Abstract

This research paper explores the ethical issues in using financial technology (FinTech), including how to navigate them and how to build customer trust. The research emphasises the importance of safeguarding customer data, complying with data protection laws and avoiding making ethical mistakes that threaten a company’s trust. The study provides practical suggestions on why it is important that a FinTech company is trustworthy, it includes examples of ethical issues and it examines how these affect fintech. However, the study is limited by its exclusion of non-English-language studies and the need for additional resources to deepen the findings. To overcome these limitations, future research could expand existing knowledge and collect more comprehensive data to better understand the complex issues examined.

Introduction

FinTech refers to the use of technology in finance, which provides a new method of transferring, keeping and collecting money through technology instead of physical sources. FinTech enables companies and customers to safely and easily manage their financial activities. In this article, we focus on the ethical and trust issues which we consider the most crucial component of a large and change-resistant structure like the financial system. This challenge underscores the necessity of examining ethical frameworks within the sector. 

Over the past two decades, the widespread impact of digital transformation and technology is evident, delivering great value and decreased costs across the world. The financial services have been unrecognisable as FinTech changes the old structures of traditional banking, promising greater efficiency and universal access as well as instant transactions. However, great opportunities bring great challenges. When the long trust-based relationship is replaced with technology, unavoidable ethical issues emerge. Trust is non-negotiable in finance, and in an increasingly digital world, consumers now depend on the integrity of algorithms, the strength of cybersecurity protocols and the transparency of the data-processing architectures. This transformation is radically redefining ethical obligation.

This paper questions how traditional ethical issues in finance, such as conflicts of interest, fraud, market manipulation, misuse of confidential information and tax evasion are changing in the context of FinTech and AI-driven digital services, and to what extent consumer-protection frameworks like the GDPR can help rebuild and maintain trust in this new ecosystem.

Consumer Trust in FinTech

With the rise of FinTech comes new consumer risks. Digital lending, investment platforms, mobile payments and peer-to-peer systems all carry different types of risks compared to traditional banking, including increasing consumer debt, unclear or hidden fee structures, and automated credit or payment systems where users may approve terms without fully understanding them (World Bank, 2022). In order to build customer trust in new financial technology, companies should be honest and clear about how they collect and use customer data, and should openly explain how their systems and algorithms make decisions, especially when it comes to loans or credit scores. Misuse of personal information, over or under-pricing, or lack of transparency will contribute to diminishing customer trust.

The General Data Protection Regulation (GDPR) establishes several core definitions central to data privacy. Personal data is defined as any information relating to an individual, while data processing encompasses any action performed on that data, whether automated or manual. Distinct roles are also established: the data subject is the individual whose information is processed, whereas the data controller determines the purpose and means of processing, often engaging a third-party data processor. The framework mandates seven key principles:

1. Lawfulness, fairness and transparency: Processing must be lawful, fair and transparent to the data subject (GDPR, 2018).
2. Purpose limitation: Data should be processed for legitimate purposes specified explicitly to the data subject when collected (GDPR, 2018).
3. Data minimisation: Only required data should be collected and processed for the specified purposes (GDPR, 2018).
4. Accuracy: Personal data should be accurate and up to date (GDPR, 2018).
5. Storage limitation: Personally identifying data should only be stored for as long as necessary for the specified purpose (GDPR, 2018).
6. Integrity and confidentiality: Processing must be done in such a way as to ensure appropriate security, integrity and confidentiality (GDPR, 2018).
7. Accountability: The data controller is responsible for being able to demonstrate GDPR compliance with all these principles (GDPR, 2018).

In FinTech, almost every service is built on personal and transactional data. Therefore, the GDPR is not just a legal framework, it is also a design constraint and trust infrastructure for the entire FinTech ecosystem. Evidence suggests that the GDPR has contributed to the development of FinTech by strengthening trust in the ecosystem.

Ethical Issues in Finance

To understand how FinTech can balance consumer trust with emerging ethical risks, it is necessary to examine the main ethical issues in the broader financial system. As the central question of this paper is how long-standing ethical issues in finance are transformed by the rise of FinTech and AI, and what this means for consumer trust and protection, we will examine the ethical issues in finance and how they transform with FinTech.

1. Conflict of Interest

A conflict of interest in finance occurs when an individual or organisation’s personal or financial interests could compromise their professional duties, leading to decisions that are not in the best interest of the clients or the company. This can happen when a person stands to gain or lose financially from a decision they make at work, such as when a financial advisor receives a commission for selling a certain product or when a director has a stake in a company that is bidding for a contract. These conflicts can damage trust, lead to financial harm for clients and are subject to strict management and reporting requirements. 

