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American Journal of  Financial 
Technology and Innovation (AJFTI)

Agricultural Loan Management by Mobile Banking: Opportunities and Challenges
Tanveer Ahmed Siddquee1* 

Volume 3 Issue 1, Year 2025
ISSN: 2996-0975 (Online)

DOI: https://doi.org/10.54536/ajfti.v3i1.5624
https://journals.e-palli.com/home/index.php/ajfti

Article Information ABSTRACT

Received: February 25, 2024

Accepted: March 14, 2024

Published: September 06, 2025

In Bangladesh, agriculture is not merely an economic activity, it is the backbone of  rural 
life. Yet, traditional agricultural loan systems often leave farmers disadvantaged due to long 
processing times, excessive paperwork, and limited access to financial institutions. This 
study aims to evaluate the effectiveness of  a digitized agricultural loan system powered by 
Mobile Financial Services (MFS) and electronic Know Your Customer (e-KYC) processes 
in overcoming these barriers. Using survey responses from 111 professionals engaged in 
agricultural loan management, the study compares traditional loan practices with a proposed 
automated model. The findings reveal that the digital system reduces loan approval time by 
an average of  62%, cuts operational costs by approximately 45%, and significantly improves 
accessibility and transparency. While the model promises transformative benefits, constraints 
such as inadequate rural internet infrastructure, low digital literacy among farmers, and the 
lack of  digitized land and identity records pose challenges. Therefore, the study recommends 
coordinated efforts from policymakers, banks, telecom operators, and agricultural agencies to 
expand rural connectivity, simplify user interfaces, digitize essential documents, and provide 
digital training for farmers. By implementing these strategies, Bangladesh can modernize its 
agricultural finance ecosystem, promote financial inclusion, and enhance rural resilience.

Keywords
Agricultural Loans, Conventional 
Loan Management System, Digital 
Transformation, Loan Automation, 
Mobile Financial Services (MFS)

1 Motijheel Branch, Bangladesh Development Bank PLC, Dhaka, Bangladesh
* Corresponding author’s e-mail: tanveer.bdbl@gmail.com

INTRODUCTION
Agriculture is considered backbone economy of  
Bangladesh, contributing both directly and indirectly to 
national development. In recent years, this sector has 
played an increasingly vital role in ensuring food security, 
creating employment, and driving GDP growth. According 
to Bangladesh Bank, agriculture contributed 11.38% and 
11.04% to the gross domestic product (GDP) during the 
fiscal years 2022–2023 and 2023–2024, respectively (BBS, 
2023, 2025). Beyond its direct contribution, agriculture 
supports the growth of  the industrial and service sectors 
by supplying raw materials and labor. As per the Labor 
Force Survey conducted in 2022, approximately 45.40% 
of  the employed population in Bangladesh are engaged 
in agricultural activities, emphasizing its significance in 
the country’s labor market (BBS, 2022). The agricultural 
sector is crucial in helping communities adapt to climate 
change, ensuring we have enough food, and protecting 
livelihoods in rural areas. It also plays a vital role in 
achieving the United Nations’ SDGs, including ending 
hunger, reducing poverty, and promoting decent work. 
To make progress on these goals, it’s important to provide 
timely support to farmers. Agricultural loans are one way 
to ensure they have the resources they need to grow 
their crops, improve productivity, and secure a better 
future (UN, 2024). In Bangladesh, agricultural loans are 
small, low-interest loans provided to farmers for crop 
cultivation. In the 2023-2024 fiscal year, the target was 
set at BDT 35,000 crore, but scheduled banks disbursed 
BDT 37,153.90 crore, benefiting 3.7 million farmers. 
The Bangladesh Rural Development Board (BRDB) also 
supported rural farmers, with a target of  BDT 1,423 

