A Systematic Literature Review on Biometric Authentication in Mobile Banking

1.1 Motivation

The rapid increase in mobile banking has exposed financial facilities to well advanced cyber risks, and at the same time, it made the processes rather convenient. Password-based techniques of authentication are exposed to several attacks such as phishing attacks, brute-force attacks, and face issues in areas of memorability and limits of mobile operating environment. Therefore, an incentive to approach biometric solutions that will provide higher security levels and user experience is present in the sphere of mobile banking.

By searching previous studies for the period (2020-2025), we did not find a systematic literature review that focused specifically on the uses of BBA in mobile banking. There are some studies that focused on multi-factor authentication, while others focus on the use of all authentication methods in general and their uses in online banking. Therefore, in this research, we focused on studies that examined the use of biometric authentication in mobile banking.

So, the main contributions of this study are summarized as follows:

1.2 Intended audience

The present manuscript is aimed at a wide audience of both academic researchers and industry practitioners. To the academic community, the research can help in offering a synthesis of the state of the art biometric authentication methods in mobile banking to serve as a reference point when carrying out further studies in the research subject. The review highlights to financial institutions, banking professionals, and policymakers some practical challenges, new security threats, and usability challenges that must be addressed to ensure that mobile banking can become more secure. The paper can also be of practical use to developers and system designers interested in deploying serviceable and easy-to-use authentication systems in financial applications.

The rest of this paper proceeds as follows: Section 2 presents an overview of mobile banking, biometric authentication, role of biometrics in mobile banking and overall rating, Section 3 presents the research methodology, detailing criteria and process we applied in choosing and assessing the academic papers that are collected. Section 4 provides a comprehensive analysis of the academic papers that are gathered, discussing methods used in mobile banking, threat facing mobile banking and biometric authentication methods in leading banks and challenges. Section 5 present the limitation of our study, finally Section 6 present conclusion and future directions.

2.1 Mobile banking

Mobile banking applications changed financial management by providing users with speed and security together with convenience. Users employ these applications to view their account balances and fund transfers and bill payments while also requesting loans through their mobile devices.²⁶ Owing to technological progress, banking services have become more accessible for individuals located in distant areas, thus eliminating their need to visit bank branches. The security features of banks are enhanced through developments such as biometric authentication and encryption to protect against user risk exposure.²

2.2 Biometric authentication

Biometric authentication has also augmented digital security in that it is stronger and more convenient compared to the use of passwords or PIN-code-based access control systems. As compared to traditional systems, biometric authentication systems also validate identity using individual physiological and behavioral attributes i.e. fingerprints, facial characteristics, the pattern of the iris, voice recognitions, and the dynamics of keystroke²⁷ which are naturally very hard to imitate or steal.^28,29 Biometric authentication continues to gain momentum because mobile banking needs cryptographic protection, as do healthcare services,³⁰ border security systems and enterprise network access systems. Biometric solutions have gained prominence among organizations and financial institutions to build improved security systems because these institutions face escalating cyber risks and data breaches.³¹ The benefits of the enhanced security and convenience that biometrics provide systems include serious privacy and ethical risks, data safety and security challenges, and system weakness problems. Figure 2 shows the two types of biometric authentication and presents the common methods used.

Figure 2. Classification of common biometric authentication.

The security model of user authentication via biometrics has several powerful attributes that establish it as a modern choice to protect digital systems. The main advantage of biometric user authentication lies in its security because individual traits such as fingerprints, facial features and iris patterns are unique and difficult to steal or duplicate from traditional passwords.^32,33 Biometric systems increase user convenience because users do not need to memorize complicated passwords or transport physical security measures.³⁴ The system of biometric authentication contains important weaknesses that need to be addressed. System inaccuracies can produce either unauthorized access or user dissatisfaction due to false positive or false negative results.³⁵ Biometric data cannot be altered after a breach occurs in the way that passwords can be changed, thus resulting in severe privacy and security issues when databases are compromised.³⁶ User consent and data protection statutes generate serious ethical and legal issues that emerge when managing biometric data collection and storage processes. User access, which relies on biometric authentication, should be deployed with appropriate precautions while receiving supplemental security safeguards for data protection.³⁷

Biometrics have their strengths and weaknesses,³⁸ as well as the areas in which they are commonly used. For example, fingerprint and facial recognition work well with mobile phones because the phone already has scanning devices.³⁹ Therefore, they are widely used in various digital systems, such as banking systems, healthcare systems, and other mobile applications. Table 2 provides a brief overview of their primary characteristics such as strong and weak points as well as the common uses in digital environments.

