Social engineering in banking: Detecting Account and Device Takeovers before money moves

Online banking has made life easier, but it has also made social engineering a prime weapon for fraudsters. Instead of breaking through technical defences, attackers now target something far more vulnerable: people.

Social engineering attacks manipulate emotions like fear, urgency, or trust to trick victims into giving up credentials, approving transactions, or downloading malware. The result? Compromised accounts, hijacked devices, and financial losses that traditional security tools often fail to prevent.

This article looks at the most common types of social engineering attacks, how they target online banking, and what you can do to spot and prevent the fraud that often follows.

Social engineering attacks are attempts to manipulate individuals into divulging sensitive information or performing actions allowing attackers to complete the fraud. 

Social engineering is not per se a way to complete fraud, but it opens the doors to fraudsters to perform Account Takeovers. As explained in our previous article, “Online banking fraud: what it is and how to prevent it”, an Account Takeover (ATO) happens every time a cybercriminal takes over an online account to steal information or money. 

This is where fraud happens. 

The latest large-scale attack in the banking industry dates back to 2022, when a broad social engineering campaign run by Brazilian criminals targeted bank users in Portugal, Spain, Brazil, Mexico, Chile, the UK, and France.
Over the years, cybercriminals have carefully transformed their techniques from simple and easily detectable tactics, like impersonation, to complex psychological manipulations, making the impact of fraud on mental health a growing social issue. 

As social engineering scams in online banking continue to grow, we will focus only on the most common scenarios to help banks detect and prevent them.

Phishing, smishing, vishing 

The most dangerous and widespread social engineering attack is phishing, where cybercriminals masquerade as trustworthy entities to deceive unsuspecting victims via emails, text messages (smishing), or phone calls (vishing).

Phishing attacks can be highly convincing, imitating the official logos, email templates, and language of reputable banks or organisations to trick users into divulging sensitive information, such as login credentials or credit card details, by clicking on a malicious link or replying to the message. 

Once obtained, this information can be used for fraudulent transactions, unauthorised access, or identity theft. 

Spear phishing

Spear phishing targets specific individuals inside organisations, as their successful infiltration can lead to more significant financial gains for the attackers. For this reason, it is more dangerous and difficult to detect than general phishing scams. 

This type of social engineering attack is highly used in online banking. 

Baiting

Baiting attacks exploit human curiosity by luring people into traps disguised as attractive offers.

Victims are enticed with something seemlingly value, such as free software, exclusive discounts, or irresistible deals containing malware-infected links or downloads. Once clicked or installed, cybercriminals gain access to sensitive data. 

In online banking, baiting attacks can compromise login credentials, granting attackers unauthorised access to user accounts and facilitating fraudulent transactions.

Pretexting

In pretexting attacks, cybercriminals assume false identities, often posing as trusted individuals or authorities, to trick victims into revealing confidential information.

Scammers may pose as authoritative figures, such as bank representatives or IT support personnel, and manipulate victims into providing personal or financial data. 

Pretexting attacks can compromise online banking security by exploiting trust and authority, leading to unauthorised access and financial losses.

Pharming

Pharming attacks redirect victims to fake websites resembling legitimate online banking platforms. 

By exploiting vulnerabilities in DNS servers or injecting malicious code into users' systems, cybercriminals misdirect victims to fraudulent websites, where they unknowingly provide their login credentials and other sensitive information. 

Pharming attacks can lead to unauthorised access, identity theft, and financial fraud.

Artificial intelligence has elevated social engineering to new levels. Deepfake voices, realistic chatbots, and personalised messages make it nearly impossible to distinguish real from fake. Fraudsters can convincingly impersonate bank representatives, friends, or even family members in real-time.

Audio deep fake is extensively used to complete Authorised Push Payment fraud, a specific type of social engineering attack that tricks customers into making payments to fraudsters’ banking accounts. 

This new wave of “AI-driven social engineering” demands equally intelligent countermeasures.

As AI advances, security professionals and online users must stay vigilant and employ robust countermeasures to protect against these evolving attacks.

Social engineering attacks have profoundly impacted online banking fraud, resulting in significant financial losses and compromised customer trust. ‍

When attackers access victims' credentials through social engineering, they can transfer funds, make fraudulent payments, and carry out other unauthorised transactions, causing financial harm to individuals and institutions. 

Social engineering attacks often involve collecting personal information. Attackers can use this information to create fake identities, open fraudulent accounts, and commit identity theft, leading to long-term consequences such as damaged credit scores and reputations. 

Additionally, successful social engineering attacks erode customer trust in online banking systems. Instances of fraud and unauthorised access can make customers question the security measures in place, potentially resulting in customers abandoning online banking services altogether.

Cleafy takes a proactive stance against social engineering by monitoring how users interact with their online banking environment — not just what they do.

• Session-level behavioural analysis detects unusual activity patterns that reveal early signs of manipulation or remote access.
• Adaptive automation continuously adjusts detection and response based on evolving behaviours, minimising false positives while improving accuracy.
• Device and network intelligence helps identify compromised environments, even if login credentials appear valid.

By analysing live sessions and behavioural context, Cleafy can spot account or device takeover attempts up to 15 days before any fraudulent transaction occurs. This early warning reduces financial exposure and allows fraud teams to act decisively before funds are at risk.

Every alert matters, but an excess of false positives can slow teams down and obscure real threats. Cleafy’s adaptive detection framework intelligently prioritises high-risk sessions, ensuring fraud and SOC teams spend time where it counts most.

By filtering out noise and surfacing only relevant alerts, banks can achieve:

• Faster investigation cycles, thanks to streamlined triage and contextual insights that highlight the highest-risk sessions first.
• Fewer manual reviews, as automation reduces the need for human intervention in low-risk or repetitive cases.
• Lower operational strain, freeing fraud and SOC teams to focus on strategy, investigation, and prevention rather than constant firefighting.

In short, Cleafy doesn’t just detect fraud earlier — it helps teams work smarter, not harder.

No system is immune to manipulation, but understanding and anticipating human-centred attacks makes all the difference. By combining continuous monitoring, behavioural analytics, and automation, Cleafy helps banks turn reactive fraud prevention into proactive fraud prediction.

Social engineering will continue to evolve, but with early detection and more intelligent automation, it doesn’t have to win.