crore. These loans are part of  the Agricultural and Rural 
Credit Policy, overseen by Bangladesh Bank (Bangladesh 
Bank, 2024). Despite efforts to improve, Bangladesh’s 
agricultural loan system remains outdated and inefficient. 
The process is still largely manual, causing delays in loan 
disbursement. Farmers often struggle to get loans on time 
due to lengthy procedures and required in-person visits, 
especially during the planting season. This delay reduces 
the effectiveness of  the loans, impacting agricultural 
productivity and the economy (Thakur, 2024). A major 
challenge is the inaccessibility of  bank branches, which 
are mostly located in urban areas, while many farmers live 
8 to 10 kilometers away in rural areas. To access a small 
loan of  less than BDT 50,000, a farmer spends around 
BDT 2,500 on travel, which is 5% of  the loan amount. 
Including repayment, the total cost of  loan management 
rises to 10-15%. The process can take 5 to 10 days, leading 
to significant opportunity costs for farmers who lose 
valuable time from their farming work (Ahmed, 2024). The 
documentation process is a hassle for farmers, as they have 
to visit multiple offices for document verification. While 
some documents, like National IDs and land records, are 
online, key documents like title deeds still need manual 
checks, slowing down loan processing. This highlights 
the need for a fully automated agricultural loan system 
in today’s tech-driven world (NirvikBD, 2025). Getting 
a farm loan is still a hassle. Farmers often have to run 
between offices like the Union Land Office and Upazila 
Parishad for document checks. While some records, like 
National IDs and land ownership, are online, key papers 
like title deeds still need manual verification. This slows 
everything down. In today’s digital world, it’s clear we 



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need a fully automated system to make agricultural loans 
faster and easier (Abdullah, 2025; Arifuzzaman & Islam, 
2024). Mobile financial services like Nagad, Bikash and 
Rocket are already part of  daily life in rural Bangladesh. 
By connecting these platforms to the agricultural loan 
system, farmers could apply for loans, get funds, and 
make repayments all from their phones. It’s a smart way 
to cut down on bank visits and make the process faster 
and easier (Prodhan et al., 2024; Yesmin et al., 2019). A 
key requirement for this transformation is the execution 
of  electronic Know Your Customer (e-KYC) protocols. 
E-KYC allows individuals to open a bank account using 
their National ID card by submitting a selfie and a photo 
of  the ID through a mobile phone. The system verifies 
the provided information in real time using the national 
ID database (BFIU, 2019). Once verified, the account 
becomes fully operational. By combining e-KYC with 
MFS and online document verification, an end-to-end 
automated loan management process can be developed. 
This system must be user-friendly, especially considering 
that many farmers have limited digital literacy (BFIU, 
2019; World Bank, 2017). As industries worldwide go 
digital, it’s time for agriculture in Bangladesh to catch up. 
Automating the agricultural loan process using mobile 
financial services (MFS) can make borrowing quicker, 
cheaper, and more accessible for farmers. This research 
aims to identify the challenges in the current system and 
propose a digital, MFS-based loan framework that is 
cost-effective, legally sound, and scalable. The goal is to 
reduce loan delays, cut transaction costs, and give farmers 
timely access to credit empowering them and boosting 
the agricultural economy.

LITERATURE REVIEW
Agriculture is vital to Bangladesh’s economy, contributing 
11.02% to GDP in FY 2023–24. It also supports industrial 
and service sectors and employs 44.41% of  the workforce 
(Labor Force Survey, 2023). Agriculture plays a significant 
role in food production, exports, employment generation, 
and resilience against climate change. Technological 
advancement in agriculture is essential for food security, 
poverty reduction, and rural welfare. Therefore, the 
government formulates agricultural loan policies annually 
to ensure adequate financial support (Bangladesh Bank, 
2025a). Agricultural loans are available for genuine 
farmers and individuals engaged in income-generating 
rural activities. Special priority is given to landless, 
marginal, and small farmers (less than 2.47 acres of  
land). Sharecroppers can also access loans upon verifying 
their involvement in production and residency within 
the bank’s operational area, with NID and landowner 
certification (Bangladesh Bank, 2025a). Banks are 
expected to simplify loan forms for easy understanding by 
farmers. Instructions must be clear and comprehensive. 
Crop loan applications should be processed within 
10 working days, and disbursement should occur at 
least 15 days before the crop season begins. Rejected 
applications must be documented with reasons for audit 

