How to cite:

Gerelt-Od. U, Delgertsetseg.D, Chimedtsogzol.Yo, Oyundari.B.

(2022). Factors Affecting Borrowers’ Intention in Peer-To-Peer

Lending Platform in Mongolia. Journal Eduvest. Vol 2(7): 1.306-1.311

E-ISSN:

2775-3727

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Eduvest – Journal of Universal Studies

Volume 2 Number 7, July, 2022

p- ISSN 2775-3735- e-ISSN 2775-3727

FACTORS AFFECTING BORROWERS’ INTENTION IN

PEER-TO-PEER LENDING PLATFORM IN MONGOLIA

Gerelt-Od. U, Delgertsetseg. D, Chimedtsogzol. Yo, Oyundari. B

National University of Mongolia, Mongolia

Email: [email protected], [email protected],

[email protected], [email protected]

ABSTRACT

The current paper aims to examine factors that influence borrowers’ intention

to borrow from Peer-to-Peer lending platform in Mongolia. This topic has been

attracting researchers’ interest especially since 2008 when the 3rd round of

fintech development starts over the developed countries. The most of those

studies focus on investigating the factors that explain borrowers’ intention to

borrow, and a few of them research this perspective from the investors’ side. It

is hardly to find the study that explain intentions of parties to participate in a

P2P lending platform in Mongolia. Our research tries to fill this gap by studying

factors influencing borrowers’ intention in Mongolian fintech market. We have

used the TAM model as a theoretical framework and have collected survey

questionnaires from investors and borrowers from all fintech companies in

Mongolia. The result shows that borrowers’ intention is mostly driven by initial

trust and perceived risk. Other variables, perceived ease of use and perceived

security, have no impact on borrowers’ decisions to participate in P2P platform.

KEYWORDS

Peer-to-peer (P2P), Borrowers, Mongolia

This work is licensed under a Creative Commons Attribution-

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INTRODUCTION

The era of the Fourth Industrial Revolution, characterized by speed,

automatization, and ease, has brought changes and reforms to many sectors around the

world, including health, tourism, and real estate, and has had a significant impact on the

financial sector. Technology-based, smartphone-based financial services reach a group of

