Hackers, social engineering
fraudsters, human error and customers who are just plain careless with
credentials are all security threats that banks and credit unions must take
into account. Prevention requires an in-depth, multiyear strategic plan, not a
short-term, quarter-to-quarter focus that leads only to reactive, merely
tactical solutions.
Security breaches have become one of the
biggest threats to financial institutions. Remote working, cloud computing and
the current geopolitical climate have all played a part, but older forms of
infiltration also continue. For example, recent years have seen a sixfold
increase in malicious emails designed to trick people into giving away login
credentials, a type of attack known as “social engineering.”
Banks should be
the safest place for people’s money. Indeed, they have a fiduciary
responsibility to proactively mitigate and manage risk for account holders.
Unfortunately, bank and credit union executives often don’t understand how
severe the problem is. Data at risk leads to identity theft and funds stolen
electronically. Ultimately, reputations erode.
Outlined here are some of the top threats
that lie ahead and what approaches we’re seeing to address this.
How Cybercrime Is Hitting
Banking Today
We
believe financial institutions will place a heavy emphasis on implementing
passwordless solutions with a requirement of multi-factor authentication (MFA).
A 2021 Forrester survey noted
that 67% of corporate leaders were in the process of adopting passwordless
authentication for their employees and partners, a trend we think will—and
should—continue in banking.
With
the adoption of cloud computing and hybrid environments, we will see an urgent
need to implement Secure Access Service Edge (SASE) solutions. Tech
improvement breeds exposure, because most companies started with on-premise
equipment and have moved apps, workloads and storage to the cloud, the attack
surface has increased exponentially.
This
in turn has created less visibility into the internet environment, eliminating
the “secure perimeter,” creating more complexity, and requiring the purchase
and configuration of additional forms of protection.
The
more complex an environment, the more human error we see. Put simply, SASE
methods push security onto the cloud.
Because most companies started with on-premise equipment and have moved apps, workloads and storage to the cloud, the attack surface has increased exponentially.
In the coming years, artificial
intelligence and machine learning will continue to be a major factor in
cybersecurity for the financial services industry and industries
abroad. We’ve started to see this already in some cutting-edge security
products that are coming to market – “good bots” pitted against “bad bots,” for
example.
Automation is another big factor—both as risk
and benefit—as companies move to automate everything they can. We will start to
see more low-code and codeless platforms which aim to make organizations more
efficient while cutting down on human error.
Where
Cyberthreats to Banks and Credit Unions Arise
How
can financial institutions do more to prevent cybercrime? First, they need to
be aware that this is a long-haul process — and must plan for it. Improving
cybersecurity is a journey, not a sprint. An in-depth, multiyear strategic plan
is called for, not a short-term, quarter-to-quarter focus that leads only to
reactive, merely tactical solutions. Budget Cutbacks Undermine Cybersecurity:
Even when strategic plans are developed, they are often undercut by midyear
budget cuts and executive churn that stymie progress.
Firms need to understand and assess the range of risks
they face, starting with internal
threats. Errors and mistakes that compromise security happen
frequently, and steps need to be taken to better safeguard against them.
Whether they take place in the office or remotely, malicious acts by employees
and contractors are also a significant risk.
External
threats come from a mix of technology and people. Human
hackers and automated bots alike constantly probe systems looking for
vulnerabilities. Customers are essentially the external counterpart to employee
error; customers represent the riskiest component in the entire threat
ecosystem because their inadvertent lack of care and precaution introduce
significant vulnerabilities by doing things like logging on through open
internet connections, using predictable passwords, and failing to update their
security credentials.
Even when strategic plans are developed, they are often undercut by midyear budget cuts and executive churn that stymie progress.
“Social engineering” continues
to represent a significant security threat. Cybercriminals rely increasingly on
psychological manipulation, rather than technology, and they target both employees
and customers.
Phishing
emails, which employ psychological manipulation techniques to fool the
recipient of the email to open a link or attachment that contains malicious
software, are one example of a tried-and-true social engineering scam. Some
prey on people’s fears, anxieties, or emotions, causing them to lower their
defenses and let a hacker into their system. Others invoke a sense of scarcity
or urgency to goad a victim into acting quickly without thinking.
A
Broad Plan of Attack on Cyberthreats
Financial
services organizations need to improve their processes, engineering and
technology to protect against these risks. Systems reliability engineering
needs to be improved, if only because— despite the many concerns about hackers
and other nefarious actors — only 6% of all failures at major banks are caused
by external forces. Most system availability problems occur because of bad
change processes, poor software, deployment issues, incorrect specifications,
and other issues.
Security
can be improved through several means, but multiple layers of protection are
called for. Passwordless logins that use biometrics and tokenization provide
login protection that is more secure than passwords.
Behavioral analysis and pattern recognition are also powerful tools to improve cybersecurity — building customer profiles makes aberrant or fraudulent behavior easier to detect so that, for example, credit card charges that are outside the cardholder’s usual activity can be declined.