and verification. Crop collateral is acceptable for up to 5 
acres of  cultivation. Larger loans may require traditional 
collateral depending on the bank-customer relationship. 
Loans up to BDT 500,000 for income-generating rural 
activities can be disbursed without collateral (Bangladesh 
Bank, 2025a). Banks can verify NID and smart card 
data online through the Bangladesh NID Application 
System. This digital verification ensures authenticity and 
transparency in financial services (Economy, 2015). The 
e-KYC system allows digital identity verification and is 
used to open bank or MFS accounts using an NID and 
smartphone. It ensures legal digital transactions (BFIU, 
2019). Bangladesh has digitized its land records, maps, 
and registrations to improve transparency and reduce 
corruption. This initiative helps modernize agricultural 
documentation (Issue-I, 2025). The Credit Information 
Bureau (CIB) database provides borrower history, 
including outstanding and closed loans. For loans below 
BDT 50,000, CIB reports are not mandatory (New Age, 
2024). Land certificates (Porcha), mutation documents, 
and rent receipts now include QR codes. These can be 
verified online to detect forgeries easily (bdnews24.
com, 2022b). Land ownership and mortgage data can 
be accessed through Bangladesh’s mortgage databank, 
Ministry of  Land portals, and GIS tools (bdnews24.com, 
2022a). MFS has become an essential part of  financial 
inclusion, especially in rural areas. As of  June 2024, 
21.82% rural and 18.75% urban populations had MFS 
accounts. Monthly transactions reached BDT 1.45 trillion 
in September 2024, showing a 33.85% increase from 2023. 
MFS bridges formal banking with informal economies, 
expanding financial access nationwide (Zaman, 2024). By 
January 2025, around 12,000 bank branches operated in 
Bangladesh, with only 5,700 in rural areas. Conventional 
systems remain manual and labor-intensive, though many 
support services are now digital. Challenges include 
poor internet connectivity and insufficient digitization 
(Bangladesh Bank, 2025b). However, based on the overall 
procedure the proposed system is app-based. Farmers 
will open an account using e-KY. Link MFS numbers for 
disbursement and repayment. Choose loan schemes and 
submit details. Upload collateral and required documents. 
Bank officers will verify submissions and communicate 
approval or rejection. Disbursement and recovery will 
be entirely via MFS, reducing processing time to under 
3 hours for farmers and 1 hour for bankers. This system 
aims to eliminate queues, delays, and dissatisfied clients.
Although other sectors in Bangladesh have undergone 
successful digital transformation, agricultural 
loan management remains manual. With available 
infrastructure, rules, and cloud technology, there’s a 
unique opportunity to develop a fully automated, cost-
effective, and lawful system. The paper highlights this void 
in automation as a key research gap that, if  addressed, can 
significantly enhance agricultural productivity and GDP.

Research Questions
Given the background, here are the key questions this 



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research aims to explore 
1. How does the mobile financial service (MFS) 

based automated loan management systems influence 
loan management costs compared to conventional loan 
management system management in agricultural loan 
management?

2. What is the effect of  mobile financial services (MFS) 
based automated loan management systems on the time 
taken for loan sanction and disbursement in agricultural 
loan management?

3. To what extent is the mobile financial service 
(MFS) based automated loan management system more 
convenient than the conventional loan management 
system in agricultural loan management?

Objectives
The several objectives of  this study are given below: 

1. To examine the impact of  mobile financial service 
(MFS) based automated loan management systems on 
loan management costs in agricultural loan management.

2. To assess the effect of  mobile financial service (MFS) 
based automated agricultural loan management systems 
on loan sanction and disbursement time compared to the 
conventional agricultural loan management system.

3. To evaluate the convenience of  mobile financial 
service (MFS) based automated loan management 
systems in agricultural loan management.

MATERIALS AND METHODS
To explore how Mobile Financial Services (MFS) can 
improve agricultural loan management in Bangladesh, 
this study employed a quantitative approach using a 
structured questionnaire survey of  111 professional 
including bankers, loan officers, and IT staff—from 
both public and private banks. Participants were selected 
through purposive sampling to ensure relevant experience 
in agricultural loan processing, and the sample size was 
justified based on accessibility and comparable studies 
suggesting 100+ respondents are adequate for Likert-scale 
analysis. The questionnaire, developed through literature 
review and expert input, focused on three key areas: cost, 
time, and convenience of  the loan process, with items 
rated on a 5-point Likert scale. A pilot test involving 

10 participants was conducted to refine question clarity 
and content validity. Data analysis was carried out using 
SPSS, employing descriptive statistics to identify trends, 
Cronbach’s Alpha to confirm internal reliability (0.77 for 
the conventional system, 0.79 for the automated system), 
and paired sample t-tests to examine significant differences 
between systems, alongside correlation analysis to explore 
inter-variable relationships. While the findings offer 
meaningful insights into the advantages of  digitization, 
the study recognizes limitations such as potential self-
reporting bias, selection bias due to purposive sampling, 
and limited generalizability, highlighting the need for 
future studies to incorporate randomized sampling and 
operational data for broader validation.

