The relationship between banks and company business models

Finance and financial markets are the engine of sustainability. Financial institutions are one of the main channels influencing

entrepreneurs. By determining the conditions of access to financial services, the financial market affects the decisions and attitudes

of entrepreneurs, including their business models. The purpose of this article is to diagnose whether (and to what extent) banks

affect the decisions and business models of enterprises. The research material is based on data obtained by survey, supplemented

by in-depth interviews with 60 Polish enterprises operating in ESG-sensitive sectors. The study uses correspondence analysis, a

method of multivariate analysis. The results of the study indicate that financial institutions have an impact on enterprises that have

a business model and such enterprises declare their will to co-operate with the bank and to implement the ESG risk reduction

measures recommended by the banks. On the other hand, enterprises that do not have developed business models do not succumb

to the bank's influence and co-operation with the bank is limited to a minimum; usually considering only account keeping and

monetary settlements related to it.

© 2019 The Author(s). Published by Elsevier B.V.

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Peer-review under responsibility of KES International.

Keywords: sustainability, fiancial institutions, business model, correspondence analysis

* Corresponding author. Tel.: +48-91-444-18-01.

E-mail address: magdalena.ziolo@usz.edu.pl

Magdalena ZiołoIwona BąkKatarzyna ChebaAnna Spoz

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2 Author name / Procedia Computer Science 00 (2020) 000–000

1. Introduction

Financial institutions, when determining the criteria for assessing the risk of transactions, select entities by

excluding entities that do not meet their specified requirements in terms of the availability of financial services. In

turn, entities fulfilling the criteria, depending on the assessment of the level of transaction risk and conditioned by the

degree of implementation of the criteria, are differentiated by financial institutions in terms of their terms of service

(including price, range of services, level of monitoring, legal repayment security, and so on). Criteria for assessing the

risk of transactions change under the influence of economy changes. This is particularly evident in the conditions of

"greening" of the economy and social inclusion. These two phenomena, referring to the environmental and social

pillars of sustainable development, respectively, strongly weigh on the necessity of extending the risk assessment

criteria of financial institutions to ESG (environmental, social, and corporate governance) risk. The demand for

extending risk assessment methodologies with ESG components has been emphasized by the United Nations

Environmental Program Financial Initiative (UNEP FI), and the state of implementation of this postulate by financial

institutions, depending on the country and institutions, remains at different levels of advancement. Since 1992, the

United Nations Environmental Program Financial Initiative (UNEP FI) has pointed out the need for financial

institutions to integrate environmental, social, and corporate governance factors (ESG factors) into the decision-

making process [1]. The internal regulations of banks also indicate that environmental risk must be taken into account

with respect to their own ethical guidelines, prestige, and reputation risk [2]. Among financial market actors, the so-

called environmental, social, and governance rating agencies (ESG rating agencies or sustainability rating agencies)

have emerged as key actors, connecting how companies are managing their contributions toward sustainable

development with the decisions taken by the financial markets [3]. To make companies work towards corporate

sustainability (CS), the financial market has been regarded as a key factor [4]. Based on a literature review, no studies

on the link between financial institutions and business models have been published so far and no study has analysed

the impact of financial institutions on sustainable value creation (SVC) in business models in depth. The aim of this

paper is to analyse the impact of bank on companies’ business models. The following research questions have been

raised:

• Do (and how do, if so) banks, as financial institutions, impact the business models of companies towards

sustainability?

• Does the bank's impact depend on whether the company already has a sustainable business model, or if is it

missing?

• Does co-operation with a bank reduce the risk in an enterprise, in the context of sustainability? What kind of risk

is it?

The paper is organized as follows, apart from the abstract and introduction of Section 1, which reviewed the

literature on the issues of business models of enterprises and changes taking place as part of research on business

models. Section 2 contains a description of the research material, methods of its collection, and research methodology.

In Section 3, the results of the study are described and a discussion is carried out. The article ends with a conclusion,

which includes the conclusions of the study.

2. Literature review

In the literature, the concept of a "business model" appeared for the first time in 1957 [5]; however, the term did

not become important until the late 1990s. Amit and Zott [6] stated that a business model “depicts the design of

transaction content, structure, and governance so as to create value through the exploitation of business opportunities”.

