Account takeover fraud is now considered one of the most serious security threats for companies. On this journey, where companies are going online, cybercriminals take advantage of the user’s account. This is where the financial loss, reputational losses, and trust breaches can be taken advantage of by malicious criminals for monetary gain. Understanding Account Takeover Fraud and preventing it is essential for any company involved in customer accounts.
Account takeover fraud occurs when a fraudulent actor gains unauthorised access to a legitimate user account, which is then used for harmful reasons. Account Takeover Fraud differs in that, unlike accounts that are never created, it exploits already existing trusted accounts, making it even more deadly. After entering the user’s account, an intruder can take money, make unauthorised purchases, or enter sensitive information in addition to using such an account to perpetrate extra malicious actions. The compromised accounts seem genuine to security systems, so scammers can operate undetected for years.
When it comes to account takeover fraud, that process is multi-stage. Phishing campaigns, data breaches, credential stuffing attacks, malware, and purchasing stolen credentials from dark web marketplaces are commonly the vectors by which thieves first get user credentials. An attacker begins its login process with one or more stolen credentials after gaining access and later logs in with self-administered automation. Using a variety of tools, the stolen credentials are tested across multiple platforms after logging in to their accounts. The criminals collect all of these credentials and use the information acquired for reconnaissance to appreciate different aspects of their account’s value and security measures. All of this information, including passwords, email addresses, and phone numbers that are essential to their operation, is changed in order to keep control and shut out legitimate users. Eventually, once full control is established, the fraudsters take advantage of the account via unauthorised purchasing, transfers of funds, or digging up more personal information.
The use of lists of stolen credentials to automate and attempt to log in through multiple platforms is one example of password reuse.
Phishing-based ATO involves social engineering to persuade users to provide credentials through convincing fake sites or emails.
SIM swapping allows phone fraudsters to persuade mobile carriers to transfer a victim’s cellular phone number to their SIM card, bypassing SMS-based authentication.
Brute force attacks systematically try various passwords in an effort to find the correct one.
Social engineering ATO uses specially designed cases to entice customer service representatives or users into revealing access for certain reasons.
Identity fraud uses personal information. It’s a different matter than account takeover fraud. Identity fraud takes the identity of a person, using their personal information as the basis for opening new accounts or claiming their own name, requiring huge personal data such as Social Security numbers and birth dates. Account takeover fraud attacks existing accounts, playing on the established trust and history of existing accounts. At the entrance stage, Account Takeover Fraud fraudsters don’t even have to pass through proper identity verification to compromise a genuine account — they just steal access to legitimate accounts. The point of view is critical: Identity fraud occurs at account creation, while Account Takeover Fraud acts on existing accounts, and thus requires different methods of prevention.
Direct access to funds increases risk for financial institutions. Account Takeover Fraud occurs when e-commerce establishments experience unauthorised purchases using stored payment methods. Payment processors and digital wallets are targeted because of their role in financial transactions. Social media and email platforms are gateways to other accounts that need to be crossed. Healthcare organisations hold sensitive information such as medical records and payment records. As digital assets are becoming available at an inflated market value, cryptocurrency exchanges are becoming critical targets with the irrevocability of cryptocurrency transactions making the cost of ATO fraud, particularly that of a cryptocurrency account, prohibitive.
Problems such as unusual logins from unknown geographic locations, uncommon machine/device types, deviation from typical time-of-day access patterns, or multiple fast login attempts might signal a compromise. Sophisticated monitoring also indicates speed of logins, being able to tell when credentials are being used across a range of sites at once.
Fraudsters change account details in order to gain access to account information to stay in control. Red flags range from unauthorised modifications to email addresses, phone numbers, security questions, adding different payment methods, and changes to notification preferences to obfuscate fraudulent activity.
Transaction monitoring observes purchases which indicate abnormal buying behaviour not in line with typical user behaviour. Warning signs can include rapid and successive purchases, attempts to max an account balance, purchases from unfamiliar merchants, and immediate withdrawal or transfer of funds.
User reports are dependable signs of account takeover. Reports from customers contacting support about unexpected transactions, loss of account access, or receiving unfamiliar notifications are the best signals for an immediate investigation.
