this last comparison matrix is 0.00 %.

Finally, the comparison matrix for the four possible answers considered—“FSB,” “SB,” “BAU,” and “nBAU”—is

	FSB	SB	BAU	nBAU
FSB	1	1/3	1/5	1/9
SB	3	1	1/3	1/5
BAU	5	3	1	1/3
nBAU	9	5	3	1

The normalized relative-weight vector is

a	53.71 %
b	27.85 %
c	13.53 %
d	4.91 %

The level of inconsistency for this last comparison matrix is 3.81 %.