Cybersecurity in Banking – Top Security Threats and How to Mitigate Them
Since the start of the Covid-19 pandemic, cyber threats have increased and become more complex in every area of cybersecurity: data leaks, phishing emails, malware, account takeovers, and more.
As organizations grow and further develop their digital-first strategy, staying secure online has never been more critical.
And the biggest and best banking institutions are no exception to this.
In this article, we’ll take a look at the importance of cybersecurity in banking, the biggest threats banks are facing right now, and how these threats can be mitigated. We’ll touch on the digital transformation banks to adopt artificial intelligence (AI) and machine learning (ML) into their processes and systems.
Why Is Cybersecurity So Important in the Banking Industry?
Customer Retention and Reputation
Reputation is everything in business, especially for banks that are handling their customers’ livelihoods, savings, and credit.
Once a customer has lost trust in a bank, they are going to look elsewhere, with 76% of people saying they are likely to take their business somewhere else due to negligent data handling.
This leaves banks vulnerable to losing out to competitors and in severe circumstances can lead to a run on the bank.
Breaches Cost Time and Money
Cybersecurity breaches in the banking sector are costly, to say the least. According to IBM’s Cost of a data breach 2022 report, the financial industry had the second-highest average cost per breach.
The report claims that the average cost of a security breach in the financial sector is $5.97 million.
Examples of Cybersecurity Incidents in Banking
In 2020, one of the largest banks in the United States had to notify more than 1.5 million customers that their social security number had been stolen in a data breach.
This resulted in the customers bringing a lawsuit against the company, costing the bank a total of $5.9 million to settle in 2021.
In 2021, Robin Hood experienced a data breach in which the personal information of 7 million customers was compromised. More than 5 million customer email addresses and 2 million customer names were stolen.
The stock of the company fell 3.8% in just 1 day following the announcement.
Top Cybersecurity Threats in the Banking Sector
Spoofing is an act in which a hacker impersonates a bank to contact customers via email, phone, or SMS, in an attempt to coerce users into handing over sensitive information such as their passwords and card details.
A cybercriminal would target bank users by creating a spoof website, replicating the bank’s official website. By sending a spoof email or text message that appears to be from the bank, they can direct unsuspecting customers to the hoax website.
A user accessing the website would be none the wiser that the website was tracking their keystrokes, giving the scammer access to their password and card credentials.
Phishing is a form of spoofing whereby the fraudster sends emails pretending to be from a reputable company in order to coerce individuals into revealing personal information such as passwords of credit card numbers.
Similar to the above, a cybercriminal would send emails that appear to be from a bank with malicious links in an attempt to obtain the individual’s personal or business credit or debit card details.
Malware is software specifically designed to damage or gain unauthorized access to a computer system.
Cybercriminals use spoofing techniques to trick users into clicking malicious links that plant malware onto their system to steal the sensitive information of that individual or data held by the whole organization.
4. The Use of Unencrypted Data
Unencrypted data is ‘easy to read’ information. Opposed to encrypted data that is translated into another form, or code that only people with access to the key can read.
Banks using unencrypted data are ‘easy targets’ for cyber criminals and highly vulnerable to cyber-attacks.
5. Data Manipulation
There are numerous reasons a fraudster may attempt to hack into a system and alter the data. For example, they may alter their interest rate – lowering it to reduce their monthly payments or manipulate the amount of payments made so that there’s more money in their account.
What Can Be Done to Diminish These Threats?
AI and Automation
Artificial intelligence in cybersecurity is on the rise and has significant benefits in the banking industry.
A report from IBM explains that companies with a fully developed AI and automation program were able to identify and contain a breach 28 days faster than those that didn’t. The result is an average saving of $3.05 million.
It should also be noted that organizations with partially developed AI programs also had significantly better results than those with no AI and automation programs in place.
Multi-factor authentication backed by artificial intelligence requires a user to provide two or more verification factors before they can access their account.
The required verification factors will usually be made up of a password and one of the below:
- SMS verification
- Biometric ID such as fingerprint or face ID
- A 3rd party authenticator app such as Microsoft authenticator
Biometric data in particular is extremely difficult for hackers to replicate in order to breach a user’s account.
Increase Consumer Awareness
Ensuring that bank customers are aware of the potential threats that are out there, how to spot them, how to avoid them, and where to report them is vital to maintaining security.
Processes such as enabling users to validate emails they’ve received by viewing them within their accounts is just one way to give more power to banking customers to control their own safety.
Legitimate communications from banks should always include messages such as “we will never ask you to enter your login details via email or text” to remind customers to be vigilant at all times.
Anti-malware programs are designed to protect whole systems and individual components from malware or malicious software.
However, traditional malware programs known as signature-based detection can only detect known threats.
That’s why digital transformation and the adoption of AI and ML-based detection methods is critical to detecting unknown threats by scanning software to search for certain characteristics, not signatures.
Customer profiling works by building purchaser profiles and models for ‘normal’ employee behavior to identify abnormal system behavior.
This is enabled by ML models that analyze customers banking related transactions such as:
- Monthly cash flows
- Spending habits
- Credit history
- Financial and household information
- And many more
The models analyze all transactions in real-time to determine if they should be blocked and flagged as suspicious or normal customer behavior.
Similar to customer profiling, ML models are used to build profiles on employee behavior.
Any abnormal behavior such as clicking suspicious links or downloading software can be flagged immediately to IT teams with a security rating.
Despite mounting cyber threats, a cross-industry study found that only 30% of companies had cyber insurance.
However, with the potential financial implications to organizations such as banks, who are responsible for such staggering amounts of sensitive information, cyber insurance is absolutely essential to offset any financial losses caused by a cyber attack.
For more information on how Rediminds security specialists support our clients to maximize their cybersecurity, head over to our Identity and Access Management Solutions