Direct monetary injury comprises stolen funds, unauthorised purchases, chargebacks, expenses to investigate the fraud, legal assistance, customer reimbursement, and increased insurance premiums. This usually leads to expenses several multiples higher than the original stolen amount.
Reported ATO incidents can damage brand reputation. Customers expect organisations to manage their accounts. High-profile breaches undermine consumer confidence and result in customer churn much longer than they should, after security issues have been resolved.
Organisations could face lawsuits from affected customers claiming negligence. Violations against data protection and financial regulations mean fines from regulatory bodies. Without proper use of security precautions, enforcement actions or huge fines can be issued.
Consistent erosion of customers’ trust undermines behaviour, decreases engagement with digital services, and reduces the likelihood of providing more information. Rebuilding trust is hard to accomplish without ongoing work, open, honest communications, and showing a commitment to fraud prevention.
Based on this, the risk-based authentication system dynamically adjusts requirements based on the assessment of new conditions and vulnerabilities in real time. The model considers a variety of factors, including device, location, network features, user actions, and context for transactions. Scenarios with low risk have minimal friction, and high-risk attempts are confirmed with more verification. Through RBA, systems are continually learning from new data to adjust their risk models to enable the identification of new types of threats.
Biometric authentication is based on your unique physical attributes (fingerprints, facial recognition, iris scanning, voice recognition). They even offer harder to copy and steal authentication elements, which make them resistant to credential stuffing. Most modern systems use liveness detection to curb spoofing efforts.
Multi-factor authentication asks users to provide multiple forms of verification — something the user knows, has, and is. One-time-only, time-based passwords, push notifications, hardware-based security keys, and SMS codes are typical examples of MFA deployments. High-value transactions and sensitive account changes need MFA, and organisations need to mandate it.
Behavioural biometrics focus on detecting patterns in behaviour as users interact with devices, creating unique profiles driven by their typing rhythm, mouse movement patterns, touchscreen interaction and navigation habits. This technology runs around the clock during user sessions and offers a continuous authentication process. Disconnecting from familiar habits causes alarms — or other validation.
By assessing large datasets of user behaviour and transaction histories, machine learning algorithms detect complex patterns that suggest potential fraudulent activity. These evolving, adaptive systems evolve with fraud manoeuvres, so detection accuracy improves with lower false positive rates. Scoring up to date in real-time provides the ability to assess risk instantly for automated response.
Device Fingerprinting provides unique identifiers and is capable of scraping the operating system, browser version, screen resolution, and hardware from devices to create unique identifiers. When users log in from non-identifiable devices, the systems activate extra authentication. It aids in identifying credential stuffing attempts and tests of automated bot security.
IP geolocation monitors where access attempts come from geographically to detect impossible travel scenarios or points of entry from high-risk areas or VPN services. When combined with historical users’ behaviour, this generates great signals of potential exploitation. Nevertheless, IP data must be combined with other risk signals for an accurate threat assessment.
The Payment Card Industry Data Security Standard makes provisions for tight access controls, encryption, regular security tests and a comprehensive set of policies for organisations working within payment card space. The conditions include multi-factor authentication for remote access, user account management policies, logging, and monitoring access and regular security testing.
The General Data Protection Regulation mandates necessary technical security and organisational approaches to safeguard personal data. Account takeover events are data breaches that must be notified within 72 hours. Without balancing the privacy considerations against fraud prevention, organisations need to prove that they have adequate measures to ensure security to avoid large penalties.
In recent years, regulators have also offered guidance on how to build this toolkit: The Federal Financial Institutions Examination Council emphasises risk-based authentication, layered security, customer education and incident response planning. There must be account validation to address risks and tracking of suspicious activity.
Account takeover fraud means vigilance at all times and the right prevention tactics, in a much more sophisticated way than security at all times. This means implementing sophisticated authentication technologies, continuous monitoring, the use of machine learning for detection, and continuous user education. Security has to be used in a way that neither impedes the legitimate users nor prevents fraud. Organisations are increasingly held accountable in a regulatory environment, and compliance is a business requirement: as fraud develops, organisations should adapt their security practices that leverage emerging technologies. Investing in strong fraud prevention pays dividends: greater customer trust, less loss, and greater regulatory compliance.
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