Financial fraud detection continues to be overlooked by small- to medium-sized businesses, even though they are among the most vulnerable targets. Global SMEs experience a staggering median loss of $141,000 per fraud case. As fraud schemes evolve, it is more crucial than ever to adopt effective fraud protection and prevention strategies.
What is financial fraud detection?
Financial fraud detection is the process of identifying and preventing fraudulent activities within financial transactions or operations. This includes detecting fraudulent transactions, accounting errors, and malicious activities such as cybercrime, identity theft, and employee fraud.
Financial fraud detection systems use various methods, such as data analytics, machine learning, and behavioural analysis to monitor and flag suspicious activities in real time. By analyzing transaction patterns and identifying inconsistencies, businesses can prevent significant financial losses, protect sensitive information, and ensure regulatory compliance.
Common types of financial frauds
Financial frauds come in different forms and need specific measures to be detected and prevented.
| Fraud type | Description |
| Identity theft | Fraudsters use stolen personal data to impersonate individuals for financial gain. |
| Promotional abuse | Exploiting discount codes, referral bonuses, or new customer offers. |
| Payment fraud | Unauthorised use of payment information, including stolen business debit cards or fake transactions. |
| Chargebacks | Customers dispute payments to reclaim funds after receiving goods or services. |
| Fake accounts | Creating multiple or fictitious user accounts to exploit services or manipulate systems. |
| Phishing | Deceptive messages (e.g., emails or texts) designed to trick users into revealing sensitive data. |
| Account takeovers | Gaining unauthorised access to legitimate user accounts, often to steal funds or data. |
amnis – The add-on to your local bank for global payments
As a smart complement to your local bank, amnis provides an all-in-one account for cross-border payments, 0% FX fees, and local IBANs in Switzerland, Germany, the UK, and the US. Multi-currency debit cards and seamless integrations make international spending and accounting effortless.
To keep your finances secure, amnis includes powerful fraud-prevention features:
– Role-based access: separate card admins and users
– Real-time alerts for transactions and logins
– Full control over your multi-currency debit card: block instantly or restrict by country
Identity theft
Identity theft occurs when criminals obtain and use someone’s personal information such as name, address, National Insurance number, or banking details without consent. This information is often used to open bank accounts, apply for credit, or make unauthorised purchases.
Data breaches and social engineering have made identity theft increasingly common. Preventing identity theft requires robust data protection practices, including secure storage of personal information and awareness training to avoid phishing and other social engineering attacks.
Promotional abuse
Promotional abuse involves exploiting marketing campaigns, such as referral schemes, sign-up bonuses, or discount codes, in ways not intended by the provider. Fraudsters may create multiple fake accounts or use automated tools to repeatedly redeem one-time offers.
While this type of fraud may seem minor, it can cause significant financial loss and skew marketing performance metrics. For SMEs, promotional abuse can waste limited budgets and distort customer acquisition data. Preventive measures include setting redemption limits, verifying account authenticity, and using fraud detection tools to monitor abnormal user behaviour linked to promotional campaigns.
Payment fraud
Payment fraud is the unauthorised use of payment instruments such as stolen credit card details or spoofed bank transfers to purchase goods or services. It can also involve invoice manipulation or account hijacking to redirect payments. SMEs are particularly vulnerable due to limited fraud monitoring resources.
Businesses can mitigate these risks through payment verification systems and real-time fraud detection. Educating staff about suspicious transaction patterns and ensuring secure checkout processes are also critical defences against payment fraud.
Chargebacks
Chargebacks occur when customers dispute a card transaction and request their bank to reverse the charge. While legitimate in cases of unauthorised use or unsatisfactory goods, chargebacks are sometimes abused, which is also known as “friendly fraud”. Chargebacks are costly due to lost merchandise, bank fees, and administrative burdens. High chargeback rates may also result in penalties from payment processors.
To reduce chargebacks, businesses should maintain clear transaction records, provide accurate product descriptions, and offer responsive customer service. Fraud prevention tools and secure payment gateways also help that transactions are authorised and verifiable.
Fake accounts
Fake accounts are fraudulent user profiles created to exploit online platforms, often using automated scripts or stolen data. They may be used for various forms of abuse, such as promotional fraud, spam, fake reviews, or social engineering. Fake accounts can undermine marketing efforts and expose systems to cyberattacks.
Financial fraud detection involves revising the account creation process by integrating email or phone verification. Proactively managing user onboarding processes and behavioural monitoring can further limit the damage caused by fake or duplicate accounts.
Phishing
Phishing is a deceptive practice where fraudsters impersonate legitimate entities to trick individuals into revealing sensitive information. This is commonly done via email, SMS, or fake websites. Phishing can lead to credential theft, unauthorised transactions, and data breaches.
Regular employee training, simulated phishing tests, and secure email gateways can reduce the risk. Businesses should also promote a culture of caution where staff are encouraged to verify unexpected or suspicious communications before responding.
Note: 87% of all breaches begin with a phishing attack.
Account takeovers
An account takeover happens when a fraudster gains unauthorised access to a user’s account, often through stolen credentials. Once inside, attackers may make fraudulent purchases, change account settings, or steal sensitive data.
Protecting against account takeovers requires strong authentication practices, such as multi-factor authentication, session monitoring, and tools that identify unusual login behaviour. Educating users about password hygiene and security practices also plays a critical role in financial fraud detection.
Financial fraud detection 2025: From AI scams to fraud as a service
Up to now, financial fraud has evolved rapidly due to technological advancements that have lowered the barrier to entry for cybercriminals. The emergence of Fraud-as-a-Service (FaaS) platforms has democratised cybercrime and enables even individuals without technical expertise to execute complex fraud schemes. These platforms offer ready-made tools and tactics, which makes fraud more accessible and widespread.