Conflicts of interest manifest in various forms within the financial sector. A common example is advisor commissions, where a professional recommends products based on personal gain rather than client benefit, a scenario mirrored in FinTech when crypto exchanges promote tokens they hold a stake in. Other instances include the misuse of insider information for personal trading, competing interests when advising rival firms or personal relationships influencing business decisions. To mitigate these risks, firms must implement robust policies and procedures, including the strict segregation of duties to prevent individuals from acting on conflicts. Transparency is also critical; firms are often required to disclose potential conflicts to clients, while third-party reviews and external audits ensure these management strategies are effective.

HOW FINANCIAL FIRMS MANAGE CONFLICTS OF INTEREST

• Policies and procedures: Firms must create and maintain strong policies and procedures to identify and manage conflicts.
• Disclosure: Firms are often required to disclose potential conflicts of interest to clients.
• Segregation of duties: Separating business units or individuals to prevent them from acting on conflicts.
• Third-party reviews: Using external audits to ensure conflicts are properly managed. For FinTech firms, independent model audits, algorithm fairness assessments and cybersecurity risk reviews are performed.
• Regulatory oversight: Financial regulators hold firms accountable for managing conflicts and can impose penalties for failing to do so. With FinTech, oversight is now extended greatly. It includes digital lending models, robo-advisors, crypto platforms and open banking systems. The aim is to ensure automated systems follow the same ethical expectations as human advisors and cannot be manipulated.

2. Insider Trading

Insider trading is the buying or selling of a company’s securities based on material non-public information (MNPI) about the company. It is important to distinguish between legal and illegal forms of this practice. Legal insider trading occurs when corporate insiders trade their company’s securities while strictly adhering to reporting regulations and public disclosure requirements. In contrast, illegal insider trading involves profiting from confidential, material non-public information, such as knowledge of pending mergers or unreleased financial results. This behaviour creates an unfair advantage, erodes market trust by establishing a two-tiered system, and distorts prices to the detriment of uninformed investors. Consequently, penalties are severe, including fines of up to $5 million for individuals and prison sentences of up to 20 years.

In the FinTech ecosystem, insider trading concerns are evolving, especially in algorithm-driven trading platforms, cryptocurrency exchanges and decentralised finance (DeFi). Financial institutions were previously slow and bureaucratic, but that is no longer the case. Some FinTech platforms operate in fast-moving and less-regulated digital markets, increasing the risk of undisclosed access to privileged technical, operational or blockchain-level information. Modern compliance software is used to identify anomalies in trading data, such as unusual timing or volume, that may indicate insider trading. In FinTech, machine learning models and blockchain analytics play an important role in detecting suspicious token movement and wallet address clustering.

3. Confidentiality

Confidentiality in finance is the ethical and legal obligation for financial institutions and professionals to protect sensitive client information from unauthorised disclosure. This includes personal data, account details and transaction histories, which are kept private unless the client gives consent or a legal mandate requires disclosure. Confidentiality builds trust and is protected by professional standards and laws, though there are legal exceptions that require information to be revealed. In FinTech ecosystems, the risk of large-scale exposure is much higher than in traditional finance. Therefore, confidentiality also includes digital infrastructures such as cloud storage systems, automated decision-making models and open banking data flows. 

KEY ASPECTS

• Protection of client data: Financial professionals must safeguard sensitive information like full names, addresses, account numbers, passwords and financial records. In FinTech platforms, especially mobile banking and digital wallets, biometric authentication (such as Face ID or fingerprint login) is commonly used to strengthen protection. 
• Legal and ethical duty: The obligation to maintain confidentiality is both a matter of professional ethics and a legal requirement, governed by laws and industry standards. The GDPR, PSD2 and data residency laws have been widely used and accepted. In open banking environments, third-party service providers must provide compliance with the rules and standards.
• Client trust: Confidentiality is crucial for building trust between clients and financial institutions, which is essential for the efficient operation of the financial sector. For example, in the 2020 ledger breach case, a crypto wallet company’s customer database was hacked. This led to the leaking of names, emails and home addresses. This incident showed that confidentiality failures in FinTech can create real physical and emotional risks, not just digital ones (Ledger Incident Report, 2020).
• Limited exceptions: Information can be disclosed without consent only in specific situations, such as a court order or other legally-mandated case.
• Scope of information: Confidential information includes all non-public data, whether it is in digital or printed form, and can even include strategic business plans.
• Application: This principle applies to a wide range of financial services, from banking to accounting and financial advising. It includes robo-advisors, buy-now-pay-later services, crypto exchanges, AI-based credit scoring tools and decentralised finance (DeFi) identity systems that store sensitive financial data in distributed environments.

