The clock is ticking: Financial cyberattacks are more dangerous than ever

The stakes have never been higher. Whether it’s billion-dollar crypto heists or employees leaking sensitive data, financial institutions must act now.

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Joe Leung

May 02, 20252 min read

Image of a banker and a threat hunter assessing a potential financial cyberattack.

In February 2025, Bybit, a major cryptocurrency exchange, suffered one of the largest heists in digital finance history. Hackers stole $1.5 billion in Ethereum by exploiting security. While this attack was external, the financial services industry faces an even greater threat—insider-driven breaches.

In recent months, malicious insiders have been caught selling confidential bank client data, leaving customers vulnerable to fraud and identity theft. Even government institutions aren’t safe, as seen in the CFPB breach where an ex-employee illegally transferred the personal data of over 250,000 consumers.

Insider threats: a growing concern

Unlike external cyberattacks, insider threats are harder to detect because they come from employees or contractors who already have access to sensitive systems. According to Verizon’s 2023 Data Breach Investigations Report, insider threats now account for three out of every four data breaches.

The financial sector is particularly vulnerable:

  • The average data breach cost in financial services rose to $6.08 million in 2024, up from $5.90 million the previous year (Statista, Cost of data breaches in financial industry worldwide, 2024).
  • 64% of financial firms have more than 1,000 sensitive files accessible to every employee (Varonis, 82 Must-Know Data Breach Statistics, 2024).
  • Cybersecurity talent shortages have hit a record 4.8 million unfilled positions, weakening financial institutions’ ability to detect insider threats (ISC2, Growth of Cybersecurity Workforce Slows in 2024 as Economic Uncertainty Persists, 2024).

The solution: AI-powered behavioral analytics

Traditional security tools often fail to detect insider-driven breaches, leaving financial institutions exposed. OpenText Core Threat Detection and Response provides an AI-powered, behavioral analytics-driven solution to proactively detect and mitigate these threats before they escalate.

With features like unsupervised machine learning-based anomaly detection, behavioral risk scoring, and seamless integration with Microsoft Defender for Endpoint, Microsoft Entra ID, and Microsoft Copilot, OpenText helps financial organizations automate threat hunting and detect insider and other elusive threats in days instead of months, reducing the cost and damage of breaches.

Don’t wait for the next breach

The stakes have never been higher. Whether it’s billion-dollar crypto heists or employees leaking sensitive data, financial institutions must act now. We’ve got you covered with our latest guide to AI-powered threat detection and response in the financial services industry. Learn how you can elevate your organization’s defense against unknown threats posing some of the biggest cybersecurity challenges.

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Joe Leung

Joe Leung is the product marketing director for OpenText Cybersecurity’s Threat Detection and Response portfolio. Prior to this role, he was the AI product marketing manager focused on use cases for unstructured data analytics. One of the key use cases was converged security.

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