2.3 Role of biometrics in mobile banking

The adoption of mobile banking biometric authentication for purely secure account access has become widespread because of the widespread implementation of modern financial services digital transformation, with improved efficiency and user experience of verification processes. User account passwords combined with PIN-based authentication face growing risks from cyber intruders, who exploit phishing attacks, steal credentials and gain unauthorized system access.^31,48 Online banking security evolves through biometric authentication, which is used physical and behavioral features to provide safe access and protection from fraud.²⁸

Mobile banking security, along with fraud prevention, is one of the fundamental purposes of biometric authentication systems. The security of mobile banking in physical biometrics, such as fingerprint scans, facial verification, hand, iris and vein methods, is important for authenticating authorized users.^32,49

Biometrics offer very high resistance against replication and remain difficult to counterfeit, which protects users from unauthorized transactions as well as identity theft.⁵⁰ Continuous authentication from behavioral biometrics becomes essential since it analyzes touch interaction patterns and keystroke dynamics along with voice patterns and typing speed, making network breaches more difficult for cybercriminals.⁵¹ Biometrics serves as a key instrument for delivering improved accessibility while providing excellent user experience. The user experience becomes more convenient through biometric authentication since users obtain immediate and effortless access to mobile banking applications without needing passwords to remember. Security levels are enhanced through this system because users do not need to manage passwords. Financial inclusion grows stronger through biometric authentication because it enables users who lack literacy skills or disabilities to protect banking services by using their fingerprint or other traits instead of standard user authentication, such as passwords/PINs.⁴⁶

Biometric authentication users of mobile banking benefit from its advantages while dealing with privacy risks and security vulnerabilities, which include data protection and system protection issues.⁵² Any unauthorized access to stored biometric information poses substantial risks to users because each person has permanent and distinctive data. To protect biometric data security banks, encryption advances in combination with blockchain-based storage systems and multiple authentication factors have been employed.⁵³

By integrating AI and ML, mobile banking authentication systems can gain the ability to detect more fraudulent transactions alongside the delivery of personalized banking service options to customers.⁵⁴ The future of mobile banking security is moving toward a safer and more efficient digital financial environment because biometric authentication maintains a balance between security and convenience and privacy.⁵⁵

2.4 Overall rating

The concept of mutual compensation enables authentication security by properly utilizing each authentication variable to eliminate their individual weaknesses ( Table 1). A secure authentication system emerges when users provide PBA, KBA and BBA that protects against multiple types of security attacks. People trust the knowledge authentication type for its familiar design, yet this element remains exposed to password intrusion attacks.⁵⁶ When ownership requirements for physical tokens or devices are applied together with passwords, the system provides enhanced security even when a password becomes exposed.⁵⁷ The cost and risk exposure for the ownership element arises from losses connected to token or device disappearance or theft. Security measures benefit from the biometric element because it brings both security through uniqueness and convenience while belonging to the user. Strong protection of biometric data is essential to minimize password-related attacks while physical tokens remain necessary, yet the implementation leads to either positive or negative false negative outcomes.⁵⁸

Although the three authentication categories (KBA, PBA, and BBA)¹⁶ each offer specific advantages, they leave gaps when used alone that can be exploited. KBA is simple but has the lowest security level in terms of phishing and brute-force attacks; PBA is a strong security mechanism based on use of one-time codes or tokens, but it is prone to device-loss attacks; BBA is a strong identity binding mechanism but raises privacy and hardware-cost issues. Thus, our analysis supports a hybrid multi-factor approach whereby complementary factors compensate for the weakness of each other. In environments that require high security, like mobile banking, a three-factor setup (password + token + biometric) offers the best balance of protecting against the theft and spoofing of credentials.¹³ However, in lower risk or resource constrained environments a two-factor scheme (i.e. PIN + OTP) may provide sufficient security with better usability. This aligns with recent banking practices summarized in Table 7, where most institutions adopt mixed MFA frameworks combining knowledge, possession, and inherence factors.

3.1 Research questions

This research aims to evaluate the biometric authentication methods currently adopted for online mobile banking user access. Also, this research examines the effects of cyber threats on online banking user authentication and presents examples of biometric authentication systems used by major banks worldwide, also examines the advantages, disadvantages, aims and challenges through the following research questions:

3.2 Search strategy

A collection of academic papers focused on biometric authentication served as the basis for our review. The selected time span begins on January 1, 2020, and ends on July 1, 2025. This stage involved focused examination of scientific digital libraries and databases alongside searches of keywords and reference management tools and search processes. The next sections delineate the processes described.

3.3 Scientific digital libraries

The analysis took place through major English-language scientific digital libraries and databases. Science Direct, Scopus, IEEE and Google Scholar formed the database scope for this SLR.

3.4 Search for keywords

The research questions of the SLR served as the foundation for creating the search keywords. The included figure presents alternative search terms. We have also added synonyms and alternatives. The synonym keywords are extracted from the corpus of online banking security related subjects in literature. The search query keywords appear in ( Figure 4) as they were applied to the digital libraries mentioned. To provide comprehensive coverage, the literature search was performed in four major databases: ScienceDirect, Scopus, IEEE, and Google Scholar.

Figure 4. PRISMA flow diagram of the process of selecting and screening studies that were included in this systematic literature review.

3.5 Reference management

The research utilized “Mendeley Reference Manager” v2.132.0⁶¹ to serve as the reference management system for collecting and handling retrieved scientific papers. Using Mendeley Reference Manager v2.132.0 allowed researchers to perform quick document management features on their internal database.

3.6 Selection of the study

We examined the research papers that led to the selection of suitable content for our final evaluation using specified inclusion and exclusion criteria. We examined each paper to check its application toward the study’s goals. The review used predefined inclusion criteria to identify and analyze suitable study materials, which led to reliable and valid research outcomes. All the results of this research stem from the number of papers that fulfilled the established criteria permitting their entry into our research.

3.6.1 Exclusion criteria

All studies that were not published in the English language were excluded. Additionally, book chapters, reviews, periodical articles, theses and duplicate papers are excluded.

