Received: 07 January 2026; Revised: 07 March 2026; Accepted: 17 March 2026; Published Online: 18 March 2026.
J. Collect. Sci. Sustain., 2026, 2(1), 26401 | Volume 1 Issue 3 (December 2025) | DOI: https://doi.org/10.64189/css.26401
© The Author(s) 2026
This article is licensed under Creative Commons Attribution NonCommercial 4.0 International (CC-BY-NC 4.0)
Perceived Security and User Satisfaction in UPI 3.0-based
Payment Systems
Pankajkumar Anawade*
and Deepak S. Sharma
Faculty of Commerce and Management Sciences of Datta Meghe Institute of Higher Education and Research, Wardha, Maharashtra,
442107, India
*Email: pankaj.anawade@dmiher.edu.in (P. Anawade)
Abstract
With UPI 3.0 promising new security features and the launch of user-centric fully automatic wallets, the system is set
to take an already transformed digital payment landscape in India up yet another notch. This study explores the co-
relation between perceived security and user satisfaction based on UPI 3.0 based payment systems along with Indian
users. This was a descriptive research design with a sample of 450 respondents from all major cities of India. The
security of UPI 3.0 having higher impact on user satisfaction and adoption. A descriptive cross-sectional study was
conducted where the structured questionnaires were used to collect data and analyze by using statistical techniques
such as chi-square, ANOVA, and regression analysis. Results show that 91.5% of users are satisfied with UPI services
and security perception is the strongest factor influencing continued usage behaviour. The adoption of biometric
authentication cut acute security incidents and breaches by 58% in 2025, while the deployment of AI-powered fraud
detection tools reduced the number of fraudulent attacks by 47%. Results shows that perceived security, ease of use
and trust explains as a total 78% variance in user satisfaction. The study finds that UPI 3.0 advanced security
architecture has successfully encouraged user confidence that is establishing India as a leading innovator in digital
payments, surpassing with 491 million Users and 640 million transactions every day.
Keywords: UPI 3.0, Perceived security, User satisfaction, Digital payments, Payment systems.
1. Introduction
The Unified Payments Interface (UPI) is regarded as the most significant fin-tech innovation in India-driven by the
National Payments Corporation of India launched in April, 2016.
[1,2]
UPI 1.0 to UPI 3.0 migration marks the beginning
of a whole new implementation of how Indians make transactions, with the UPI platform processing ₹223 lakh crore
worth over 185.8 billion transactions per annum as of FY 2025.
[3]
Such unique growth pattern made India the leading
country in performing real-time payment transactions, with almost 49% share of the total numbers of real-time
payment transactions happening globally.
[4]
UPI 3.0 launched in 2024 is the major technological leap from previous
versions integrating conversational voice payments, blockchain-enabled settlements, new advanced biometric
authentication technology and AI-based fraud detection systems. By including these features, it solves important
problem which have been barriers to the adoption of digital payment in the past such as security, privacy and user
experience.
[5]
Such an impression by virtue of its performance can be drawn from UPI that now has 491 million active
users and around 640 million transactions per day, disrupting the cash transaction economy of India.
[6]
You cannot
underestimate the importance of perceived security in digital payment systems. Previous studies have shown that trust
and perceived security are critical factors in the technology acceptance of financial services.
[7]
Nevertheless, the
continuous improvement of UPI technology especially the recent advancements in UPI 3.0 towards additional security
warrants a renewed examination of how these advancements may impact user satisfaction and adoption behavior. This
study fills this gap in research by studying the differential effects of perceived security features of UPI 3.0 on user
satisfaction across demographic segments in India.
This transformation in this landscape is unprecedented with Government of India initiatvies like demonetization and
COVID-19 impact activated the ongoing shift with push for contactless payment systems.
[8]
In the period from February
2022 to an estimate for August 2025, daily UPI transactions exploded from 240 million to 645 million, a growth of
169%. Indicative of comfort with the system security architecture too, this high rate of adoption is a case of not just
convenience that UPI offers. The study comes when UPI is gaining international acceptance in 27 countries and
agreements are being discussed with 30 more.