Align to the objectives following hypotheses were 
developed

H1: The automated agricultural loan management 
system using mobile financial services (MFS) significantly 
reduces the cost of  managing loans compared to the 
conventional system.

H2: The automated system significantly reduces the 
time needed to approve and disburse loans.

H3: The automated system is more convenient than the 
traditional method of  managing agricultural loans.
All three hypotheses were tested using statistical tools. 
The results showed strong evidence that switching to an 
automated, MFS-based system reduces costs saves time, 
and makes the whole process more convenient for both 
bankers and farmers.

RESULTS AND DISCUSSION 
Demographics analysis
This part of  the study highlights the main results and 
present the findings from the research, focusing on 
the demographic characteristics of  respondents and 
the operational effectiveness of  conventional versus 
automated agricultural loan management systems in 
agricultural loan management. The following discussion 
highlights key insights derived from the data and 
addresses the impact of  automation on efficiency, cost, 
and convenience in the sector.

Table 1: Age of Respondent
Age Frequency Percent Cumulative Percent
Below 25 years 2 1.80 1.80
26 to 35 years 43 38.70 40.50
36 to 45 years 55 49.50 90.10
46 to 55 years 11 9.90 100.00
Total 111 100.00

Table 1 indicates age distribution and shows that most 
respondents (49.50%) are aged 36 to 45 years, followed 
by 38.70% in the 26 to 35 years group. Only 9.90% fall in 
the 46 to 55 years range, and a minimal 1.80% are below 
25 years. This suggests a workforce primarily in mid-

career stages, with younger employees being significantly 
underrepresented. The cumulative percentage confirms 
that the majority (90.10%) are between 26 and 45 years 
(Table 1).



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Table 2: Gender of the Despondences
Gender Frequency Percent Cumulative Percent
Male 96 86.50 86.50
Female 15 13.50 100.00
Total 111 100.00

Table 3: Designation of Respondent
Official designation Frequency Percent Cumulative Percent
Assistant General Manager and above 27 24.30 24.30
Deputy General Manager 1 .90 25.20
Job seeker 1 .90 26.10
Loan Applicant (Borrower) 1 .90 27.00
Officer / Senior officer 31 27.90 55.00
Principal Officer 27 24.30 79.30
Senior Principal Officer 23 20.70 100.00
Total 111 100.00

Table 4: Banking Experience of Respondent
Duration of Experience Frequency Percent Cumulative Percent
Below 5 years 20 18.00 18.00
06 to 10 years 34 30.60 48.60
11 to 15 years 41 36.90 85.60
16 to 20 years 14 12.60 98.20
Above20 years 2 1.80 100.00
Total 111 100.00

Table 5: Respondent Experience in Agriculture Loan Management
Experience in Agriculture Loan Management Frequency Percent Cumulative Percent
Below 05 years 69 62.20 62.20
06 to 10 years 33 29.70 91.90
11 to 15 years 6 5.40 97.30
16 to 20 years 2 1.80 99.10
Above 20 years 1 .90 100.00
Total 111 100.00

Table 2 reveals the he genders distribution and indicates a 
significant male dominance, with 86.50% of  respondents 
being male and only 13.50% female. This suggests a 

gender imbalance in the surveyed population, potentially 
reflecting industry trends. The cumulative percentage 
shows that females make up a small fraction.

The table 3 illustrates designation distribution and reveals 
that the largest group comprises officers/senior officers 
(27.90%), followed closely by assistant general managers 
and principal Officers, both at 24.30%. Senior principal 
officers make up 20.70%, while deputy general managers, 

job seekers, and loan applicants each account for a 
minimal 0.90%. The data suggests a workforce primarily 
composed of  mid-to-senior-level professionals, with 
relatively fewer individuals at entry-level or job-seeking 
stages.