3.6.2 Inclusion criteria

The inclusion criterion was that the studies were published in English. Only journal publications and conferences that publish studies were included. The biometric authentication in mobile banking research studies covers the methods used in mobile banking, threats, strengths and weaknesses, as well as the methods used in major international banks and user usability challenges and limitations.

3.6.3 Results

The research process resulted in 97 articles through the elimination of duplicate and unrelated studies. The preferred items for reporting systematic reviews and meta-analyses. Two complementary search queries were applied to ensure coverage of biometric authentication keywords ( Figure 4).

The screening process based on PRISMA is illustrated in Figure 4. A total of 913 records were identified in the four databases (Science Direct = 394, Scopus = 152, IEEE = 174, Google Scholar = 193). After elimination of 187 duplicates, 726 unique papers were screened. Following title and abstract screening, 523 papers were excluded, and 203 full-text articles were eligible for further screening. Based on the inclusion and exclusion criteria, 106 papers were deemed ineligible, and 97 studies were finally included in this systematic review.

4.1 Biometric authentication methods used in mobile banking

This section provides an answer to research RQ1: “Which biometric authentication methods are currently used in mobile banking systems?”. The gathered literature appears in Table 3 for 41 studies that are analyzed in three parts: description, year and reference. The taxonomy in Figure 5 illustrates different online payment biometric approaches, which are classified as BBA and MFA. The taxonomy structure enables a complete comprehension of the different authentication approaches, which demonstrate that all current methods operating in online banking use biometrics.

Figure 5. Biometric authentication taxonomy in internet banking, methods based on knowledge, possession and biometrics factors.

4.1.1 Biometric authentication methods

The BBA category uses two types of biometrics, including physical traits, which consist of fingerprints, facial IDs, irises, hands and veins,^{11,17,32,62,63} alongside behavioral traits, which include voice patterns,⁴⁶ “biotuch” (dynamic/continuous touch authentication),^28,64 and tapping behavior. The other behavioral biometric trait was implemented by,⁶⁵ who proposed a new activity recognition model for smartphone applications based on physical activities that are detected by collecting data from different sources, such as biometric sensors or body-worn sensors. The authentication system uses unique biological traits from users to create a high level of security protection. The authentication approach of behavioral biometrics shows great reliability in authorization but creates problems involving data protection and storage security requirements. Organizations use biometric information in addition to developing preventative solutions to combat unapproved system access and illegal information handling.⁶⁶ Various users sometimes encounter difficulties when organizations attempt to establish biometric authentication systems. Online banking system implementations of biometric technology require thorough consideration of hardware needs together with quality standards and acceptance levels from users.⁶⁷ Table 3 provides a description and year for each study.

4.1.2 Integration of biometrics within MFA

Any authentication system built with a single authentication factor remains vulnerable to security threats regardless of the use of fingerprint scans, facial recognition, palm recognition, passwords or PIN. Authentication system developers develop their systems via integrated MFA.⁹⁴ The integration of BBA methods, including fingerprints, faces, irises, hands, veins and behavioral biometrics, serves as the main authentication component for the MFA and 2FA systems.⁹⁵ PBA authentication methods consist of OTPs combined with tokens and NFC⁹⁶ and operate when enhanced with other supporting factors. Various security elements, such as proxies, QR codes, geolocation, IP address MAC addresses and “CAPTCHA,” have joined the MFA and 2FA approaches to increase security measures. Multiple authentication methods used together by banks create enhanced system security, which implements multiple defense barriers for attackers to break. The security system becomes protected by multiple layers if attackers gain access to one part because the remaining layers shield the system from further attacks.^97,98 Users must first type their password before submitting their fingerprint for authorization purposes during system access. This authentication logic increases the security level by making it difficult for attackers to compromise the system despite knowing the user password.⁹⁹ Online banking can establish a secure and all-encompassing authentication system through 2FA and MFA, which reduces the threats caused by depending on a single authentication mechanism. The analysis of previously discussed online banking authentication approaches that can be combined with biometric factors yields the results in Table 5, which presents their strengths together with weaknesses. Based on 41 studies, this research examines the use of biometric authentication methods in online mobile banking, including their role within MFA. These methods are presented in Table 4 and Figure 5. Table 4 provides a comprehensive list of these authentication strategies, complete with their corresponding references.

Figure 5 presents a detailed taxonomy scheme of authentication methods that were specifically developed to protect online banking systems. The taxonomy system groups authentication methods into four basic categories, including the PBA, BBA and KBA approaches and MFA methods. The BBA is divided into two parts: physical biometrics, including fingerprints, faces, irises, hands/pales and veins, and behavioral traits, including voices, touch screens, EEGs, keypads, signatures and ECGs. The KBA consists of a password PIN. The PBA includes OTP and NFC. Other types of authentications include MAC address, IP address, CAPTCHA, QR, proxy and location. The MFA introduced a good security solution by combining the 2FA or MFA from the previously mentioned methods, which illustrates the wide range of security methods used for user verification. This research focuses heavily on biometric authentication by providing detailed information about fingerprints, facial recognition, irises, palm, voice recognition methods, touchscreens, and keystroke dynamics as behavioral verification indicators. This taxonomy explains MFA, which requires users to combine different authentication components such as passwords together with OTP or fingerprints in combination with the MAC address to increase security. The taxonomy establishes itself as a beneficial reference for recognizing the complex authentication methods that modern digital finance systems implement.