[9]
Similar insights not only help develop strategies for international
expansion, but also make sense of the local market and the factors driving user satisfaction and perception of security
the domestic market of India. Moreover, while UPI is already now handling 790 million transactions a day on average
and evolving towards 1 billion daily transactions by FY 2027, the insights can help with sustaining long-term growth
of UPI and remain the default payment mode against emerging payment alternatives like state-level (via blockchain
based) CPA payment systems.
2. Literature review
Previous literature surrounding digital payment systems have developed considerably over the last ten years but largely
from the theoretical lenses of technology acceptance models and trust related constructs. Davis's Technology
Acceptance Model established that perceived usefulness and perceived ease of use are two key dimensions that
determine whether or not technology will be adopted, a model used widely in research on digital payments.
[10]
Alongside this base, financial technology-specific variables such as perceived security, trust, and risk perception have
been subsequently integrated into more advanced studies.
[1]
Unified Payments Interface and Payment Apps in India: A
Security Analysis of UPI Payment Using Android Apps Abstract: Payment This dependent on Early implementations
Internet Protocol provides a set of The Unified payments interface transfer. Information and communication (UPI)
enabling security, while summarizing authentication Such excellent acknowledgement of detail mechanism. In their
work presented at the 29th USENIX Security Symposium, these researchers describe how UPI offers a strong
foundation for security through a two-factor authentication mechanism based on the combination of device binding
with UPI PIN verification but note that user education is necessary to defend against social engineering attacks. This
paper set the groundwork for understanding UPI security by establishing a baseline that UPI 3.0 improvements can
be measured against.
Shree et al.
[4]
extended the study of digital payments and consumer experience within the Indian context by conducting
a survey-based empirical study and revealed the strong evidence regarding perception and trust in digital payments
playing a pivotal role in consumer digital payment behavior. 91.5%, and 95.2% of users who gave feedback in the
survey stated that they are satisfied with UPI and are comfortable with the payment process through UPI, respectively.
Notably, the research found that about 75% of the respondents said they spent more because of UPI and top-of-the-
mind positive user experience and perceived security showed correlation with payment frequency and ticket size as
well. Extensive documentation exists on the role of trust in digital payment adoption, especially in developing
markets. Singh et al.
[7]
was the first to study the factors that drive consumers adoption and recommendations of mobile
wallet services in India, by investigating the influence of innovativeness, stress to use and social influence. The results
showed that, ease of use, useful, perceived risk and attitude have a significant effect on user intention which in turn
affects user satisfaction and recommendation to use the mobile wallet services. Using a modified Technology
Acceptance Model integrated with UTAUT2, the research found that the moderating elements of stress and social
impact significantly determine user satisfaction.
During this period, Sivathanu
[5]
conducted a pioneering empirical study based on the adoption of digital payment
systems in the demonetization period in India using UTAUT2 and innovation resistance theory framework. According
to responses from 766 participants, usage of digital payment systems is significantly affected by behavioral intention
and innovation resistance, while stickiness to cash payments moderates the relationship. The results from this study
thus offered the first insights into the impact of digital payment adoption induced by policy efforts on users and added
to the existing knowledge gaps regarding the importance of behavioral inclination towards technology acceptance.
Previous studies on user satisfaction in digital payment systems have widely reported the multidimensional nature of
the underlying satisfaction constructs. Chaudhari and Chaudhari
[11]
focused on consumer satisfaction on UPI in
Hyderabad and suburbs and their study identified that customers have positive behaviour towards UPI but education
level has significant correlation with usage pattern. They postulate that the higher the educational status, the more the
adoption rate and satisfaction, which underlines the need for implementing digital literacy initiatives.
So when payment experiences involve new with advanced and high-end security features, adoption rates have seen a
significant impact. Venkatesh et al.
[10]
Facilitating conditions, which include security infrastructure, are widely
recognized in the unified theory of acceptance and use of technology (UTAUT). More recently, this framework has
been adapted to include digital payment specific cyber security risks. This was quite pronounced in contexts of high
fraud incidence rates or limited prior experience of users with digital financial services, with the perceived security
playing a major role in the trust formation process. Interesting patterns have emerged from studies of
demographically-diverse groups UPI adoptions. To get an insight into the research of the evolution of mobile banking
in the UPI era, Balasubramanian and Amanullah
[12]
focused on the use of UPI for fund transfers and research revealed
that UPI is optimal for low-value fund transfers but conventional modes are prospective for high-value transactions.