Another definition describes a business model as a story which explains how enterprises work and the numbers

reflecting cost, revenue, profit, and loss [7]. Osterwalder and Pigneur [8] understood it as a rationale of how value is

created, delivered, and captured by an organisation. According to them, a business model is like a blueprint for a

strategy to be implemented through organisational structures, processes, and systems. Upward and Jones [9] extended

the canvas of business models to include environmental and social aspects. Currently, business models for companies

to achieve their sustainability goals are becoming sustainable business models [10]. Sustainable business models

leverage firms to integrate their economic objectives with their sustainability ambitions in such a way that the benefits

of all stakeholders are achieved simultaneously [11, 12]. Bocken et al. [13] pointed out that sustainable business

Magdalena Zioło et al. / Procedia Computer Science 176 (2020) 1507–1516 1509

Author name / Procedia Computer Science 00 (2020) 000–000 3

models incorporate stakeholder interests, including environmental and societal aspects. Porter and Kramer [14] argued

that sustainable business models are sources of competitive advantage, in which incorporating sustainable value

propositions, value creation, and value capturing mechanisms bear economic benefits to the companies. The capability

of a fast and successful shift into new business models is one of the most important determinants of sustainable

competitive advantage and is a factor leveraging the sustainability performance of organisations [15]. Witjes and

Lozano [16] surmised that collaboration between procurers and suppliers leads to reductions in raw material utilization

and waste generation through the creation of sustainable business models. Schaltegger et al. [17] showed that the

business case for sustainability requires three conditions to be met simultaneously: voluntary (or mainly voluntary)

activities for society or the natural environment realized by the company, the activity must create a positive business

effect (e.g., cost savings, increase of sales or competitiveness, or improved profitability), and conviction that

management activity leads to the achievement of aims of societal, environmental, and economic effect [18]. Lüdeke-

Freund [19] identified the influence of financing on the sustainable business model. He is convinced that creating and

managing business models is always linked to creating and managing (new) financial models to survive the “valley

of death” and allowing sustainable entrepreneurs to achieve success. The interest of the financial industry in business

models created to address sustainability issues has been increasing; thus, we can identify specific models. Entities

from the financial industry are looking for new ways to create sustainable values, which makes BMfS extremely

relevant. In their recent study, Yip and Bocken [20] focused on archetypes in the banking sector, including innovative

sustainable financial products such as green bonds, crowdfunding, socially responsible funds, and impact investing.

Developing a sustainable business model could be supported by a “brown taxonomy”, the development of which has

been recommended by the Technical Expert Group (TEG) on Sustainable Finance [21]. This recommendation comes

from the TEG’s final report on the EU taxonomy for sustainable (or “green”) activities [22]. A “Brown taxonomy”

could help companies to explain how they are reducing the negative impacts of their business activities as they try to

become more sustainable. Environmental, social, and governance (ESG) investing has become more popular and its

role in credit risk analysis grows [23]. According to the S&P Global Market Intelligence 2019 ESG Survey [24], ESG

investing has the ability to generate better long-term returns, providing evidence that it can have a positive impact on

financial performance. While most respondents have invested a relatively small percentage of their funds in ESG, they

aim to increase this over time [24]. Cripps [25] also noticed that ESG ratings have become embedded in mainstream

investment decision making. Although these ratings are crucial for ESG-focused investors, they have also been

criticized by some experts for their unreliability and inconsistency. Institutional investors more often consider ESG

factors in investment processes. The Stewardship Code in the UK and Japan, and the Code for Responsible Investment

in South Africa, have been updated to reference the ESG factors and risks connected with them [26]. Green bonds

have been playing an important and growing role in funding. In 2019, green bond fund asset growth reached over

100% for three funds and over 80% for several others. Lester [27] explained that these are benefits from rising market

credibility and the arrival of ubiquitous corporate names (such as Pepsi and Apple). The combined value of funds

specialising in green bonds was around $10 billion by the end of 2019; for comparison, in 2018, it was around $6

billion. Ehlers and Packer [28] noticed that the definitions of what makes a bond “green” vary, which has originated

from the evolution of various certification mechanisms. Financial institutions can influence the activities and business

models of companies in various industries. Voysey et al. [29] argued that reducing the cost of funding in the market

for banks booking sustainable trade finance transactions or products is currently the most viable and practical

approach, while systematic consideration of sustainability in credit risk analysis should also be pursued. The report