 
Gerelt-Od. U, Delgertsetseg.D, Chimedtsogzol.Yo, Oyundari.B 
Factors Affecting Borrowers’ Intention in Peer-To-Peer Lending Platform in Mongolia 
    1.307 
people with sudden financial needs and urgent need for a small amount of money, allowing 
them to access credit services regardless of time or location without collateral.  
Promoting sustainable economic growth and  reducing inequality and  poverty are 
important goals for policymakers in many countries (Staníčková, 2017). Achieving both 
goals at the same time means that the country is creating inclusive growth in financial 
markets. “Innovation” is the key to increasing access to financial markets. Advances in 
products, services, and technology resulting from innovation promote competition in the 
marketplace,  reduce  costs,  and  increase  efficiency  (Ranieri  &  Almeida  Ramos,  2013). 
There are many good examples around the world of technologically advanced financial 
products and services or fintech that provide financial services and access to many people 
who have been left out of the formal financial markets (Fornell & Larcker, 1981b).  
Increasing  access  to  financial  markets  through  fintech  products  and  services 
increases  the  chances  of  achieving  sustainable  development  goals.  In  short,  financial 
innovation is a bridge between the financial sector and sustainable development.  
P2P  lending,  Internet  lending  or  person-to-person  online  lending,  involves 
individuals or “peers” who use online platforms without the involvement of a financial 
institution as a middle man (FUND, 2015).  
The  peer-to-peer  (P2P)  lending  platform  has  become  popular  and  is  gradually 
becoming an alternative to the traditional model of financing (Zetzsche et al., 2019). P2P 
lending is considered an innovative approach that unites borrowers and lenders without 
collateral or the intermediation of financial institutions (Hoang et al., 2022). 
The  Financial  Stability  Board  (FSB)  defines  fintech  as  “technologically  enabled 
financial innovation that could result in new business models, applications, processes, or 
products with an associated material effect on financial markets and institutions, and the 
provision  of  financial  services”.  This  definition  has  also  been  adopted  by  the  Basel 
Committee on Banking Supervision (BCBS), and they introduced areas that fintech covers 
can be broadly described as: (i) credit, deposits, and capital-raising services; (ii) payments, 
clearing and settlement services, including digital currencies; (iii) investment management 
services  (including  trading);  and  (iv)  insurance.  Part  of  the  technological  backbone  of 
fintech is the  Blockchain technology.  It  has  been  suggested that there  have  been  three 
phases of fintech and we are currently in the third phase (Zabala Aguayo & Ślusarczyk, 
2020). 
International studies have highlighted the importance of online P2P credit services, 
including the efficient allocation of assets, high interest rate competition, low transaction 
fees, and a mixed credit service mechanism (Arner et al., 2020). Investment in the fintech 
sector is growing rapidly year by year, in 2019 worldwide $135.7 billion invested in the 
fintech sector (Chikalipah, 2020; Farahani et al., 2022). P2P loans increased by 262 percent 
from more than $26 billion to $68 billion from 2015 to 2019. Above all these suggests that 
P2P lending is evolving into a form of lending that will have a significant impact on future 
financial market development. 
In Mongolia, as of the first quarter of 2020, a total of 388.3 thousand borrowers in 
financial sector received technology-based  loan  services, and  the number of  borrowers 
receiving these services is growing rapidly. The loan amount per person receiving this 
service is 336.0 thousand MNT, total loan amount already reached more than 80 billion 
MNT  (Macchiavello  &  Siri,  2022).  These  are  major  incentives  to  increase  access  to 
financial services by promoting competition and increasing the efficiency of products and 
services. There are 15 non-banking financial institutions that are offering P2P lending in 
Mongolia. This research was conducted with the aim of knowing what factors influence a 
borrower's intention to obtain a P2P loan. 
 

Eduvest – Journal of Universal Studies

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1.308 http://eduvest.greenvest.co.id

RESEARCH METHOD

We have prepared survey questions relating to our dependent and independent

variables, precisely 5 items for perceived risk, 3 items for perceived trust, 3 items for

perceived ease of use, 3 items for perceived security and 3 items for initial borrow intention.

It is important to mention that all of our questionnaires have reached all fintech companies’

borrowers and 347 respondents participated. For measurement, Likert-type five-point scale

was used ranging from 1 “strongly disagree” to 5 “strongly agree”.

In order to analyze the intention of borrowers in P2P platform in Mongolia, we used

Partial Least Square (PLS) analysis that is mainly used among researchers on this topic.

RESULT AND DISCUSSION

Majority of respondents (borrowers) were women representing 73%, with men

representing 27%. In case of age group, the largest percentage goes to age group between

19-24, followed by age group of 25-30 (17.6%) and 41-50 (16.1%) respectively. Most of

the respondents work in private companies, government organization and students.

Table 1 Characteristics of Respondents

Number

Percent

Gender

Male

Female

253

Age Group

Up to 18

2.9

19-24

120

34.6

25-30

17.6

31-35

11.2

36-40

9.6

41-50

16.1

More than 51

Occupation

Government organization

20.8

Private

115

33.1

Self-employed

10.4

Student

28.2

Other

7.5

Income

Up to 200.000 MNT

201.000-400.000 MNT

2.8

401.000-700.000 MNT

700.000-1.000.000 MNT

20.5

1.000.001-1.500.000 MNT

20.7

1.500.000-2.000.000 MNT

7.8

More than 2.000.001 MNT

9.5

Model assessment

For model assessment, the convergent validity of items loading (Loading), average

variance extracted (AVE), and composite reliability (CR) were tested.