4. Fraud

Financial fraud is the intentional deception to gain money or assets, often by misrepresenting facts or stealing information. Common types include investment scams, identity theft, payment fraud and tax evasion, which can result in significant financial losses for individuals and businesses. In the FinTech environment, fraud has evolved greatly with digital tools. For example, fake cryptocurrency platforms, deepfake voice scams and fraudulent mobile payment requests are becoming more common and dangerous. Preventing financial fraud involves being aware of the risks, implementing strong security measures and reporting any suspicious activity immediately. 

Financial fraud has evolved alongside digital tools. Investment fraud, such as Ponzi schemes, have found new life in FinTech through fake cryptocurrency or NFT platforms that promise high returns with minimal risk. Identity theft and payment fraud also pose significant threats, with attackers targetting digital wallets and using SIM-swap attacks to authorise fraudulent transactions. Furthermore, phishing remains a prevalent tactic, where scammers impersonate digital banks to extract sensitive information from users. These external threats sit alongside internal crimes such as embezzlement, insider trading and money laundering, all of which undermine the integrity of the financial ecosystem.

5. Fraudulent Financial Reporting

Fraudulent financial reporting is the intentional misstatement or omission of material information in a company’s financial statements to deceive users like investors and creditors. This includes overstating revenues, inflating asset values or concealing liabilities and expenses to make the company appear more profitable or financially healthier than it is. The goal is often to meet targets, inflate stock prices or secure loans, and the practice is a form of corporate fraud distinct from the misappropriation of assets for personal gain.

In the FinTech sector, fraudulent financial reporting can appear in several forms. For example:

• Intentional misrepresentation: A deliberate act to provide false information, unlike an honest accounting error. For example, the crypto exchange FTX misrepresented its asset reserves and liquidity position before its collapse in 2022 (NY Times, 2022; Digital Defend, 2025).
• Deception: The intent to mislead stakeholders to make decisions based on inaccurate data. Wirecard is a well-documented example, where €1.9 billion in reported cash reserves did not exist, misleading investors, regulators and global banking partners.

6. Market Manipulation

Market manipulation is a criminal act that involves attempting to mislead the market by providing false or misleading signals about financial instruments’ supply, demand or prices. It can also be done indirectly by spreading false or misleading information about a listed company. 

Market manipulation can take several sophisticated forms. One such method is advancing the bid, where orders are entered specifically to artificially increase a financial instrument’s price. Another technique, layering, involves submitting multiple orders away from the market price to create a false impression of liquidity, only to cancel them once a favourable trade is executed, a practice recently observed in crypto market-making firms. Perhaps the most well-known scheme is “pump and dump”, where false positive information is spread to inflate prices before the manipulator sells off their position. Other tactics include marking the close, where trades are executed near the end of a session to influence the reference price, and the use of misleading signals to disrupt supply and demand perceptions.

7. Objectivity

Objectivity in finance means presenting financial information based on verifiable evidence and facts, free from personal bias, emotions or conflicts of interest. This principle ensures that financial reporting is neutral, accurate and credible, which builds trust with stakeholders and supports sound decision making. Key aspects include using verifiable data like invoices and receipts, applying consistent methods and disclosing any potential conflicts. 

CORE PRINCIPLES

• Based on verifiable evidence: Financial information must be supported by objective, reliable evidence such as invoices, receipts and bank statements, rather than subjective beliefs or opinions.
• Free from bias: Financial reporting should be impartial and neutral, not influenced by personal feelings, motives or the desire to present a more favourable picture than reality. Revolut was criticised because employees’ compliance concerns were ignored while the company focused mainly on fast growth and increasing its value. This situation raised doubts about whether reporting was objective and made people question the governance culture of the company (Komolafe, 2025).
• Independent and impartial: Accountants and financial professionals should set aside personal views and inclinations to avoid undue influence from others or conflicts of interest.
• Consistent application: Applying the same accounting principles and methods across different reporting periods ensures consistency and comparability, which is a key component of objectivity. 

8. Stealing Funds

Misappropriation of company funds is a form of financial or “white-collar” crime. It involves the unauthorised use or theft of money or other assets. It is the using of funds that were intended for a different, specific use. The funds may belong to an individual, company or organisation such as the UK government. Funds misappropriation can include anything from a director using company funds for personal gain (such as to buy a new property) to an employee siphoning cash from an organisation’s accounts. It is a serious offence which can result in unemployment, fines, director disqualification or even a prison sentence.