The combination of user interface design and promotional strategy of these platforms has made Google Pay one of the
most significant contributors to the latest payment methods, according to a research paper by IIT Bombay, indicating
that the growth of platforms such as Paytm and PhonePe overshadowed the government-owned BHIM app.
Multiple studies have identified the role of social influence in the adoption of payment technology. Siva Kumar and
Kavya
[13]
investigated the impact of UPI mode of payment on digital banking services through an empirical study on
user perception and also concluded that peer recommendations and social norms play an important role in the adoption
decision of UPI. This finding is consistent with a larger literature on technology adoption indicating that network
effects and social proof are a critical component of financial technology acceptance, particularly within collectivist
cultures such as India. Recently, the link between the strength of perceived security and actual usage behaviour has
also been better understood. Arora
[8]
suggests that, although users might claim to appreciate security tools, their use
behavior might hint that they still fear of fraud, data privacy issues or reversibility of transaction. This gap between
stated preferences and revealed behavior provides a narrative on the limitations of notion satisfaction measurement in
the context of digital payments (DP) and the necessity of a comprehensive user experience research framework that
goes beyond the cognitive dimension and encompasses some behavioral aspects.
3. Objectives
The present study aims to achieve the following objectives:
1. To assess the level of awareness and adoption of UPI 3.0 security features among Indian users across different
demographic segments.
2. To examine the relationship between perceived security measures in UPI 3.0 and overall user satisfaction with the
payment system.
3. To identify the key security factors that influence users' continued usage intention and recommendation behavior
for UPI-based payment systems.
4. To evaluate the impact of UPI 3.0's enhanced features including biometric authentication, AI-powered fraud
detection, and blockchain integration on user trust and satisfaction levels.
4. Methodology
The study used a descriptive design to examine perceived security and user satisfaction in UPI 3.0 enabled payment
systems. This method was chosen as a way to methodologically report on the characteristic, behavior, and perception
of UPI users concerning security features and satisfaction. A sample of 450 respondents was chosen from the major
cities towns situated across India (Delhi NCR, Mumbai, Bangalore, Hyderabad, Chennai and Kolkata). The sample
was participants that were active users of UPI with minimum 10 transactions in three months. Representativeness
across ages (18–60 years), income groups, levels of education, and occupational divisions was provided in the sample
set by a stratified random sampling method used. The sample was made up of 58% men and 42% women and the
majority, or 65%, were between the ages of 25-40, those that make up the main user base for digital payments. The
structured questionnaire was adapted for online and physical administration for data collection. The questionnaire was
divided into four sections i.e. (i) demographic profile, (ii) UPI usage patterns and use of UPI 3.0 features (iii) recording
of perceived security measures on a five point Likert scale, and (iv) user satisfaction survey. The instrument was pre-
tested by 50 subjects and further adjusted according to reliability analysis (Croanbach's alpha =.87), which confirmed
the internal consistency.
The fieldwork for the primary data was conducted over a 4‐month period from September to December 2024. Data
were collected online through Google form using the social media and email for (online) whereas (off line) personal
interviews were conducted at shopping mail, educational institutions, corporates etc. Data collection and secondary
source: Secondary data were collected from NPCI reports, RBI publications, academic journals and private industry
reports to supplement the analysis and put the findings in perspective. Statistical analysis was conducted with the help
of SPSS 26.0 and AMOS 24.0 software. Demographic characteristics of the users and usage data were summarized
using descriptive statistics, including frequencies, percentages, means and standard deviations. The relationship
between categorical variables was analyzed using Chi-square test. The variance analysis between multiple groups
was tested by one-way ANOVA. Predictors of user satisfaction were also determined by means of multiple regression
analysis. Hypotheses were tested using structural equation modeling looking at the associations between perceived
security, trust, and satisfaction constructs.
5. Results
The demographic distribution of respondents is shown in Table 1. The sample is accordingly slightly male dominant
(58%), consistent with national digital payment usages reported by Shree et al.
[4]
Age distribution shows 64.9
percentage of respondents fall within the age gap 26-45 (the workforce population that drive digital payment uptake).
Academic status indicates a highly educated sample 50% have post-graduate qualification which correlates with
greater digital literacy and propensity of technology adoption (Table 1).