In the meantime, Table 4 shows that a majority of  
respondents (36.90%) have 11 to 15 years of  banking 
experience, with another 30.60% having worked in the 
sector for 6 to 10 years. 
A smaller portion (12.60%) has 16 to 20 years of  

experience, while only 1.80% have over 20 years. 
Notably, 18% have less than 5 years of  experience. This 
suggests a workforce primarily composed of  mid-career 
professionals, with fewer employees at senior levels.

On the other hand, Table 4 depicts the experience 
distribution in agriculture loan management shows that 
a majority (62.20%) have less than 5 years of  experience, 

followed by 29.70% with 6 to 10 years. Only 7.20% have 
more than 10 years of  experience, with just 0.90% having 
over 20 years. This indicates that most respondents are 



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relatively new in this field, with a limited number of  highly 
experienced professionals, suggesting a workforce in its 
early to mid- career stages. Agricultural loan management 

system isa very easy. More than 1 year experience is 
enough to provide excellent service for these types of  
loan.

Table 7: Reliability Statistics
Cronbach's Alpha Number of Items
0.791 3

Table 6 illustrates the key responsibilities in AGM are 
primarily held by dealing officers (33.30%) and sanctioning 
authorities (26.10%), indicating their significant roles in 
the process. Loan credit committee members account for 
18.00%, while recovery and legal officers make up 9.00%. 
A notable 9.00% marked “N/A,” possibly indicating 
indirect involvement. Who are not working in this sector. 
Other roles, such as IT security, ICTD, and cash handling, 
are minimal. This suggests that most respondents 
are actively engaged in loan approval and processing 
functions. Most of  the respondents are directly involved 

with loan sanctions and disbursement, so we find most 
realistic data.

Reliability analysis
Cronbach’s Alpha measures the reliability of  a scale. An 
alpha of  0.9 or higher is excellent, 0.8 to 0.9 is good, 0.7 
to 0.8 is acceptable, and 0.6 to 0.7 is questionable. Below 
0.6 indicates poor reliability. Generally, an alpha above 
0.7 is considered reliable for most research (Cheung et 
al., 2024).

Table 7 shows that Cronbach’s Alpha values for the 
conventional agricultural loan management system (0.77) 
and automated agricultural loan management system 
(0.79) indicate good internal consistency for both variables. 
Since both values are above 0.70, the measurement 
scales for these systems are considered reliable. The 
slightly higher alpha for the automated system suggests 
marginally better consistency in responses compared to 

the conventional system.

Hypothesis testing
The findings delineated in Table 8 elucidate whether the 
posited paths achieve statistical significance, adhering 
to a conventional significance threshold of  p < 0.05 
(Roohafza et al., 2016)

Table 6: Respondent Key Responsibility in Agricultural Loan Management
Key Responsibility Frequency Percent Cumulative Percent
Cash 1 .90 .90
Loan Committee Member 20 18.00 18.90
Dealing Officer 37 33.30 52.30
ICTD 1 .90 53.20
IT security 1 .90 54.10
N/A 10 9.00 63.10
Other 1 .90 64.00
Recovery Officer/Legal Officer 10 9.00 73.00
Sanctioning Authority 29 26.10 99.10
Supervising 1 0.90 100.0
Total 111 100.00

Table 7: Hypothesis Testing
Hypothesis Standard Deviation (SD) P Values Results
H1: The automated agricultural loan management 
system using mobile financial services (MFS) 
significantly reduces the cost of  managing loans 
compared to the conventional system.

0.080 0.038 Supported

H2: The automated system significantly reduces the 
time needed to approve and disburse loans.

0.126 0.024 Supported

H3: The automated system is more convenient than 
the traditional method of  managing agricultural loans.

0.090 0.002 Supported

H1 highlights that the automated system significantly cuts 
the cost of  managing loans, with SD = 0.080, p < 0.038, 
meaning the reduction in costs is statistically significant. 

H2 demonstrates that the automated system also speeds 
up the process of  loan approval and disbursement, with 
SD = 0.126, p < 0.024, proving a substantial decrease in 



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processing time. Finally, H3 confirms that the automated 
system is much more convenient than the old method, 
with SD = 0.090, p < 0.002, showing clear evidence of  its 
ease of  use. These findings highlight that the automated 
system significantly improves cost-efficiency, time 
management, and overall convenience for both farmers 
and banks (Table 8).