"Bank 2030. Accelerating the transition to a low carbon economy" [30] presented the methods of banks expanding

coverage of the low carbon economy, which are as follows: financing and intermediation activity (e.g., project

financing), providing product innovation for investment clients that price in externalities (e.g., products that include a

carbon offset mechanism), or extension of the bank’s business or operational remit beyond core financing or

intermediation. Each of these must be used carefully.

3. The characteristics of the research material

Statistical data on the selection of financial institutions were taken from survey "Business models" conducted in

2019 among business owners or their financial directors. The respondents completed the questionnaires independently

using computers (CASI method). The questions concerned the enterprise's cooperation with financial institutions. 60

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respondents participated in the study. 7 questions were selected to achieve the research goal, which were included in

the study. The categories of variables were assigned appropriate symbols associated with the given question (Table

1). Question 4 introduces four variants corresponding to the intensity of the phenomenon, where 1 - means a small

significance, 2 – a medium significance and 3 – a large significance, 4 - the phenomenon does not occur. Whereas in

question No. 6 five options are given, with 1 - the minimum benefit for the company from cooperation and with the

financial institution, and 5 - the maximum one.

Table 1. Questions included in the survey and their symbols

Item Questions/answers Variable

category

1. Which of the features characterizes the motives for your company's cooperation with the bank

A bank offering cheap products and services M1

Bank socially involved M2

Ethical bank M3

Environmentally friendly bank M4

2. Is the bank important for the company's business

Yes B1

No B2

3. What changes did the company have to make to cooperate with a financial institution

Implement pro-environmental activities P1.1–P1.4

Change personnel policy to a more pro-social one P2.1–P2.4

Introduce balanced reporting P3.1–P3.4

Change the policy towards suppliers to take environmental and social factors into account when choosing

them

P4.1–P4.4

Improve financial results P5.1–P5.4

Introduce good management practices P6.1–P6.4

Change the risk management system to take into account environmental and social factors P7.1–P7.4

Other P8.1–P8.4

4. Does the company have a sustainable business model

Yes MB1

No MB2

5. Has the cooperation with the financial institution in the enterprise limited

the environmental risk - Yes, No RŚ1, RŚ2

the social risk - Yes, No RS1, RS2

other risk - Yes, No RIN1, RIN2

6. Benefits for the enterprise resulting from cooperation with a financial institution

Organic business risks; the bank monitors the company's risk and reacts K1.1–K1.5

Transfer of knowledge and good practices - the bank advises solutions beneficial for the company, which

affects the organization and management of the company

K2.1–K2.5

Impact on investment efficiency, the bank analyzes and assesses the company's investments, has an impact

on the conditions of their implementation and the cost of financing

K3.1–K3.5

Increase in the company's credibility for cooperators K4.1–K4.5

Impact on environmentally friendly business solutions through the access to finance innovation for

companies

K5.1–K5.5

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Impact on sustainable development and growth of the company by limiting the financing of "dirty" business

and financing "clean" companies

K6.1–K6.5

Other advantages K7.1–K7.5

7. The size of enterprise

Micro and Small P1

Medium P2

Large P3

4. Methods

Correspondence analysis is one of the methods of statistical multidimensional analysis. This method makes it

possible to accurately recognize the co-occurrence of variable categories (or objects) measured on a nominal scale.

The algorithm for using multidimensional correspondence analysis consists of the following stages

[31,32,33,34,35,36,37]:

1. The determination of the Burt matrix (B), resulting in a symmetrical block matrix in which, apart from the main

diagonal, there are contingency tables corresponding to two different variables, containing the numbers of

objects with the categories of these two features. On the other hand, diagonal matrices are placed on the main

diagonal, in which non-zero values denote the number of occurrences of a given category of the variable.

2. The determination of the dimension of the real space of co-occurrence of the categories of variables K based

on the formula:

𝐾𝐾 = ∑ (𝐽𝐽𝑞𝑞 − 1)𝑄𝑄

𝑞𝑞=1 (1)

where: Jq – the number of feature categories q (q = 1, 2, ..., Q), Q – the number of variables.

