Cybercriminals are easily attracted to the trillions of dollars in assets and sensitive data stored by the financial sector.

The number of cyber threats continues to grow, and so do the financial losses suffered in each attack. 

Keep reading to learn about the biggest cybersecurity risks in this industry and the tools financial institutions can use to stop them.

Top Stats About Cybersecurity in the Finance Space

Cybersecurity Threats and Risks for Financial Organizations

The combination of direct access to sensitive data and the potential for large payouts makes the financial sector an attractive target for all types of cybercriminals. 

Here are some of the most common and costly cybersecurity threats in the industry.

Rapidly Advancing Tech Stacks

Nearly all financial institutions are adopting new tech solutions like cloud computing, digital identity architecture, 

and AI. This opens a plethora of new vulnerabilities and entry points for cybercriminals.

One survey found that more than 80% of banks use some type of AI technology, but only 11% have strong, trustworthy AI practices in place. In fact, securing AI technology against cyber threats didn’t even rank among the top five implementation priorities.

Third-Party Software Providers

Third-party vendors and software supply chains are another avenue that hackers can use to access financial systems. Criminals can insert malicious code into the software, harvest credentials, or exploit misconfigurations in a vendor’s servers. 

For example, in a 2024 cyberattack, hackers broke into a database held by a third-party vendor and stole sensitive data from Santander, the largest bank in Spain. Data from more than 30M customers was compromised.

In addition, many IT vendors work with multiple financial institutions, enabling hackers to impact numerous organizations with a single attack. 

This occurred in the summer of 2025 when both UBS and Pictet, two Swiss banks, suffered data breaches because of an attack on Chain IQ, a third-party procurement service provider.

Sophisticated APT Groups

Advanced persistent threat (APT) groups are well-funded, politically motivated “hacktivists.” They’re especially attracted to the financial sector because of the potential for large-scale theft and strategic disruption. 

Banks around the world, as well as the U.S. Department of the Treasury, have reported APT attacks in recent months.

Between April 2024 and April 2025, one APT group targeted 34 financial organizations, and another group attacked 29 businesses in the sector.

Compliance Requirements

Financial institutions are required to comply with several regulations regarding the protection of consumer data and financial information. They’re also required to follow specific guidelines regarding when and how they report a cyberattack. 

Failing to follow these regulations can result in huge penalties, as was the case for US-based Flagstar Bank in 2021. The SEC fined the bank $3.5M because it misled customers and investors regarding the seriousness of a data breach. 

Lack of Skilled Staff

For the amount of risk they face, banks and financial institutions don’t have adequate cybersecurity coverage.

On a global scale, nearly 70% of organizations report having a moderate-to-critical lack of cybersecurity expertise.

Financial services organizations rank as one of the top four sectors suffering from the cybersecurity workforce shortage.

When looking at just the financial sector, one survey found that more than 30% of companies are not confident that they have the resources necessary to mitigate cyber risks.

Cybersecurity Tools for Financial Services

Nearly 90% of financial services professionals say their business is planning to increase cybersecurity spending in the next 24 months. But what tools and strategies will make the most impact? 

Here are the best practices for today’s financial institutions.

Identity and Access Management

Banks and other financial organizations should put strict identity and access management (IAM) policies in place, including multi-factor authentication, single sign-on, and biometrics. This applies to both internal and external user identities. This ensures that only the proper people have access to sensitive data. 

Studies show that financial organizations that deploy IAM solutions save up to $223K annually. 

“Never Trust” Policies

Financial institutions should implement a zero-trust network access (ZTNA) approach. 

Unlike a traditional VPN that trusts everyone who is inside the network, ZTNA operates on “never trust, always verify” principles. It assumes that all users and systems need to be continuously verified at any access point.

Next-Generation Firewalls (NGFWs)

NGFWs go beyond traditional firewalls to protect the network perimeter in several ways. 

Web Application Firewalls (WAFs)

A WAF works like a reverse proxy to protect web applications from malicious internet traffic and prevent attacks like cross-site scripting and SQL injection. 

WAFs are rules-based. They can operate on a blocklist or allowlist model or a combination of both. Some WAFs have machine learning capabilities and can update policies automatically as threats evolve.

Financial institutions, many of which rely on online portals and mobile banking APIs, should view WAFs as an essential cybersecurity tool, but adoption is too low, experts say. One recent survey found that more than half of external enterprise assets lack WAF protection.

Advanced Threat Protection (ATP) Solutions

ATP systems are suites of tools that combine several types of cybersecurity technology.  These systems continuously monitor activity and respond to threats in real time. Email protection, endpoint monitoring, network security, and cloud security could all be included in an ATP bundle for a bank or other financial organization.

ATP uses advanced behavior analytics, along with machine learning technology, to automatically recognize anomalies. The system also analyzes potential threats to look for malicious code and known threat signatures. It may even isolate the threat in a sandbox environment in order to perform additional analysis.