TYPES OF MISAPPROPRIATION OF FUNDS

• Embezzlement: The theft or exploitation of money entrusted to someone for safekeeping or management. For example, a bookkeeper who steals company funds from their employer’s bank account. In 2023, a former employee at the digital bank Chime was charged for creating fraudulent refund transactions and transferring customer funds into personal accounts, demonstrating how digital refund systems can be exploited when internal controls are weak (US Department of Justice, 2023).
• Fraud: Deliberately deceiving others to gain access to funds that would not otherwise be available. This can take many forms, including identity theft, false invoices and falsifying financial statements. A major case occurred when criminals used Zelle and other US instant payment platforms to impersonate bank representatives, tricking users into authorising transfers that appeared legitimate but resulted in consumer losses and legal debates around liability (New York Times, 2022).
• Insider trading: Obtaining confidential or non-public information, such as a trade secret, to make unfairly advantageous trades on the stock market.
• Money laundering: The process of hiding profits from illegal activity by making them appear legitimate. Money laundering often involves moving funds through multiple bank accounts, or countries, to conceal how the money was obtained.
• Tax fraud: Deliberately providing false information to HMRC to pay less tax. This includes failing to declare income, overstating expenses or claiming false tax credits.
• Director self-dealing: When a director uses company funds to repay a loan which they have personally guaranteed, thus lessening their personal exposure to repaying the debt in the event that the company cannot pay that liability. This can be referred to as self-dealing or simply a conflict of interest.

9. Misrepresentation

A misrepresentation is a false statement made intentionally by one party to influence the other party to abide by the contract’s terms and conditions. A justified misrepresentation in the execution renders the contract void, and depending on the situation, the deceived party may seek legal redress and be awarded damages for any loss incurred or rescind the contract.

TYPES OF MISREPRESENTATION

Fraudulent misrepresentation. Fraudulent misrepresentation is a reckless statement made by one party to induce another party to enter a contract. For example, a party may provide a statement that they know is untrue to another party that a parcel of land in Texas is in an area where oil drilling recently started. The party becomes liable for fraudulent misrepresentation if the land is purchased based on false information. The Theranos case, although categorised under health-tech, is widely referenced in digital financial services because investors, partners and regulators were misled into believing the platform’s technology was operational and validated; misleading claims contributed to over $700 million in investor losses, making it a frequently cited example in digital innovation ethics (US Securities and Exchange Commission, 2018).

Negligent misrepresentation. Negligent misrepresentation is a form of non-fraudulent misrepresentation, where a defendant makes a false statement without due care in ascertaining its truthfulness. For example, if an audit firm is aware that a client will use one of its reports to get a bank loan, the firm will be liable for wrongful misrepresentation if the report contains false information about the client’s business. The injured party may rescind the contract or file for damages incurred. Thus, negligent misrepresentation renders a contract voidable.

Innocent misrepresentation. Innocent misrepresentation is a statement of a material fact made by one party to induce a contract with another party without the knowledge of its falsity but with due care. The remedy is usually termination or rescission of the contract. For example, consider a party who is contracted to sell a parcel of land to another party with a mutual understanding that the buyer will build an apartment on it. Both parties believe that it is lawful to use the parcel for the intended purpose. However, several days before completing the contract, the municipality in which the property is located had enacted an ordinance precluding land use for such purpose.

Conclusion

For FinTech to grow, companies must integrate ethical values into their design, decision making and operational processes. Building trust requires strategies based on transparency, accountability, fairness and user empowerment.

In the Wells Fargo case, the bank created millions of unauthorised accounts without customer consent and charged hidden fees which was a major scandal that showed how automation and algorithmic systems can violate neutrality (US. SEC, 2018). This incident emerged from both incentive structures of the bank and uncontrolled individual practices. Regulators have responded by prioritising data rights, transparency and accountability, using frameworks like the GDPR as global reference points.  Instead of relying on punishment, regulations showed that collaboration and early safeguards can build trust while supporting innovation.

The evolution of customer services reflects a broader shift in how organisations understand and respond to consumer expectations. From traditional, transaction-focused support to today’s proactive, technology-driven and highly personalised experiences, customer service has become a central pillar of competitive strategy. Advancements such as automation, data analytics and omni-channel communication have empowered businesses to provide faster, more seamless interactions while also giving customers greater control over their service journeys. Yet, as important as these tools are, the human element remains essential; empathy, trust and relationship-building continue to differentiate exceptional service from merely adequate support. Ultimately, the ongoing transformation of customer services underscores a simple truth: organisations that adapt, listen and innovate will be best positioned to meet the evolving needs of their customers and thrive in an ever-changing marketplace.

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