[4]
Monthly distribution of income shows having
a vast majority of the sample coming from middle and upper-middle income segments, reporting up to 80% earning
more than ₹30,000 which reflects that the respondent profile for urban India's active digital payment users is drawn
predominantly from higher socioeconomic strata.
Table 1: Demographic profile of respondents.
Demographic Variable
Category
Frequency (n)
Percentage
(%)
Gender
Male
261
58.0
Female
189
42.0
Age Group
18-25 years
108
24.0
26-35 years
184
40.9
36-45 years
108
24.0
46-60 years
50
11.1
Education
Graduate
162
36.0
Post-Graduate
225
50.0
Professional
63
14.0
Monthly Income
Below ₹30,000
90
20.0
₹30,000-₹60,000
198
44.0
Above ₹60,000
162
36.0
Table 2: UPI 3.0 feature awareness and adoption.
UPI 3.0 Feature
Aware
(n)
Aware
(%)
Adopted
(%)
Not Adopted (n)
Not Adopted (%)
Biometric
Authentication
387
86.0
68.0
144
32.0
Voice-based
Payments
315
70.0
35.1
292
64.9
Geo-fencing
Security
279
62.0
36.0
288
64.0
AI Fraud
Detection
342
76.0
58.0
189
42.0
Blockchain
Settlement
189
42.0
16.0
378
84.0
Dynamic QR
Codes
405
90.0
79.1
94
20.9
Table 2 demonstrates the awareness and adoption of UPI 3.0 features in the sample. Among the different types of QR
codes, typical to merchant payment usages studied by Kumar et al, dynamic QR codes exhibit highest awareness
(90%) and adoption (79.1%). (2020). Biometric authentication is high on the agenda (with 86% awareness and 68%
adoption), to demonstrate that people are willing to embrace more secure environments that see transaction fraud drop
by 58%, according to industry stats. Voice payment, although well-known (70%), has a relatively low rate of
penetration (35.1%) due to easy preference for traditional input means or non-accuracy in multilingual environment.
A lower level of awareness (42%) and use (16%) of blockchain settlement functionality indicates poor user
understanding of backend technological infrastructure that camouflages the sharp upgrade in transaction processing
speeds that these features achieve. In the results, I find relationship among feature visibility, perceived usefulness and
adoption rates, which confirms finding of Sivathanu
[5]
on the key importance of user education in acceptance of
technology.
Table 3: Perceived security measures rating.
Security Measure
Mean Score
(out of 5)
Standard
Deviation
High Rating
(%)
Neutral
(%)
Low Rating
(%)
Two-factor Authentication
4.32
0.78
82.4
14.2
3.4
PIN Security
4.18
0.85
76.9
19.1
4.0
Device Binding
4.05
0.91
72.0
23.1
4.9
Transaction Verification
4.28
0.81
80.2
16.4
3.4
Data Encryption
3.98
0.96
68.4
26.2
5.4
Fraud Monitoring
4.15
0.88
75.3
20.4
4.3
Table 3 shows the respondents' levels of agreement on different types of security employed in UPI 3.0 systems.
Double-factor authentication had the highest mean rating (4.32), 82.4% of respondents rated it high, users have
consistent trust on multilayer security technique which Kumar et al.
[1]
stressed in their security analysis. The transaction
verification features are rated with 4.28, indicating a personal preference toward real-time confirmation possibilities
which would contribute immediate feedback of the payment status. 43, because it falls in the same direction to that of
PIN security level, endorses that there is an existing confidence of user on pin-based access control mechanism despite
the advent of biometric alternatives. Device binding got a score of 4.05, indicating moderate trust on the security
check that binds up UPI accounts with specific mobile devices. Data encryption scores the minimum mean (3.98),
indicating likely user apprehensions regarding data confidentiality and storage security, which is also in line with the
result of Shree et al.
[4]
on privacy issues in the adoption of digital payments. The low standard deviations in all the
measures show agreement among respondents on security perception, thus confirming that users feel significantly
influenced by security characteristics.
Table 4: User satisfaction levels with UPI services.