3. The verification to what extent the eigenvalues of lower dimension spaces explain total inertia† with the use of

the Greenacre criterion according to which, the major inertia are considered important for the study if they are

greater than 1/𝑄𝑄.

4. The implementation of the modification of eigenvalues according to Greenacre's suggestions in order to increase

the quality of mapping in n-dimensional space in the following way:

𝜆𝜆̃𝑘𝑘 = ( 𝑄𝑄

𝑄𝑄−1)

2

⋅ (√𝜆𝜆𝐵𝐵,𝑘𝑘 − 1

𝑄𝑄)

2

(2)

where: Q – the number of analyzed variables, kB, – the k-th eigenvalue of matrix B (k = 1, 2, ..., K),

(√𝜆𝜆𝐵𝐵,𝑘𝑘 = 𝛾𝛾𝐵𝐵,𝑘𝑘), kB, – the k-th singular value of matrix B.

5. The graphic presentation of the results of correspondence analysis in the n-dimensional space, including the

modification of eigenvalues. The new coordinate values are equal:

𝐹𝐹̃ = 𝐹𝐹∗ ⋅ 𝛤𝛤−1 ⋅ 𝛬𝛬̃ (3)

where: F

~ – the matrix of new coordinate values for variable categories, F* – the matrix of original coordinate

values for variable categories, 1−

 – the inverse diagonal matrix of singular values, 

~ – the diagonal matrix

of modified eigenvalues.

† Total inertia  is the sum of K eigenvalues, where K is a dimension of the actual co-occurrence space.

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5. Results and discussion

Correspondence analysis was carried out on the basis of Burt's matrix measuring 6161 formed out of 22 variables,

whose categories were defined in Table 1. The dimension of the actual space of responses co-occurrence to the

analyzed questions established pursuant to the formula (1) amounted to 52. In the next stage, it was checked to what

extent the eigenvalues of the smaller dimensions explain the total inertia ( = 2,7727). For this purpose, the Greenacre

criterion was used, according to which major inertia greater than 1/Q=1/22=0,0455. Table 2 shows that these are

inertias for K with values up to 20. For these dimensions, the  kmeter values were analyzed. In addition, a graph of

eigenvalues was prepared and using the "elbow" criterion, it was found that the space of co-occurrence presentation

of variable variants should be five-dimensional (Fig. 1) The degree of explanation of inertia in this space is 39.63%

(Table 2). In order to increase the quality of the mapping in the five-dimensional space, the eigenvalues were modified

according to formula (2) and it turned out that after the modification the degree of inertia explanation increased to

53.07%.

Fig. 1. Eigenvalue– elbow criterion

Source: own elaboration pursuant to Table 2.

Table 2. Singular values and eigenvalues together with the degree of explanation of the total inertia in the original and modified versions

K Singular

values k Eigenvali

ues k  /k k k

~  ~

/

~k k~

1 0,6514 0,4243 15,3032 15,3032 0,4030 0,2160 0,2160

2 0,5004 0,2504 9,0323 24,3355 0,2272 0,1218 0,3378

3 0,3898 0,1519 5,4791 29,8146 0,1301 0,0698 0,4076

4 0,3844 0,1478 5,3296 35,1442 0,1261 0,0676 0,4752

5 0,3528 0,1244 4,4878 39,6320 0,1036 0,0556 0,5307

6 0,3455 0,1194 4,3048 43,9368 0,0988 0,0530 0,5837

0,0000

0,0500

0,1000

0,1500

0,2000

0,2500

0,3000

0,3500

0,4000

0,4500

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

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7 0,3417 0,1168 4,2107 48,1476 0,0963 0,0516 0,6353