Among all the biometric authentication methods face, fingerprint, password, PIN and continuous touch screen authentication methods are the most used since they appear 15, 13, 7, 6 and 6 times, respectively, in total. OTPs and veins appeared 4 times each, and voice was used only 2 times throughout the given data and iris. The authentication system uses several types of verification, including CAPATCHA and keypads, which appear in 3 cases each. One mention exists for each of these authentication methods: palm, keystroke, time-based location, MAC address, IP address, proxy, QR, signature, EEG, ECG, FKP and NFC. MFA security becomes more effective because face and fingerprint detection are used multiple times with additional KBA, such as password/PIN and OTP. Multiple security layers protect sensitive online banking data since MFA operates together with 2FA by employing several authentication techniques. Figure 6 presents the frequency of authentication methods in biometric authentication methods contexts that are implemented in the banking sector.

Figure 6. Frequency distribution of authentication techniques used in biometric systems among studied mobile banking studies.

This study presents a comprehensive and well-structured systematic literature review on biometric in online mobile banking systems, which offers valuable taxonomy, security threat analysis, and insights into global banking practices. Its key achievement is to synthesize the recent research (2020-2025) and provide a clear classification of authentication methods and challenges. So, the absence of quantitative performance and empirical validation comparisons limits its practical depth. Overall, the study provides a strong theoretical foundation and serves as a reliable reference for both academia and industry.

4.1.3 Evaluation of the methods of mobile banking

Table 5 analyzes different authentication methods from our study based on their strengths and weaknesses and corresponding research sources. Simple security systems based on passwords and PINs continue to be popular because they are quick to set up while attackers take advantage of vulnerabilities that result in brute-force attacks and phishing schemes as well as shoulder surfing. User authentication through PIN combined with facial recognition delivers better usability while providing touchless access at the cost of reduced security effectiveness. The implementation of passwords, fingerprints, faces, OTP and locations coupled with MAC address recognition increases security, whereas the use of external communications remains a weak point, and spoofing presents a persistent threat. Biometric authentication through fingerprint scans mixed with facial identification combined with iris analysis creates secure user authentication solutions despite their limitations in terms of external conditions and the need for specific hardware systems. Emerging techniques such as EEG and touchscreen behavior offer unique behavioral or physiological markers but face limitations in practicality and consistency. MFA represents a powerful security method that achieves adequate protection from MFA, while users experience decreased convenience and dependence on devices during authentication processes. Different digital systems require customized authentication strategies that depend on their unique operational needs according to this analysis.

The results summarized in Table 5 emphasize that each category of authentication provides different benefits and weaknesses and confirms the fact that there is no one method which provides total protection against the wide range of cyber threats in the mobile banking environment. Instead, a combined optimization of security strength, usability and implementation cost is required to achieve practical and scalable protection. KBA methods, including passwords and PINs, are the most common because they are so simple and easy to implement. However, they are also the weakest layer of defense, because they are highly vulnerable against brute-force, phishing, and credentials-reuse attacks.^3,100,101 Moreover, users often use predictable passwords or reuse the same passwords for different platforms, which makes compromise much easier. PINs are faster to enter, and they have very little cognitive load, but they are short and vulnerable to observation (shoulder surfing) which limits their effectiveness on their own.

PBA methods such as OTP, NFC-based tokens provide stronger protection with an introduction of time factor or hardware-binding factor. OTPs greatly decrease the chances of the credential replay but rely on the reliability of the communication and can be decrypted on their way or stolen via a SIM-swap attack. NFC cards and hardware tokens provide a physical guarantee although they involve the user carrying or maintaining an external tool, increasing usability and logistical costs.¹¹¹

BBA methods with reference to the fingerprint and facial recognition processes provide an ideal compromise between security and convenience, that is why they quickly become standard in any large mobile banking application.^12,49 Fingerprint recognition is more accurate and faster to verify, and facial recognition can be used contactless and more conveniently. However, they are vulnerable to the quality of sensors, lighting, and spoofing as well as cause serious privacy issues because biometric identifiers are not reversible once compromised.

More expensive modalities, like iris, vein or palm recognition, are very resistant to anti-spoofing and very accurate, but expensive specialized sensors preclude their mass-market use. For example, routine account access may rely upon simple 2FA such as PIN + OTP and high value or cross-border transactions may require full MFA including a biometric check. This strategy offers both convenience and high level of security.

Moreover, incorporating AI-based behavioral monitoring into the MFA pipelines will enable a continuous risk evaluation process and allow making real-time adjustments without undermining the usability. Generally, the comparative synthesis implies that the most resilient way of authentication of mobile banking is hybrid, context-aware and adaptive MFA architectures. By combining the desirable attributes of the various factors such as password familiarity, token possession and biometric factors, but at the same time balancing the weaknesses of these factors, it will be possible to ensure high assurance and acceptance by the user for banks. The findings of this comparative evaluation reflect contemporary trends in international banking practice, in which the most important institutions are increasingly using biometric and MFA in tandem to enhance resilience against changing cyber threats.^113,114

Although the heterogeneity of the reviewed studies made it impossible to conduct a complete quantitative meta-analysis, a systematic summary of the reported performance ranges was built to support the quantitative patterns and trends of biometric modalities deployed on mobile devices. The summarized values of false acceptance rate (FAR), false rejection rate (FRR), and equal error rate (EER) - and indication whether liveness detection and spoofing resistance mechanisms were used - are shown in Table 6, which is for studies published between 2020 and 2025.