Proposed Automated Agricultural Loan Management 
Model
Convert conventional agricultural loan management 
system to automated agricultural loan management 
system we considered a lot thing. After analyze survey 
result and face to face interview we drown a model (flow 
diagram) of  automated agricultural loan management 
system. In this model, the loan applicant and the bankers 
are meet only when the charge documents will sign.

Figure 1: The Proposed Model

Previously loan applicant will compile his/her applications 
and banker are verified all documents through existing 
online. If  all documents are valid and loan applicant fully 
compliance the loans application conditions then bank 
will approved & sanction loan. Then bank will invite the 
loan applicant for sign charge documents and to submit 
required documents to bank. After charged documents 
signed and bank received required original documents 
from loan applicant, bank disburse loan through mobile 
financial service. Finally, bank will monitor & recovery 
the loan until the loan is liquated through mobile financial 
service (MFS). To complete all thing (From loan applicant 
registration to loan disburse) required not more than two 
hours (Figure 1).

Findings
Based on the results the findings are as follows

1. The majority of  respondents (49.50%) are aged 
between 36 to 45 years, followed by 38.70% in the 26 
to 35 years group. Only 9.90% are aged between 46 to 
55 years, and a minimal 1.80% are below 25 years. This 
indicates that the workforce is primarily composed of  
mid-career professionals.

2. A significant gender imbalance exists, with 86.50% 
of  respondents being male and only 13.50% female. This 

suggests a male-dominated workforce in agricultural loan 
management.

3. The largest group comprises officers/senior officers 
(27.90%), followed closely by assistant general managers 
and principal officers, each at 24.30%. This indicates 
that most respondents hold positions with significant 
involvement in loan processing.

4. Most respondents (36.90%) have between 11 to 15 
years of  banking experience, followed by 30.60% with 6 to 
10 years. This suggests that a majority of  the respondents 
have substantial experience in the banking sector.

5. The majority (62.20%) have less than 5 years of  
experience in agricultural loan management, with only a 
small portion (5.40%) having more than 10 years. This 
shows that many respondents are relatively new in this 
specific field

6. Most respondents are involved in loan processing 
and sanctioning. The largest group consists of  dealing 
officers (33.30%) and sanctioning authorities (26.10%), 
indicating that a significant portion of  the respondents is 
directly responsible for loan approval and disbursement.

7. It is also found that the help automation system 
decreases cost of  loan management (p < 0.038), shortens 
the lead time of  loan approval and disbursement (p < 
0.024) and improves users’ convenience (p < 0.002). Such 



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statistically significant findings imply beneficial gains in 
the cost-effectiveness, time-saving and user-friendliness 
of  the new model, which is advantageous for farmers as 
well as for the banks.

Recommendations 
Based on what the study found about using mobile 
financial services (MFS) to automate agricultural loan 
management in Bangladesh, here are some practical 
suggestions to make the system more effective and 
farmer-friendly: 

1. As the workforce mainly consists of  the professionals 
between 36 and 45 years old, such training programs may 
concentrate on the upgrading this group to become more 
efficient in agricultural loan management.

2. This striking gender imbalance emphasizes the 
importance of  policies and programs aimed at increasing 
the number of  women in agricultural finance.

3. As they already have a large number of  experienced 
bankers, the banks have to introduce mentor programs to 
enlighten the less experienced staff  members about the 
agricultural lending procedures.

4. Since the duration of  working experience is less than 
5 years for most of  the staff, special training and updating 
programs need to be implemented to enhance their level 
of  skill.

5. Since a substantial majority of  the respondents 
perform the actual work of  loan processing as well as 
sanctioning, clear operational instructions, accountability 
and performance rewards should be introduced to 
minimize both time and incorrect decision.

6. The demonstrated advantages of  automation in 
terms of  cost, time to approval, and user convenience, 
tell us that banks are to consider investing into or scaling 
up the use of  automated applications in agricultural credit 
processing.

7. Moreover, farmers, especially smallholder farmers, 
need easy to use digital tools for loan applications and 
tracking to increase adoption and satisfaction.

8. The tools of  automation and the capacity of  the 
workforce to deliver services and support policy must be 
continuously monitored to ensure these are improving 
over time.