8 0,3297 0,1087 3,9196 52,0672 0,0887 0,0475 0,6828

9 0,3104 0,0964 3,4750 55,5422 0,0770 0,0413 0,7241

10 0,3047 0,0928 3,3478 58,8900 0,0737 0,0395 0,7637

11 0,2943 0,0866 3,1231 62,0131 0,0679 0,0364 0,8001

12 0,2714 0,0737 2,6563 64,6694 0,0560 0,0300 0,8301

13 0,2685 0,0721 2,5998 67,2691 0,0546 0,0293 0,8594

14 0,2653 0,0704 2,5377 69,8068 0,0530 0,0284 0,8878

15 0,2586 0,0669 2,4118 72,2186 0,0499 0,0267 0,9146

16 0,2541 0,0645 2,3278 74,5464 0,0478 0,0256 0,9402

17 0,2387 0,0570 2,0546 76,6010 0,0410 0,0220 0,9621

18 0,2309 0,0533 1,9237 78,5247 0,0378 0,0202 0,9824

19 0,2185 0,0478 1,7225 80,2471 0,0329 0,0176 1,0000

20 0,2084 0,0434 1,5670 83,4155 𝜆𝜆̃𝑘𝑘 = 1,8654

Due to the large number of analyzed variables and their variants, the interpretation of results obtained in a five-

dimensional space is not possible. Therefore, the Ward method‡was used to determine the relationships between

variable variants. Combining the results of correspondence analysis in a five-dimensional space with the Ward method

has allowed for the separation of three typological groups (Fig. 2):

Group I: (K5.1, K4.1, K2.1, K6.1, K3.1, K1.1, P8.3, K7.2, P6.4, P5.4, P7.4, P3.4, P4.4, P2.4, P1.4) – the

enterprises belonging to this group generally do not see the benefits of cooperation with financial institutions. They

claim that in order to cooperate with these institutions, a company does not have to introduce changes in sustainable

reporting, policy towards suppliers to take environmental and social factors into account when choosing them. In

addition, it does not have to improve financial results or introduce good management practices and change the risk

management system towards the consideration of environmental and social factors.

Group 2: (K7.3, K7.5, P3, RIN1, P8.2, K3.3, P6.2, K2.3, P5.2, K2.3, K2.4, K4.4, K3.4, K1.3, K6.3, P7.2, K1.4,

P4.2, K5.4, P7.3, P4.3, P3.3, P2.3, P1.3, K2.2, P1.2, P2.2, P3.2, M4, P2, K5.3, K4.3, RŚ1, RS1, MB1, P8.1, K6.4,

P6.3, P5.3, M2)

The enterprises from this group have a business model. They believe that cooperation with financial institutions

has reduced all types of risk in their enterprise. They work with banks that are socially involved and environmentally

friendly. In their opinion, to cooperate with financial institutions, the company had to introduce a number of changes

that were of great importance for this cooperation. The most important of them are: the implementation of pro-

environmental measures, the change of personnel policy to a more pro-social one, the change of policy towards

suppliers, the introduction of balanced reporting, the improvement of the financial result and change of the risk

management system towards the consideration of environmental and social factors. According to respondents, the

cooperation with financial institutions will bring many benefits to enterprises, related to, for example, risk reduction,

investment effectiveness, increased company credibility and company growth.

Group 3: (K6.2, K5.2, K3.2, K4.2, P6.1, P5.1, P7.1, P4.1, P3.1, P2.1, P1.1, K3.5, K2.5, K6.5, K5.5, K4.5, K1.5,

RIN2, RŚ2, K7.1, B1, M3, P8.4, P1, RS2, MB2, B2, M1)

This group includes companies of all sizes that speak both positively and negatively about banks. They do not have

a sustainable business model. They are interested in ethical banks offering cheap products and services. They believe

that cooperation with financial institutions has not reduced any type of risk in their enterprise. In their opinion, the

‡ The Ward method is one of the agglomeration grouping methods. It is used in empirical research both in relation to

the classification of objects and features. In this method, the distance between groups is defined as the module of the

difference between the sums of squares of the distance of points from the centers of the groups to which these points

belong [38, 39, 40, 41].

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changes introduced by the company were of minimal importance for starting cooperation with financial institutions.

They see the benefits of cooperation with these institutions, the most important of which are related to the increase in

the company's credibility for business partners, the impact on environmentally friendly financial solutions and the

impact on sustainable development and the growth of the company.