Satisfaction
Parameter
Very Satisfied
(%)
Satisfied (%)
Neutral (%)
Dissatisfied (%)
Very Dissatisfied
(%)
Mean
Score
Transaction Speed
45.3
42.2
8.9
2.7
0.9
4.28
Ease of Use
48.9
40.0
8.0
2.2
0.9
4.34
Security Features
38.7
47.6
10.2
2.7
0.8
4.21
Transaction
Success Rate
41.3
45.3
9.8
2.9
0.7
4.24
Problem
Resolution
32.4
46.2
16.4
4.0
1.0
4.05
Overall
Satisfaction
42.2
49.3
6.7
1.3
0.5
4.32
Table 4 User satisfaction across UPI service parameters. The general satisfaction which 91.5% (comprising satisfied
and Very Satisfied) are with our finding almost similar by Shree et al.
[4]
, who observed a similar rate of satisfaction.
User-friendliness had the highest mean score (4.34) and 88.9% were satisfied, corroborating Singh et al 's (2020)
notion that perceived ease of use directly affects usage interest and satisfaction. Transaction speed (mean 4.28) and
success rate (mean 4.24) have been rated high, highlighting the UPI 3.0’s technology upgrade in processing
efficiency.” Regarding security, users were asked to score this feature out of 5; it achieved a mean value of 4.21 with
a percentage satisfaction factor of 86.3%, which means that improved security levels met the users needs without
increasing inconvenience. One of the dimensions that scored least was problem solving (mean=4.05), indicating areas
for adjustment in services to public and grievance redressal systems. The high combined satisfaction confirm the
study’s hypothesis that perceived security affects positively to the user’s satisfaction, with low dissatisfaction values
(1.8 % for combined dissatisfied and very dissatisfied) suggest effective implementation of feature in UPI 3.0 Features.
Table 5: Impact of security features on continued usage intention.
Security Feature
High
Impact (%)
Moderate
Impact (%)
Low Impact
(%)
Chi-Square
Value
Significance
(p)
Biometric
Authentication
68.4
26.7
4.9
187.32
0.000*
Real-time Fraud Alerts
72.0
23.6
4.4
201.45
0.000*
Transaction Limits
54.7
36.4
8.9
128.67
0.000*
Encryption Technology
58.2
34.2
7.6
143.89
0.000*
Customer Support
51.6
40.0
8.4
118.23
0.000*
Regulatory Compliance
48.4
42.7
8.9
105.78
0.000*
*Significant at p<0.001
The relationship between security features and UPI Continued Usage Intention is analyzed for the determinants
depicted in Table 5, all relationships are statistically significant (p<0.001). Real-time fraud alerts showed the greatest
effect (72.0%), highlighting the need for proactive anticipatory security that provides immediate notifications for
suspicious activities regarding fraud prevention mechanisms.
[1]
Again, biometric authentication had a high impact
among 68.4% of the respondents, which is indicative of a user sentiment towards appreciation between convenience
and security with respect to the UPI 3.0 features. Moderate-to-High Impact Encryption technology (58.2%) and
transaction limits (54.7%) have the same moderate-to-high impact, as users appreciate these features but are not quite
aware of the technical mechanisms and details behind them. Customer support (51.6%) and regulatory compliance
(48.4%) have a lower but still significant impact, so it can then be said that users consider institutional trust factors as
well as technical security measures. Chi-square analysis shows that there is a highly significant association of perceived
security features with continued usage intention therefore, using the model by Sivathanu
[5]
which states that behavioral
intention has a significant impact on actual usage. The above findings validate the assumption that improved security
features associated with UPI 3.0 are positively related to user retention and platform loyalty.
Table 6: Regression analysis - predictors of user satisfaction.
Independent
Variable
Beta
Coefficient
Standard
Error
t-
value
Significance
(p)
R²
Perceived Security
0.352
0.041
8.585
0.000*
0.782
Ease of Use
0.298
0.038
7.842
0.000*
Trust
0.264
0.044
6.000
0.000*
Transaction Speed
0.189
0.036
5.250
0.000*
Social Influence
0.156
0.033
4.727
0.000*
Perceived Risk
-0.143
0.039
-3.667
0.000*
*Significant at p<0.001; Adjusted R² = 0.775; F-statistic = 142.67 (p<0.001)
Table 6 presents the results of multiple regression analysis of predictors for user satisfaction in UPI 3.0 systems. The
model accounts for 78.2% of the variance in user satisfaction (R²=0.782, Adjusted R²=0.775), which is a high
explanatory power as found in technology acceptance literature.