Limitations
This study has a few limitations to keep in mind. With 111 
respondents, it might not capture the full picture especially 
for entry-level workers in agricultural loan management. 
Since the research focused on specific areas, its findings 
might not apply well where internet or mobile coverage 
is weak. Also, because the data came from self-reporting, 
there’s a chance of  some bias or inaccuracies. We do 
not yet know how well the automated system performs 
over the long term. Legal issues like data privacy weren’t 
fully explored, and the views of  important groups like 
policymakers or tech providers were missing. Still, despite 
these gaps, the study offers helpful insights into how 
automation could improve agricultural loan management.

CONCLUSION
This study shows that moving to a mobile financial service 
(MFS)-based system can make agricultural loans faster, 
cheaper, and easier for farmers in Bangladesh. Instead 
of  spending days traveling to banks and dealing with 
paperwork, farmers can now apply, receive, and repay 
loans right from their phones. It saves time, cuts costs, and 
makes the whole process more convenient for everyone 
involved. But to make this work for all farmers, especially 
in rural areas, there’s still work to do. Many farmers need 
better internet access and support to use digital tools 
confidently. Key documents like land records also need to 
be fully digital for the system to run smoothly. In short, 
automating agricultural loan management isn’t just a tech 
upgrade, it’s a step toward empowering farmers, boosting 
productivity, and building a stronger agricultural sector. 
With the right support and investment, this change can 
create lasting benefits for both rural communities and the 
broader economy.

REFERENCES
Abdullah, S. (2025). Click, wait, repeat: Digital land 

services struggle to deliver promised ease. The Business 
Standard. https://www.tbsnews.net/bangladesh/
infrastructure/click-wait-repeat-digital-land-services-
struggle-deliver-promised-ease

Ahmed, T. M. (2024). Agricultural Loans Bangladesh | 
What Bangladeshi banks offer to farmers. The Daily 
Star. https://www.thedailystar.net/supplements/
boosting-growth-agri-loans/news/what-bangladeshi-
banks-offer-farmers-3598651

Arifuzzaman, Md., & Islam, S. (2024). Digitalization 
of  Land Documents in Bangladesh: Challenges 
and Prospects. OALib, 11(10), 1–9. https://doi.
org/10.4236/oalib.1112101

Bangladesh Bank. (2024). Monthly Report on Agriculture 
and Rural Finance. https://www.bb.org.bd//pub/
monthly/agri_rural_financing/agri_mar24.pdf

Bangladesh Bank. (2025a). Agricultural & Rural Credit 
Policy and Program for the FY 2024-2025. Bangladesh 
Bank. https://www.bb.org.bd//pub/annual/acfid/
arcpp-29-08-2024.pdf

Bangladesh Bank. (2025b). Monthly Report on Agriculture 
and Rural Finance. https://www.bb.org.bd//pub/
monthly/agri_rural_financing/agri_may25.pdf

BBS. (2022). Statistical Yearbook Bangladesh 2022 (42nd 
Edition). Bangladesh Bureau of  Statistics. https://
bbs.portal.gov.bd/sites/default/files/files/bbs.
por ta l .gov.bd/page/b2db8758_8497_412c_
a9ec_6bb299f8b3ab/2023-06-26-09-19-2edf60824b0
0a7114d8a51ef5d8ddbce.pdf

BBS. (2023). Quarterly Report on Crop Statistics and Agricultural 
Labour Wage. Bangladesh Bureau of  Statistics. https://
bbs.portal.gov.bd/sites/default/files/files/bbs.
portal.gov.bd/page/16d38ef2_2163_4252_a28b_
e65f60dab8a9/2024-04-04-05-48-d00d98986368326
b82adfc782251e2e7.pdf

BBS. (2025). Quarterly Report on Crop Statistics and Agricultural 



Pa
ge

 
14

2

https://journals.e-palli.com/home/index.php/ajfti

Am. J. Financ. Technol. Innov. 3(1) 135-142, 2025

Labour Wage. Bangladesh Bureau of  Statistics. https://
bbs.portal.gov.bd/sites/default/files/files/bbs.
portal.gov.bd/page/16d38ef2_2163_4252_a28b_
e65f60dab8a9/2025-07-03-07-48-1197600a834a8bab
85efbee7c25a145a.pdf

bdnews24.com. (2022a). Bangladesh’s mortgage data 
bank begins journey with info on 22,200 properties. 
Bangladesh’s Mortgage Data Bank Begins Journey with 
Info on 22,200 Properties. https://bdnews24.com/
bangladesh/kmt6yifwcz

bdnews24.com. (2022b). QR codes on land records to make 
manual signatures redundant. QR Codes on Land Records 
to Make Manual Signatures Redundant. https://
bdnews24.com/bangladesh/9zuiauttli