Gerelt-Od. U, Delgertsetseg.D, Chimedtsogzol.Yo, Oyundari.B

Factors Affecting Borrowers’ Intention in Peer-To-Peer Lending Platform in Mongolia

1.309

The result shows that indicator loading was more than 0.5 meaning that they meet the

criteria, three items (C1, C3, C4). Therefore, those items were removed because of the

lower threshold of 0.5. Then all items met the AVE threshold of 0.5, and CR threshold of

0.7.

Table 2 AVE Result

Items

Loadings

AVE

Perceived

ease of use

0.922

0.838

0.939

0.94

0.883

Perceived

security

0.792

0.665

0.855

0.752

0.895

Perceived risk

0.632

0.774

0.763

0.826

Perceived

Trust

0.731

0.635

0.839

0.837

0.819

Initial Borrow

Intention

0.914

0.709

0.878

0.907

0.685

a- All items loadings > 0.5 indicates Indicator Reliablibilty (Fornell & Larcker,

1981a)

b- All average Variance Extracted (AVE) > 0.5 as indicates Convergent Reliability

(Bagozzi et al., 1998) (Fornell & Larcker, 1981a)

c- All Composite Reliability (CR) >0.7 indicates Internal Consistency (Gefen,

2000)

*-removed because of lower threshold of loanding

Then, we have tested discriminant validity using the formulation postulated by

Fornell & Larcker (1981b). The square root of AVE from each construct was higher than

the correlations between construct and other constructs, meaning that there is discriminant

validity.

Table 3 Discriminant Validity

Initial

Trust

Initial

Borrow

Intention

Perceived

ease of use

Risk

Security

Initial Trust

0.797

Initial Borrow

Intention

0.566

0.842

Perceived ease of use

0.524

0.352

0.915

Risk

-0.092

-0.235

-0.183

0.709

Security

0.208

0.240

0.187

-0.095

0.815

Eduvest – Journal of Universal Studies

Volume 2 Number 7, July 2022

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The diagonals are the square root of the AVE of the latent variables and indicate the

highest value in any column or row. It indicates that there is discriminant validity. In

summary, the measurement model demonstrates adequate reliability, convergent validity

and discriminant validity.

Then R

was used for goodness of model fit, and in our model R

was 0.368. That

means the 36.8% variance of intention of borrowers to borrow from P2P platforms can be

explained by the independent variables of perceived ease of use, security, risk and trust.

Afterwards, bootstrapping analysis with resampling 500 was managed to determine

the significance of coefficients. Interesting result was found that perceived risk and trust

have a significant relationship with the intention of borrowers in P2P lending platform, and

other two variables have no impact.

As a result, we can see that trust is a very important factor that P2P lending platform

exist in Mongolia in terms of both investor and borrowers.

Table 4 P2P Lending Platform in Mongolia

Hypotheses

Relationship

Beta

T-Statistic

P-Values

Perceived ease of use

0.025

0.092

0.349

0.727

Perceived Security

0.130

0.140

0.813

0.417

Perceived Risk

-0.187

0.088

1.990

0.047

Perceived Trust

0.504

0.082

6.209

0.000

CONCLUSION

P2P lending has been developing for last 4-5 years in Mongolia, and its rapid growth

attracted our interest to study intention of borrowers to participate in P2P platforms.

According to the TAM model, initial intention can be explained by explanatory variables,

namely perceived ease of use, security, risk and trust.

As a result of partial least square analysis, borrowers’ intention to borrow from P2P

lending platform is influenced by trust and perceived risk. Other variables have no impact.

Therefore, trust effects positively on initial intention of borrowers, meaning that our

hypothesis is supported. Moreover, perceived risk effects negatively on the initial intention

of borrowers.

Through this research, we try to give contribution to the development of P2P lending

framework. Regulators in Mongolia should consider this result to make their policy

decisions. By using PLS analysis, our study can contribute to the literature of this field in

Mongolia.

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