Further, artificial intelligence has led to a surge in scams, most notably in the use of deepfakes, which accounts for 7% of global fraudulent activity. This technology is employed to create convincing fake identities, manipulate biometric verification systems, and impersonate individuals.
These developments underscore the necessity for businesses to adopt advanced, AI-powered fraud detection systems capable of analysing and responding in real-time.
Best practices for fraud detection in 2025
As fraud schemes become more sophisticated, businesses must adopt equally advanced fraud detection tools. Combining these methods creates a layered, proactive defence against evolving fraud threats:
- AI and machine learning: AI and machine learning systems can analyse vast amounts of data to detect anomalies in real time. They identify subtle patterns and adapt to emerging fraud techniques by learning from past incidents.
- Deepfake detection: With the rise of synthetic identity fraud, deepfake detection software now integrates with KYC platforms to flag manipulated media during onboarding and verification.
- Pre- and post-transaction monitoring: Real-time analytics track user behaviour before, during, and after a transaction. Unusual activity such as IP changes, erratic mouse movements, or inconsistent device usage can trigger automatic reviews or block transactions.
- Risk-based authentication: Adaptive authentication adjusts security requirements based on the risk level of each session. For example, high-risk logins may require additional biometric checks, while low-risk ones allow easy access.
- Cross-channel user profiles: Linking customer behaviour across devices and platforms provides a holistic view. This helps identify suspicious inconsistencies, such as someone logging in from two countries within minutes.
- Leverage external data: Incorporating third-party intelligence such as blacklists, device reputation, and threat feeds strengthens fraud scoring and allows for better-informed decisions.
How AI is changing fraud detection in financial services
AI-driven fraud detection offers SMEs cost-effective, scalable protection without the need for large in-house teams. Traditional rule-based systems are often rigid and neglect subtle or novel fraud patterns. In contrast, AI excels at processing massive, complex datasets in real time, which helps spot anomalies and behavioural deviations that human analysts or static algorithms might overlook.
Machine learning models are trained on historical data to recognise both known fraud tactics and evolving ones. As new data flows in, these models continuously refine their predictions to reduce false positives and improve accuracy. Further, AI also supports advanced behavioural analytics, risk scoring, and customer profiling.
Financial fraud detection regulations: EU, US and APAC
In response to financial fraud, regulatory bodies across the European Union, US, and APAC region have implemented stringent measures to safeguard financial systems.
EU
The EU has established comprehensive frameworks to combat financial fraud, notably through the Sixth Anti-Money Laundering Directive (6AMLD) and the Revised Payment Services Directive (PSD2). 6AMLD expands the scope of money laundering offences and introduces tougher penalties, while PSD2 mandates Strong Customer Authentication (SCA) to secure electronic payments. Additionally, the General Data Protection Regulation (GDPR) enforces strict data protection standards, which determines how financial institutions handle personal data in fraud prevention efforts.
US
In the US, the regulatory landscape is shaped by the Bank Secrecy Act (BSA) and the USA PATRIOT Act, which require financial institutions to implement robust Anti-Money Laundering (AML) programs and report suspicious activities to the Financial Crimes Enforcement Network (FinCEN). The emphasis is on a risk-based approach, with institutions expected to employ advanced technologies to detect and prevent fraudulent activities effectively.
APAC
The APAC region presents a diverse regulatory environment, with countries like Singapore and Australia leading in the adoption of advanced fraud detection measures. Singapore’s Monetary Authority of Singapore (MAS) has introduced initiatives promoting real-time fraud detection and data sharing among financial institutions. Similarly, Australia’s Australian Transaction Reports and Analysis Centre (AUSTRAC) enforces stringent AML/Counter-Terrorism Financing (CTF) regulations, which encourages the use of technology-driven solutions to combat financial fraud.
Common challenges of fraud detection
Despite technological advancements, fraud detection remains a complex task due to several ongoing challenges:
- Data privacy regulations: Laws such as the GDPR and other regional frameworks restrict how organisations collect, store, and process user data, which makes it harder to track fraud across jurisdictions.
- False positives: Overly sensitive systems often flag legitimate transactions as suspicious, which leads to customer frustration, operational delays, and lost revenue.
- System complexity: Modern fraud schemes span multiple channels and use methods that require integrated systems capable of real-time analysis and cross-platform monitoring.
Financial fraud detection vs. fraud prevention
Fraud detection and fraud prevention serve different, yet complementary roles in protecting financial systems. Fraud detection focuses on identifying suspicious activity after it occurs with tools like AI, transaction monitoring, and behavioural analysis to catch possible frauds. It’s reactive by nature and critical for minimising damage.
In contrast, fraud prevention is proactive. It aims to stop fraud before it even happens by putting safeguards in place. This includes budget limits, user permissions, card controls, and real-time alerts to reduce exposure to risk from the outset.
For SMEs, prevention is often more cost-effective than relying solely on detection. Modern payment providers integrate preventive features such as budget control, card blocking, and transaction transparency, which enables businesses to reduce risk without expensive, complex infrastructure.
amnis: Your secure financial ecosystem
As a Swiss-based financial provider, amnis offers a platform to cut international transaction costs while maintaining high security standards. Built with safety in mind, the platform includes key features such as Two-Factor Authentication (2FA), 3D Secure (3DS) for online payments, and the ability to separate card administrators from users – ensuring clear roles and reduced risk.
To help you stay informed and in control, transparent email notifications are sent for every transaction, along with alerts via email and mobile app when logins occur from new devices. If needed, multi-currency debit cards can be blocked or disabled instantly. You can also restrict card usage to specific countries to prevent misuse when the card is not in use abroad.
For more best practices, visit our FAQ on account security.
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