[10]
Perceived security is ¼toº one of the most solid
predictors (β=0.352, p < 0.001), and supports to a large extent the H1of the study as well as Singh et al.
[7]
security’s
dominance in the adoption of digital payment according to Shree et al.
[4]
Easy to use (β=0.298) is placed second,
indicating that security improvements cannot come at the cost of ease-of-use, a design consideration of paramount
importance in UPI 3.0 building process. Significant positive effect of Trust (β=0.264) has been found, which supports
Shree et al.
[4]
claim of trust serving as mediating factor for the influence of system characteristics on user satisfaction.
Transaction speed (β=0.189) and social influence (β=0.156) have moderate positive impact, suggesting that
performance and peers’ opinions contribute to satisfaction. Perceived risk is found to have a significant negative effect
(β= -0.143), meaning that the fraud concern reduces satisfaction in the case when security of filling resides is assured.
The F-statistic (142.67, p<0.001) demonstrates the overall significance of the model and suggests strong evidence that
UPI 3.0's multi-dimensional approach to security usability leads into user satisfaction.
6. Discussion
Overall, the results of this study offer strong empirical support for perceived security as a critical determinant of user
satisfaction in UPI 3.0 payment systems and have direct implications for the design and development of digital
payment ecosystem in India, and beyond. The demographic composition suggests that adoption of UPI is limited to
educated, economically active urban people similar to the evidence by Sivathanu
[5]
during demonetization.
Nevertheless, it is worth emphasizing that the growing saturation among older respondents and, mainly, in a 26-45
pool of participants (where over 64.9% of all cases are included) means that UPI has managed to overcome early
adopter groups and achieve some level of mainstream adoption. Interesting differences are observed in the awareness
and usage of UPI 3.0 features, reflecting how feature discoverability does not match usage behavior. Dynamic QR
codes demonstrated 90.0 and 79.1% awareness and adoption rate, respectively due to their usefulness when making
daily transactions as well as when merchants agree to accept them, convinced by industry figures citing that 96% of
merchants have accepted it. By comparison, there is lower awareness (42%) and adoption (16%) of blockchain
settlement features, indicating that while back-end technology improvements are vital to the performance of a system,
they stay out of sight from end users. This indicates that the user-centric communication strategy which focuses on
physical value propositions rather than technological features as prescribed by Singh et al.
[7]
in their research on mobile
wallet adoption.
There are far fewer such surveys, but the one that’s out there right now suggests 68% of folks use biometric
authentication and they’ve done so at a rate much faster than card-based authentication over the past few years. At
this point, not using your fingerprint or iris or face to authenticate yourself feels backwards. Industry figures pointing
to a 58% decline in security infractions after biometric technology is deployed also reinforces this user confidence.
On the other hand, voice payments are less adopted (35.1%) though well-known at 70%, as underpinned issues may
include accent identification, language variety or privacy for example during public transactions. This discovery lays
the ground for UPI platform providers to improve voice-based recognition algorithms in India’s multi-lingual milieu
and educate users about privacy protection. The analysis of the security scores could be seen as key to understanding
user attitudes with regards to several layers of security. The high score on TFA and TV (like 4.32 for TFA and 4.28 for
TV) shows that users need suspicious security approaches with more than one layer of verification, similar to Kumar
et al.
[1]
security analysis findings. Data encryption has received a below-average score (3.98) compared to its
significance from technical perspective, resonating with the gap between backend security infrastructure and users
perception of them. This lack of clarity between standards on confidentiality and data integrity is in the significance
emphasizing the importance of clear communication on encryption norms and control measures, especially against
the backdrop of growing concerns about privacy within digital environments.
With user satisfaction levels of 91% and more, the figures certify that UPI 3.0 has struck a good balance between
security measures and user convenience." The high satisfaction with ease of use (mean 4.34) indicates that the
advanced safety requirement features in UPI have not made it difficult to engage in monetary transactions, which is
one of the major concerns when building secure systems. Transaction speed and success rate satisfaction (4.28, 4.24)
are tied to infrastructure enhancements such as blockchain integration and AI-based routing optimization.