Once a threat is recognized, ATP systems automatically contain it and block it before it causes any damage or spreads throughout the network.

Vendor Risk Management

Specific IT staff should be dedicated to developing a vendor risk management program. 

The cybersecurity practices of each vendor should be assessed in detail at the outset of the contract. This includes reviewing certifications, like SOC 2 and ISO 27001. It also includes a thorough discussion of which entity is in charge of data protection at various points in the data pipeline and who is responsible for offboarding clients or employees. The vendor’s incident response, data recovery, and cyberattack notification procedures should also be specified.

Contracts should include security requirements and right-to-audit clauses for additional protection.

Ongoing risk assessments, vulnerability scans, and system audits should be used to monitor risk throughout the lifetime of the contract. 

Deepfake Detecting Tools

The number of deepfake attacks on banks grew by nearly 250% last year, and human reasoning alone isn’t enough to fight these attacks. Financial organizations need to deploy AI models specifically trained on deepfake detection.

These specialized AI tools work in real time to scan voices and videos for deepfake signs like mismatched lips, odd microbehaviors, and shifts in tone or speed. 

Employee Training

Financial employees are often the weakest link in a cybersecurity strategy. Last year, 55% of social engineering attacks against financial institutions were successful. 

Offering frequent bite-sized training and education to employees typically works better than once-a-year sessions. For organizations with a larger budget, human risk management platforms provide online personalized training and phishing simulations for employees.

Metrics and Reporting

With all cybersecurity tools and strategies, tracking metrics is essential. These metrics may be required for compliance reporting, and they’ll also provide accountability to boards of directors and other stakeholders. 

Because nearly 60% of consumers are concerned about the security of their data, tracking metrics will also provide a degree of transparency to the public.

The Impact of AI in Financial Cybersecurity Strategies

AI is a double-edged sword for financial organizations that want to strengthen their cybersecurity efforts. 

AI tools can vastly increase the speed and scale of threat intelligence and protection, but hackers are also using AI to bolster their attacks. 

AI-Powered Cyber Threats

Phishing is one of the most common ways cybercriminals are using AI to gain access to private systems in the financial sector. 

Since “black hat” AI became available around 2021/22, phishing attacks have grown by nearly 1,200%. Now, roughly 82% of phishing emails use AI in some form. 

Beyond phishing, cybercriminals are using AI to impersonate job applicants. Once they get hired, they install malware or use other tactics to steal sensitive data and assets. Reports show that 12% of these incidents occur in the financial sector. That’s second only to the software engineering industry.

Finally, cybercriminals may attempt to manipulate or corrupt the AI systems being used by financial institutions. This is referred to as “data poisoning.” These attacks are often so stealthy that they go unnoticed for months or longer.

Changing just 0.001% of an LLM’s training data can drastically influence its performance. In the financial sector, this can lead to the approval of fraudulent applications or transactions, flawed risk assessments and portfolio management, and violations of fair lending regulations.

Using AI to Improve Cybersecurity

One of AI’s main strengths is analyzing vast amounts of data, and that makes it the perfect tool for financial cybersecurity. AI-enabled tools can scan through massive amounts of internal and external data, spot unusual behavior, and uncover malicious patterns.

AI-powered solutions can also analyze threats and prioritize the most critical risks, which makes it up to 55% faster to investigate and triage an alert. This minimizes false positives and allows low-risk threats to be automatically remediated, a feature that can take pressure off understaffed IT teams at financial organizations.

AI systems are also capable of forecasting future cyber risks and threats. Because models can analyze historical data and incidents, as well as real-time threat information, they can predict future attack strategies and alert IT teams to vulnerabilities.

Bank of America: A Financial Cybersecurity Case Study

Bank of America has repeatedly fallen victim to cybersecurity attacks orchestrated through third-party vendors.

One of the most notable occurred in late 2023 when a ransomware attack group gained access to Bank of America customer data through an SaaS product provided by Infosys McCamish Systems. The attack occurred on November 3, but Bank of America wasn’t notified until November 24. Customers were notified on February 2.

The data breach impacted more than 57K Bank of America customers and included names, addresses, birth dates, social security numbers, and passwords.

Infosys McCamish Systems hired forensic IT experts to determine the extent of the incident and the weaknesses that led to the successful attack. 

Bank of America offered two years of identity theft protection services for affected customers. 

Still, the bank received its fair share of bad press for the incident. Individuals, as well as governing bodies, were especially alarmed at the length of time that passed before the bank notified customers.

Conclusion

Cybersecurity in financial services doesn’t just protect assets and data. It safeguards the stability of the global economy. 

By deploying the right tools, organizations can uncover weaknesses and strengthen their cybersecurity strategy with a multi-layered approach. Investing in strong cybersecurity will enable financial institutions to provide stability and transparency for regulators as well as consumers.