As shown in Table 6, most of the reported biometric authentication systems after 2020 have an accuracy rate of greater than 95% and a number of multimodal and deep learning-based approaches have achieved EER values below 1%. However, almost half of the discussed studies failed to report FAR/FRR metrics and only a limited set of studies explicitly used liveness detection or anti-spoofing mechanisms. This suggests that while accuracy has improved significantly from mobile-based biometric systems, issues of presentation attack resistance and real-world scenarios of spoofing remain a major research gap.

4.2 Threat-facing mobile banking

Internet banking provides users with efficient convenience but remains at risk from multiple cybersecurity threats, which endanger both financial service integrity and confidentiality as well as system availability.^115,116 The financial sector poses three prominent security threats against banking consumers, which include phishing scams that trick customers to disclose sensitive data as well as malware intrusions stealing control of devices for login interception¹¹⁷ and man-in-the-middle (MiTM) attacks that break communication between customers and banking institutions. Ransomware attacks,¹¹⁸ along with brute force methods and credential stuffing, exploit password weaknesses by targeting ordinary users who repeat their passwords across different accounts. Moreover, social engineering methods¹¹⁹ allow users to surrender their confidential information. Security threats affect both personal users and cause substantial damage to financial institution reputation and operational stability. We provide answers to RQ2 in this section: “What are the main security threats and vulnerabilities affecting biometric authentication in mobile banking?”. These studies include:

4.2.1 Malware attacks

Mobile banking malware attacks have become increasingly dangerous because smartphone users continually increase their banking activities on mobile devices. The mobile-specific malware category includes banking Trojans and fake banking applications, which lead to theft of login data while also intercepting SMS authentication codes through screen overlay tactics.¹²⁰ The threats take advantage of users downloading harmful applications together with deceitful links that imitate genuine banking platforms. The protection of mobile banking needs strong security measures and app store monitoring while offering user education programs since mobile users demonstrate limited security awareness and malware persists in adapting.^100,121

4.2.2 Man-in-the-Middle (MiTM) attacks

The (MiTM) attack allows cybercriminals to intercept communications between two parties while they cannot detect the security threat. Internet senders become vulnerable to cybercriminals through MiTM attacks, as attackers intercept their sent sensitive information, including login credentials and transaction details, during transmission. Online attackers take advantage of unsecured networks particularly well to launch attacks against public Wi-Fi networks because these networks present communication opportunities. The combination of SSL/TLS encryption protocols with safe programming practices and user training about risk networks makes sensitive banking information secure during online financial activities.^56,122,123

4.2.3 Replay attack

An attacker generates fraud by intercepting authentic transmission data to fool an intended recipient into taking actions that might include transaction authorization. The fraudulent method of playing replays allows attackers to pose as victims and redirect transaction details to a bank for resulting payments or account transfers.¹²⁴ Attackers exploit old communication protocols without session state validation and timestamping, which they leverage for their attacks. All submitted transactions must pass through time-based authentication protocols, whereas financial institutions need to use nonce-secured requests with session tokens for attack prevention.^56,125,126

4.2.4 Phishing attacks

Criminal online attackers conduct phishing operations for social engineering by pretending to be trusted parties to steal sensitive data that includes usernames with passwords and credit card details. Criminals execute phishing attacks in online banking through fake websites or emails, which are intended to be actual banking sites because they trick users to provide login details and sensitive financial information. Phishing attacks succeed by targeting human mistakes combined with trust to obtain sensitive information, which requires users to develop heightened awareness to stop them.^121,127

4.2.5 Social engineering

Attackers use social engineering as a method to force users to reveal sensitive data or perform actions that endanger their banking account security through online interfaces. Attackers use deception techniques such as urgency fabrication along with impersonation and trust-building tactics to trick users.^57,128,129

4.2.6 SQL injection

The attackers conduct SQL injection attacks by adding harmful code to the data strings before they reach the SQL database for processing. SQL injection allows hackers to obtain user credentials, including usernames and passwords. The stolen credentials serve as keys to unauthorized access of user accounts.^14,130,131

4.2.7 Keylogger

A keylogger functions as malicious software that tracks computer keystrokes. A keylogger logs every keystroke typed on a system that has been compromised and captures sensitive data, including passwords, usernames, etc. Your computer can acquire keyloggers through a few methods, including opening tainted attachments and clicking on harmful links together with downloading files from unverified sources. A keylogger that uses the system to record keystrokes becomes operational after installation on a computer.²⁹

4.2.8 Weak password

Weak passwords pose security threats to online banking since they provide easy opportunities for attackers to guess them. The entry of unauthorized actors becomes easier when passwords are weak because they gain instant access to sensitive data and user accounts and execute fraudulent schemes.^123,132

4.2.9 Denial-of-Service (DoS) attacks

DoS attacks block access for genuine users in online banking operations through a combination of abusive network traffic that saturates system resources. Service interruptions alongside customer dissatisfaction result from this situation, which leads to financial losses for the bank. Some attacks that initiate denial-of-service conditions serve as shields for other more dangerous threats, including data theft.^98,101

4.2.10 Session hijacking

Unauthorized session access, which enables an attacker to exploit user identity for online bank account access, is known as “session hijacking.” Network connection interceptions, along with exploiting system vulnerabilities, enable attackers to conduct unlawful activities while acquiring private information.¹³³