K5:1

K4:1

K2:1

K6:1

K3:1

K1:1

P8.3

K7:2

P6.4

P5.4

P7.4

P3.4

P4.4

P2.4

P1.4

K7:3

K7:5

P3

RIN1

P8.2

K3:3

P6.2

K2:3

P5.2

K2:4

K4:4

K3:4

K1:3

K6:3

P7.2

K1:4

P4.2

K5:4

P7.3

P4.3

P3.3

P2.3

P1.3

K2:2

P1.2

P2.2

P3.2

M4

P2

K5:3

K4:3

RS1

RŚ1

MB1

P8.1

K6:4

P6.3

P5.3

M2

K6:2

K5:2

K3:2

K4:2

K1:2

P6.1

P5.1

P7.1

P4.1

P3.1

P2.1

P1.1

K3:5

K2:5

K6:5

K5:5

K4:5

K1:5

RIN2

RŚ2

K7:1

B1

M3

P8.4

P1

RS2

MB2

B2

M10

5

10

15

20

Linkage distance

Figure 2. The diagram of a hierarchical classification of variable categories performed with the use of the Ward method

Source: own elaboration

As a result of the study, it can be seen that the impact of banks on the business models of enterprises applies only

to the group of enterprises that declare that they have implemented a sustainable business model, while enterprises

which have not adopted such a model are not subject to the influence of banks. There is also a group of enterprises

called “in the middle”, which do not have sustainable business models. The bank does not have an impact on this type

of enterprise; however, enterprises from this group choose banks to comply with their business ethics, as co-operation

with such a bank makes the company more credible and has an impact on its positive perception co-operators. The

levels of impact of banks on enterprises are broadly defined and relate to financial management, human resources

management, and environmental and social management. In these areas, enterprises feel the reduction of

environmental, social, and management risk as a result of co-operation with the bank. Sustainable reporting by the

company is a key element to limiting environmental, social, and management risk. This type of reporting allows us to

obtain comprehensive information on the company's risk exposure and the sources of such risk. This information is

necessary to design the company's risk management system and, as a consequence, translates into its financial

security—in particular, its liquidity and profitability—which are key from the point of view of risk assessment by the

bank and affect the valuation of the banking services for which the financial institution pays. The introduction of pro-

environmental and pro-social activities by an enterprise limits its risk exposure, thus reducing the bank's risk resulting

from co-operation with a given company, which includes valuation of the company's assets (which are legal collateral

for the bank), or collateral for the company's financial stability, which could be violated as a result of imposing fines

on the company for non-compliance with environmental protection rules or employee rights. Additionally, enterprises

with sustainable business models and which co-operate with banks limit the risk of damaging the bank’s reputation,

which is one of the leading factors for them.

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Author name / Procedia Computer Science 00 (2020) 000–000 9

6. Conclusion

This article addresses the problem of the impact of banks on the sustainable business models of enterprises. The

analysis was based on data collected by a survey, supplemented by in-depth interviews in which 60 managers or

owners of enterprises were examined from sectors exposed to environmental, social, and managerial risk. The study

was conducted in 2020 and used correspondence analysis, a multivariate statistical method. As a result of our research,

the research questions raised in the study were answered. It was shown that banks only have an impact on enterprises

that have implemented sustainable business models. In the case of enterprises which did not have such models, the

bank’s 'influence on enterprises' decisions were not observed. In the case of enterprises in which the bank's impact on

the business model was observed, this impact concerned such areas as financial management, risk management, human

resources management, and pro-environmental and pro-social activities. These enterprises observed the impact of co-

operation with the bank as positive, due to the reduction of environmental, social, and management risk. In the other

two groups of enterprises (i.e., those deprived of sustainable business models), the influence of banks was not noted.

However, in the case of the group of enterprises included in group 3, it was noticed that, although they were not

enterprises which declare they should not influence the bank, they co-operated with the bank in order to build a positive

image and credibility among their subcontractors. This justifies the declaration that, when these enterprises are

choosing a bank, they prefer an ethical bank. Therefore, a group of three enterprises, despite not perceiving an impact

on their business risk by banks, co-operated with an ethical bank due to image-related premises.

Acknowledgement

Research results presented in this paper are an integral element of research project implemented by the National

Science Centre Poland under the grant OPUS16 no UMO-DEC-2018/31/B/HS4/00570.

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