Nevertheless, the lowest score of 4.05 for problem resolution underlines failures in customer service frameworks,
which indicates that as volumes grow towards a billion transactions daily by FY2027, grievance redressal mechanisms
should scale accordingly. The multiple regression reveals compelling evidence that perceived security is the most
significant determinant user satisfaction (β=0.352), accounting for more variance than any other variable. This has
important implications for the development of digital payment platforms in that it indicates that investments made into
systems security also result in direct benefits to user satisfaction and retention. The negative estimated coefficient (β=-
0.143) for perceived risk suggests that despite the tight security measures in place, some remain concerned about fraud
and financial loss which undermines satisfaction; a finding that contributes to the case presented by Shree et al.
[4]
were
written that highlight the value of holistic strategies to mitigate risks.
The high level of explanatory power (R²=0.782) of the model indicates that the chosen constructs account for a large
majority of those determinants playing a role in UPI satisfaction. The strong positive influence of social influence (β
= 0.156) confirms the power of network effects and peer endorsements in digital payment adoption, consistent with
diffusion of innovation theory. This result implies that satisfied users lead to natural growth in subscription through
word-of-mouth effects, which forms a virtuous cycle of penetration and satisfaction. The implications of the study
are Policy makers, National Payments Corporation of India and Regulatory bodies. The proven priority of security in
fuelling satisfaction validates ongoing investment in AI-based fraud detection, biometric authentication and
blockchain solutions. However, the awareness-adoption gap observed in some features may call for focused digital
literacy campaigns, especially for blockchain and encryption technologies due to its technical complexity.
When UPI goes international to 27 countries, it has to understand that security is a matter of perception and the
perception quotient would vary in different cultural and regulatory backgrounds. The Indian model’s apparent success
in providing high levels of satisfaction via multi-layered security may not be directly translatable to markets with
different fraud profiles or trust dynamics. Adaptation Tactics Adaptation strategies should account for local security
issues, but hold onto fundamental architectural ideas that have led to UPI’s domestic success. The growth is expected
here with the FY 2027 forecast of daily transactions touching close to 1 billion and will seriously test UPI 3.0’s security
and satisfaction frameworks as never before. AI-driven fraud detection systems that helped slash identification-based
fraud by 47% in 2025 will need to evolve and tackle new threat vectors such as deepfake authentication attempts,
advanced social engineering attacks, etc. The results of the study indicate that users are responsive to security
innovations, yielding stronger protection without sacrificing convenience, and thereby mandate for more
technological advancement.
7. Conclusion
The findings of this study confirm that UPI 3.0 has improved the user satisfaction by introducing new security
functionalities, and perceived security is the most important factor influencing satisfaction. The findings of the study
validate that with its focus on innovation in digital payments, coupled with strong security architecture and easy-to-
use applications, India has developed UPI as a benchmark by which real-time payment systems in other countries can
be compared. We believe the UPI has shown how technology can be an effective enabler of financial inclusion without
compromising on trust and security, with more than 491 million active users transacting over 640 million transactions
per day. High satisfaction (91.5%) and high usage of some new security features such as biometric authentication
(68%), dynamic QR code(79.1%) are the reflections of its adoption by users, suggesting that they have been using
UPI 3.0’s augmentations. The results of the regression analysis on perceived security, ease of use and trust which
explain 78% variance satisfaction are actionable for designers of payment systems all over the world. With UPI now
scaling internationally and focus on moving to 1 billion daily, the balance between security and usability will be a key
factor towards continued success and user trust in the digital payment revolution in India.
CRediT Author Contribution Statement
Pankajkumar Anawade: Conceptualization, Methodology, Supervision, Validation, Formal analysis, Writing –
review & editing, Project administration. Deepak S. Sharma: Data curation, Investigation, Software, Formal analysis,
Visualization, Writing - Original draft, Writing - Review & editing.
Funding Declaration
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit
sectors.
Data Availability Statement
The data that support the findings of this study are based on primary survey responses collected from 450 participants.
The dataset is not publicly available due to privacy and ethical considerations; however, anonymized data can be
shared by the corresponding author upon reasonable request.
Conflict of Interest
There is no conflict of interest.
Artificial Intelligence (AI) Use Disclosure
The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing
or editing of the manuscript and no images were manipulated using AI.
Supporting Information
Not applicable.
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