The attacks mentioned earlier show vulnerability to the supply chain and third-party or endpoint access of online banking systems, which results in supply chain attacks that involve attackers using external third-party software or vendors to access systems. The security vulnerabilities in banking systems enable hackers to break online banking security, which might result in unauthorized access and data breaches. Attackers execute endpoint attacks by focusing on both the user’s devices and end points. The attackers want to infiltrate the user’s device to access confidential banking data, which results in both financial fraud and unauthorized transactions.¹²⁶

Financial institutions need to use the security measures presented in Table 7 to build protective online banking systems that secure user financial details. Financial institutions establish better online banking security through a complete strategy that integrates technical solutions such as firewalls and antiviruses, educates users about risks and develops essential policies plus continuous observations of systems. Table 7 summarizes these threats while presenting countermeasures that could serve to prevent them.

4.3 Biometric used in international banks

The investigation of RQ3: “How do major banks worldwide implement and integrate biometric authentication into their mobile banking applications?” takes place in this section. The analysis of authentication practices utilized by international banks provides fundamental knowledge about contemporary changes in online banking safety measures. The selected banks outline their user authentication techniques in Table 8 demonstrates how various popular financial institutions authenticate their users.

The information in Table 8 reveals the user authentication strategies used by several well-known financial institutions, including JPMorgan Chase, Bank of America, HSBC, Barclays, Deutsche Bank, BNP Paribas, Santander, ING, Standard Chartered, DBS Bank, HSBC Hong Kong, RBC (Royal Bank of Canada), and NAB (National Australia Bank).

Financial institutions utilize MFA systems because they prioritize the defense of customer online account security. Financial institutions mainly employ password authentication as their principal security procedure. Account holders need to build passwords for their financial institutions, which adhere to prescribed guidelines (such as the NIST password policy) that require eight characters or more in length with a mixture of upper and lowercase letters and numbers and symbols. The initial security measure that defends against unapproved system access is the use of passwords. OTP authentication serves as a security approach that numerous financial institutions within the banking sector currently use. New device users must provide a unique OTP password that arrives through SMS or email to finish their login process. Users must provide the received code before their login process can become fully secure. OTP serves only single login sessions and operates with limited validity, making it highly unlikely for attackers to obtain the password. The rising trend in banking shows that physiological biometric identification serves banks as a safer authentication option than passcodes do. Special physical attributes such as fingerprints and facial recognition serve as verification tools to identify customers during their process.¹¹³ The authentication method poses challenges to falsify essential data, thus making it an optimal barrier against unauthorized access. Security functions at these banks are implemented via 2FA technology. Users need to enter two security factors along with their password during first-time logins from new devices by providing an OTP or biometric verification. Security protection from 2FA¹⁴⁵ creates a double authentication requirement that makes unauthorized access attempts practically impossible. Banks offer alternative authentication solutions for customers, which include USB security keys as well as security questions and challenge/response authentication and voiceprint authentication and device fingerprints.¹⁴⁶ Device fingerprints determine the devices used by users, whereas voiceprint authentication depends on a person’s voice specifics.¹⁴⁷ A challenge/response system requires the customer to enter authorization codes that originate from bank transmissions to their mobile device. Security keys connected to a USB port work as extended measures for online banking safety by enabling users to enhance transfer constraints through their computer’s USB connector. As customers complete the login process, the system asks them to answer security questions that have already been chosen by the platform, thus activating security authentication. Bank security measures receive ongoing assessment and updates from these banks to maintain timely protection of customer account safety against new security challenges.

We highlighted the use of biometrics in leading banks, extracted from Table 8, to determine the most used authentication methods. Table 9 illustrates the role of the biometric methods used by leading banks.

From Table 9 we note that: Fingerprint and Facial recognition are the two most used biometric mechanisms probably because most of the smartphones now support them and they are highly accepted by users. Voice recognition is rarer, and more often in mobile-based banking. Palm veins are quite unusual, but there is higher security and usage in physical (store for payments) authentication scenarios. Mobile banking for convenient and secure login is the most common area of biometric applications. Some banks (for example, DBS Bank) merge several biometric devices, for example: fingerprint, face and voice – suggestive of a multi-modal approach in security improvement.

Figure 7 depicts visual representation of how often each of the biometric authentication methods are used by the banks. As you can observe, fingerprints and facial recognition outrun the competitors, while voice and palm vein scanning are far rarer.

Figure 7. Distribution of biometric authentication technologies (e.g., fingerprint, facial, voice, palm) adopted by major banks in the world, reflecting adoption trends and popularity in mobile banking services.

4.4 Usability and user perception challenges and limitations

The literature shows that there is a stark tradeoff between strength of security and usability. As biometrics increase protection, the ineffective user experience will decrease adoption and efficacy. The banks must focus on usability testing, offer alternative, safe options (i.e., token generated by the device), and increase transparency regarding the use of biometric data.

The usability and how often it is perceived by the user are important issues that determine the significance and adoption of biometric authentication mobile banking techniques. As indicated in various other studies^156,157 one of the issues many users face when using biometric systems is irritation related to the unreliability of these systems, such as inability to recognize their fingerprint when their fingers are wet, in situations of skin damage, or due to technical purposes of sensors. In the same light, facial recognition has been observed to perform poorly in low-light situations or when the user is wearing glasses or face mask. Such technical shortcomings may undermine the trust in the system and make people turn off the security features or switch to the less safe options (e.g., back to the passwords or PINs).