BFIU. (2019). Guidelines on Electronic Know Your Customer 
(e-KYC). Bangladesh Financial Intelligence Unit 
(BFIU). https://www.bb.org.bd/mediaroom/
circulars/aml/jan082020bfiu25.pdf

Cheung, G. W., Cooper-Thomas, H. D., Lau, R. 
S., & Wang, L. C. (2024). Reporting reliability, 
convergent and discriminant validity with structural 
equation modeling: A review and best-practice 
recommendations. Asia Pacific Journal of  Management, 
41(2), 745–783. https://doi.org/10.1007/s10490-
023-09871-y

Economy. (2015). Banks get access to national ID 
database. The Daily Star. https://www.thedailystar.
net/business/ banking/ banks -get -access- national 
-id-database-129385

Issue-I, S. A. (2025). Introducing e-KYC. The Financial 
Express. https://thefinancialexpress.com.bd/views/
views/introducing -e-kyc-1568388135

Labor Force Survey. (2023). Qarterly Labour Force Survey 
2023. Bangadesh Bureau of  Statistics. https://bbs.
portal.gov.bd/sites/default/files/files/bbs.portal.
gov.bd/page/96220c5a_5763_4628_9494_950862ac
cd8c/2024-01-25-10-03-aad49f9f12bf7ab7c2090397
2607f7a3.pdf?utm_source=chatgpt.com

New Age. (2024). Studies find cancer-causing elements in 
fruits, vegetables. New Age. https://www.newagebd.
net/post/country/245984/studies-reveal-high-

levels-of-metals-pesticide-in-fruits-vegetables
NirvikBD. (2025, April 12). How To Get Agriculture Loan 

In Bangladesh. https://nirvikbd.com/how-to-get-
agriculture-loan-in-bangladesh/

Prodhan, Md. M. H., Ebn Jalal, M. J., Alam, H., Mostofa, 
Md. S., Khondker, B. H., & Khan, Md. A. (2024). 
State and potential of  digital financial services among 
farmers in Bangladesh: An in-depth study. Journal of  
Agriculture and Food Research, 16, 101209. https://doi.
org/10.1016/j.jafr.2024.101209

Roohafza, H., Feizi, A., Afshar, H., Mazaheri, M., 
Behnamfar, O., Hassanzadeh-Keshteli, A., & Adibi, 
P. (2016). Path analysis of  relationship among 
personality, perceived stress, coping, social support, 
and psychological outcomes. World Journal of  Psychiatry, 
6(2), 248. https://doi.org/10.5498/wjp.v6.i2.248

Thakur, Z. K. (2024). Connecting farmers to finance. 
The Daily Star. https://www.thedailystar.net/
supplements/boosting-growth-agri-loans/news/
connecting-farmers-finance-3598666

UN. (2024). Food security and nutrition and sustainable 
agriculture. United Nations. https://sdgs.un.org/
topics/food-security-and-nutrition-and-sustainable-
agriculture

World Bank. (2017). Mobile technologies and digitized 
data to promote access to finance for women in agriculture 
[Text/HTML]. World Bank. https://documents.
worldbank.org/en/publication/documents-reports/
documentdetail/en/855471513670397514

Yesmin, S., Paul, T. A., & Mohshin Uddin, Md. (2019). 
bKash: Revolutionizing Mobile Financial Services 
in Bangladesh? In Business and Management Practices in 
South Asia (pp. 125–148). Springer Singapore. https://
doi.org/10.1007/978-981-13-1399-8_6

Zaman, M. A. (2024). How mobile money is reshaping 
financial inclusion in Bangladesh. The Daily Star. 
https://www.thedai lystar.net/supplements/
mfs-and-financial-inclusion-bangladesh/news/
how-mobile-money-reshaping-financial-inclusion-
bangladesh-3529986


