Even in the digital age, customers still use their signatures as a primary form of authentication for a range of transactions. Their signatures authorize checks, new account paperwork, loan documents, and more. Unfortunately, with the rise of digital banking and e-signatures, many financial professionals are starting to overlook the importance of the signature, but doing so can put your customers and your financial institution at risk.
Check fraud poses a significant threat to banks of all sizes, but community banks face a heightened risk. To minimize the risk of fraud, your financial institution needs the right solutions to detect forgeries quickly and accurately.
What Is Forgery Detection?
Forgery detection is looking for fraudulent versions of real visual items. For example, financial institutions use forgery detection tools to look for forged signatures on checks, loan applications, or other documents. In the art world, forgery detection is used to spot fake pieces of art that may be made fraudulently or as an imitation of the original.
Forgery and Fraud Detection at Banks
To detect fraudulent signatures, banks should use a blend of manual and automatic forgery detection. Ideally, financial institutions should use automated signature verification tools that can quickly assess every presented signature in comparison to a copy of the customer’s signature saved on file. The tools use pattern recognition to analyze the signature. They also rely on machine learning and behavioral analysis to improve their accuracy over time.
If the tools spot issues that indicate a high likelihood of forgery, they can flag the transaction for manual review. At that point, a member of your team can make the final call about whether or not to allow the transaction to move through. Depending on the situation, they may need to contact your customer for verbal authentication. Taking a hybrid approach saves resources, reduces false positives, and increases fraud detection at your bank.
Types of Signature Forgeries
Be aware that forged signatures take a variety of forms depending on the forger’s knowledge of the signature, the way they attempt to copy it, and their experience as a forger. Educate your team about different types of forgeries including the following:
Blind Forgeries
These forged signatures have little to no resemblance to the customer’s actual signature because the forger does not have access to the signature. For example, this comes into play if a thief is opening a new account using a stolen Social Security Number they bought from the dark web or if they’re writing bad checks from a stolen checkbook. Because they don’t have a reference signature, the thief simply writes the name however they like.
Trace-Over Forgery
Also known as an unskilled forgery, these forgeries are created by tracing over the actual signature. They tend to look very similar to the accountholder’s genuine signature and the differences are often undetectable to the human eye alone. However, these forgers focus on accuracy over fluency, and that’s where signature verification tools that assess fluidity by looking at pen strokes and pressure can help protect your bank.
Skilled forgery
The hardest type of forgeries to detect, these signatures are produced by criminals who have spent a lot of time practicing and have the ability to replicate the actual signatures in a way that looks both accurate and relatively fluent to the naked eye. Both humans and automated tools can sometimes miss these forgeries, but if your fraud detection tools also assess patterns of behavior on the account, they are more likely to detect a skilled forgery simply because the check is unusual for the account holder.
The Risks of Manual Signature Verification
Manual signature verification can easily detect the differences between blind forgeries and actual signatures, but this approach struggles to detect traced or skilled forgeries. It also has a lot of subjectivity, and its efficacy tends to be inconsistent based on the expertise of the banking professional as well as their mood, fatigue levels, and distractions. As a result, manual signature review can lead to an uncomfortable number of incorrect rejections and forgery acceptances.
Flagging transactions as fraudulent when they are not impairs customer satisfaction and injects unnecessary delays and friction into customer transactions. On the flip side, if your team lets a skilled forgery slip through, you’re likely to suffer both financial and reputational losses as well as remediation costs. To minimize the threat of both of these scenarios, you need automated signature verification tools.
Static and Dynamic Signature Features
To effectively verify signatures, you need to examine static and dynamic features to detect minute differences between presented signatures and actual signatures. These features include the following as well as others:
- Shaky handwriting
- Pen lifts
- Signs of retouching
- Letter proportions
- Signature shape and dimensions
- Letter slants
- Speed, acceleration, and smoothness of curves
- Pen pressure and pressure changes
As you can imagine, many of these features, particularly the dynamic features such as acceleration and smoothness of curves are impossible for the naked eye to detect during manual verification, while the static features such as shaky handwriting or letter slants are easier to detect.
To move past manual signature verification and toward a verification process that looks at both dynamic and static features, financial institutions need to rely on automated tools. Ultimately, effective signature verification solutions fall into two main categories: offline and online.
Offline Signature Verification Solutions
Offline signature verification tools rely on comparing static, two-dimensional images in situations where it’s impossible to monitor real-time signature activity. These solutions imitate the detection methods used by humans, but they automate the process to help you save time and resources. Offline signature verification solutions primarily look at static features such as the texture of the signature, shape and size aspect ratios, stroke positions, and handwriting differences.
These tools analyze signatures by comparing suspicious signatures with real signatures, but unlike most humans, these solutions don’t look for an exact match. Instead, they use machine learning to assess if the signature falls into the expected range of variation of the customer’s actual signature.
Remember, real signatures are not identical. They can vary a lot depending on the signer’s mood, emotional state, age, conditions while signing, and multiple other factors, and effective signature verification tools take all of this into account.
Online Signature Verification Tools
Online signature verification tools go a step further and analyze dynamic signature features such as speed and pressure. The key feature of an authentic signature is fluency. Even a well-practiced, skilled forgery takes longer to produce than an authentic signature.
While someone can sign their own name without hesitation, forgery involves deliberately controlled muscles and a slower signing process, and online tools help you detect these dynamic differences.
The Right Signature Verification Solutions for Your Financial Institution
Most financial institutions need both offline and online signature verification solutions so they can effectively assess all the signatures that they review.
At SQN Banking Systems, we offer a variety of signature verification solutions designed to help you detect forgeries more effectively, while also reducing the burden of manual verification on your team and the risk of hurting customer relationships with false positives. To learn more, contact us today or check out the following FAQs to learn more.
Do banks check signatures?
Some banks check signatures on checks, while others do not. Not checking signatures increases the risk of check fraud at your financial institution and may also increase your liability for losses. Generally, accountholders have 30 days to report check fraud or they become liable for the losses. However, liability rules may shift when the bank accepts a forged check.
How do you tell if a signature is forged?
The most effective way to detect a forgery is with automatic signature verification tools. Automated tools speed up processing time and reduce errors associated with manual verification. Whether you’re dealing with checks or other documents, signature verification software looks for minute differences in static and dynamic details between the presented signature and the reference signature.
How do banks detect forgeries?
Banks may manually verify the signatures on checks that fall within certain parameters—for example, checks over a certain amount or checks written from new accounts. Unfortunately, this approach is error-prone and labor-intensive. To improve detection rates, banks should use signature verification tools to automatically look for forgeries.
How do banks prove forged signatures?
Banks can use signature verification tools to detect forged signatures. However, to prove the forgery, they may also need the accountholder to sign an affidavit affirming that they did not authorize or sign the check. They may also use security footage to see who deposited the check or learn more about the crime.
How do you tell if a signature is real?
Real signatures are written fluidly. Signature analysts can assess the speed, pressure, and form of signatures to see if they were signed fluidly. If the signature appears to be traced or written slowly, it may be a forgery. Additionally, signature analysts and signature verification software can compare presented signatures with reference signatures. To tell if a signature is real, human analysts and software look for discrepancies between the static elements of the signature such as letter shape, size, and slants as well as the dynamic elements of the signature such as speed and fluency.