On top of technical problems, user perception plays an important part in the adoption of biometrics. A study conducted by¹⁵⁸ has revealed that a high percentage of users were worried about the personal safety and confidentiality of biometric data particularly when this data was stored on cloud-based platform instead of being secured on the gadget. The level of confidence in banks and their confidentiality of information was a deciding factor as to whether the user activated biometric authentication. Moreover, some studies like,³⁸ have pointed out the issue of the inaccessibility of MFA especially to ageing people and individuals with disabilities who might have a hard time using or comprehending some MFA techniques. Overall, literature points at the necessity to design authentication systems in a way that composes security and simplicity to use, availability, and visibility, so that security apparatus will not be an obstacle to user interaction. Online banking user authentication techniques and cyber threats maintain an uncertain outlook, but the resulting risks remain massive.⁵⁸

In this section we answered RQ4 which stated: “What is the key usability, privacy, and user acceptance challenges related to biometric authentication in mobile banking?”.

These challenges represent the main difficulties that must be addressed when enhancing the security of online banking systems, in addition to user authentication procedures. We have classified the most important challenges as follows:

4.4.1 Artificial intelligence challenge

The adoption of artificial intelligence through machine learning by cyberattacks presents a threat to online banking infrastructure, which includes network breaches and defeats detection systems. The implementation of ML involves several methods for breaching online banking authentication systems.^159–161

4.4.1.1 Bias in biometric systems

Biometric systems powered by artificial intelligence produce irregular results when processing users from diverse population demographics, including ethnicities, as well as gender and age groups. A lack of diversity in training data can result in unfair FAR or FRR errors that produce trust and legal challenges among specific users.¹⁶²

4.4.1.2 Adversarial attacks

Information security risks exist because AI authentication systems can be deceived through adversarial examples that adversaries specifically generate to trick them (such as manipulated fingerprints, deepfakes or altered patterns). Researchers aim to build authentication models with resistance to manipulation because this remains a critical research topic.^125,163,164

4.4.1.3 Deep fakes can be produced

Artificial deep fakes demand ML techniques for their production. Artificial works labeled deep fakes combine someone else’s likeness by replacing it with extant images and footage. Any recorded online banking registration activity can be faked through deep fakes to steal user login credentials used in the fake video.^{163,165–167}

4.4.1.4 ML technology

ML enables the automation of assaults against banking systems that operate through the internet. The automation of attacks targeting online banking systems becomes possible through the application of ML techniques for addressing guessing attacks as well as brute-force attacks and DoS attacks.¹⁴⁴ The attackers benefit from simpler ways to run successful assaults against online banking infrastructure. Phishing attacks can be launched with the assistance of ML.¹⁶⁸ Phishing attacks use deceptive methods to force users to reveal their critical account information, including bank card numbers and network access secrets. AI facilitates the development of convincing phishing emails along with corresponding websites that target users.¹⁵⁹ These attacks become more deceptive because they offer a higher probability of deceiving users.

ML provides banks with tools to protect their systems from cyberattacks, enabling them to enhance the security and resilience of their systems. By utilizing ML, banks enhance both their risk management and compliance practices to detect and prevent fraud together with malware and phishing attacks.¹⁶⁹ The application approach of ML determines whether it offers either risk or an opportunity to use online banking systems.¹⁷⁰

4.4.1.5 High computational and energy demands

The functionality of real-time authentication based on AI processing through onboard device resources is restricted to older and less expensive mobile devices. Cloud storage introduces new security risks during processing combined with greater processing delays.¹⁷¹

4.4.1.6 Explainability and transparency

The issue of explainability and transparency in mobile banking deserves attention because biometric authentication systems are often complicated. Since these systems heavily depend on complicated algorithms, the AI-based and machine learning algorithms to make authentication decisions, unsuspecting individuals and even the systems operators are often locked out of the process of how such decisions are made. Failure to find an obvious justification in denying access or scoring suspicious users may cause frustration, mistrust, and losses to user abandonment. In addition, regulatory and ethical aspects, audit, accountability, and determination of fairness are also critical regarding transparent systems, especially when it is biometric data of a sensitive nature. Improving explainability will enable developers to pinpoint and redress errors or bias and give users a more effective understanding of how their data are utilized, enhancing trust and confidence in the mobile banking authentication in general.^171,172

4.4.1.7 Spoofing and presentation attacks

The presented attack and spoofing vulnerability are one of the greatest disadvantages of biometric authentication in mobile banking systems. These attacks consist of hoodwinking the system by fueling fake or imaginary biometrics, including silicon fingerprints,¹³² photographs with a high resolution of the face, or even complex masks made of 3D printers.¹⁷³ As an example, can an attacker lift a fingerprint off a surface and re-mold it in gelatin or latex material or defeat facial recognition by having a video replay or a 3D mask.¹⁷⁴ Most bio-metric systems have attempted to counteract these threats by utilizing liveness except tools, which might include blinking or feel of the skin texture, although not universally and reliably as in the case with all devices. Spoofing attacks can succeed better in low end smartphones or applications with weak security. Also, the use of liveness detection may affect user experience in some cases, which makes developers turn it off or modify it in some way.⁴³ With ever evolving spoofing techniques such as usage of deep fakes and masks embedded with motion, the present-day biometric systems are struggling to provide secure authentication. This does not only endanger user accounts to unauthorized access but also jeopardizes the user faith; it raises legal and regulatory issues to financial institutions. Implementing multimodal biometric authentication, constant surveillance and AI-based spoof protection is essential in building solid mobile banking security.¹⁷⁵

