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Abnormal for Financial Services

Discover the AI-based email security platform that protects financial institutions from the full spectrum of email attacks.

Key Insights

Financial institutions were the most targeted industry for phishing in 2022, with a 70% weekly probability of facing a BEC attack.

BEC and invoice fraud are engineered to bypass secure email gateways, exposing firms to breaches, financial loss, and compliance violations.

Manual threat response strains fraud and cybersecurity teams, diverting focus from other critical security issues.

Abnormal detects threats within active conversations using thousands of identity, behavior, and content signals—catching what legacy systems miss.

Data, Reputation, and Revenue at Risk

According to the Anti-Phishing Working Group (APWG), financial institutions were consistently the most targeted industry for phishing attacks in 2022. Further, financial organizations had a 70% probability of being targeted with a business email compromise (BEC) attack every week last year.

Additional Layers of Defense are Necessary

Advanced email threats like BEC and invoice fraud are built to evade secure email gateways. These threats are increasing and put financial services organizations at risk for data breaches, financial losses, compliance violations, and loss of trust. Responding to advanced threats manually puts stress on fraud and cybersecurity teams and takes their focus away from other security issues.

Modern Email Security for the Financial Sector

Abnormal’s cloud-native solution quickly integrates with Microsoft 365 and Google Workspace, using thousands of signals across identity, behavior, and content to separate legitimate messages from dangerous threats. Because Abnormal recognizes anomalies even in ongoing conversations, it immediately detects and remediates threats that legacy systems miss—keeping financial institutions safe from attacks.

Abnormal for Financial Services 2025

See Abnormal in Action

See how behavioral AI detects the attacks that legacy defenses miss.