4.4.1.8 Dependency and hardware limitations

In mobile banking, the performance of biometrics depends highly on the hardware capacity of their devices. Premium smartphones are additionally obvious to have improved sensors, such as depth cameras or ultrasonic fingerprint readers,¹⁷⁶ which enable more authentication with high degrees of accuracy and safety. On the other hand, the cameras that come with the low-end or older devices are of basic 2D type or capacitive sensors, and these are more error prone and could be more easily spoofed. Such hardware mismatches may cause uneven authentication experiences, false acceptance rate/false rejection rate and exclusion of users with an outdated device.¹⁷⁷ Also, the scarcity of hardware support makes the process of developing apps harder and does not allow implementing higher levels of security, which, in turn, makes mobile banking platforms less secure and readily accessible.

4.4.2 False Acceptance/False Rejection Rates (FAR/FRR)

FAR and FRR are some of the errors ( Figure 8), which make biometric authentication systems vulnerable. FAR is defined as access given to unauthorized users when it is not supposed to be which is wrong and FRR is defined as being denied by the unauthorized user when it is not supposed to be the case. Such errors may be caused, among others, with improper lighting, inclusions or damage of sensors, alterations of physical appearance of the user (age, injury, facial hair), or inconsistent behavior of the sensors among different devices. When FAR is high this compromises security whereas when FRR is high this affects usability and user satisfaction, two important functions in mobile bank applications. Designing a workable balance between these rates is a major difficulty in the design of biometric systems.¹⁷⁷

Figure 8. Illustration of the trade-off between FAR and FRR in biometric authentication.

4.4.3 Balancing security and usability

This right balance between security and usability is one of the major issues of implementing biometric authentication methods giving in mobile banking. Although greater security can be brought about by higher quality security procedures, e.g., through multiple authentication factors or high-quality liveness detection, this can also serve to deliver friction, delay or confusion to users. Conversely, simplified forms of authentication can provide a better experience but can leave systems at a higher risk of attack. To give an example, high tires of login using multiple steps can be strenuous to users and decrease the usage of the application and by contrast, using biometrics as the only mode of verification can isolate users with certain accessibility challenges. To achieve effective authentication, one therefore must balance a range between sound protection over threats and not jeopardizing ease of use and accessibility by the users. To do that, it will be necessary to have adaptive authentication mechanisms, user-centered design, and continuous assessment of security point risks as well as user behavior.^178,179

4.4.4 Regulatory and ethical compliance

Regulatory and ethical compliance plays an important role when implementing biometrics authentications in mobile banking. The legal environment is very complicated, and financial institutions have to comply with international data protection regulations including the General Data Protection Regulation (GDPR), Regulation (EU) 2016/679 of the European Parliament and of the council on data protection and privacy and the California Consumer Privacy Act of 2018 (CCPA), enacted by the California Legislature to enhance consumer data privacy protections in the United States.¹⁶¹ These laws obligate organizations to obtain informed consent from users, reduce the amount of data collected, store information in a safe manner and make the processing of the biometrics open. Banks also have an ethical obligation to stop misuses or discrimination through systems that provide poor results according to a demographic group. A failure to fulfill these responsibilities may lead to legal action and damage to reputation, an economic impact and loss of the trust of the users. To adhere to it, organizations are required to incorporate privacy-by-design, conduct regular system audit to determine its fairness and non-discriminatory nature, and ensure that it grants users full control over their personal biometric information.¹⁴⁷

4.4.5 User privacy challenge

Online banking authentication through the BBA, including fingerprint authentication, presents the highest security level because attempts to forge or steal biometric data prove very difficult. The application of BBA includes privacy-related problems. A biometric database breach of a bank will give hackers the ability to obtain all the authenticity data of its banking clients. Customers have reservations about banking establishments and other organizations storing their biometric information. Banks that utilize BBA require proper protection of biometric data that belongs to their clients. Banks must secure data against unlawful handling through preventative measures. A privacy policy needs to exist that explains to clients how their biometric information will be handled.¹²⁶

4.4.6 System compatibility challenge

Financial institutions must transform their current technology platforms and authorize procedures to welcome different authentication approaches, such as biometrics along with tokens and MFA, for online banking access. Additionally, merchants should approve of their payment vendors, who assist in online authentication.¹⁷⁹

4.4.7 System usability challenge

The user authentication sector faces a conventional challenge because securing systems becomes riskier when making authentication methods easier to use. The implementation of layering represents a security improvement approach for user authentication systems.⁹⁸ MFA requires multiple security checks that combine multiple factors such as biometric authentication, passwords/PIN, OTP and/or other factors.⁷³ Layering is founded on the fact that if one safeguard is breached, other levels of security will still protect the system from the undesired users. The number of layers determines better system protection but creates a declining usability experience. The authentication procedure becomes more challenging with each additional layer, which ultimately leads to user frustration.¹⁷⁸ Our system enhances security when we use multiple authentication layers, although usability decreases at the same time. Security and usability must be balanced when choosing authentication methods according to the required security measures.