5 Tips for Digital Identity Verification in Financial Services

In the financial services industry, smooth identity verification is vital for upholding trust. This ensures compliance and delivers an efficient customer experience. Key challenges for businesses in this field include shortening verification times, boosting customer satisfaction, and reducing abandonment rates. Here are some tips for effectively implementing digital identity verification in financial services.

Examine Various Data Layers

Approximately 45% of organizations view multiple layers of identity attributes as a best practice. As fraudsters enhance the complexity of their schemes, using additional layers, or “blankets,” of attributes is crucial for achieving a seamless customer experience and effective fraud prevention.

Solutions that integrate multiple dynamic data, especially synthetic identity fraud, but also minimize friction, as they rely on straightforward data collection practices to explain and justify. Having multiple layers central to the identity verification process allows for quicker and more precise identification of legitimate customers, resorting to additional verification methods only when necessary. An MRZ scanner SDK may be used to help with this process, as it is a software development kit designed specifically for reading machine-readable zones on documents. This can provide an added layer of verification and make the overall process more efficient.

Adopt Transparency in Data and Decision-Making

Many machine learning solutions offer a simple yet opaque pass or fail score. Institutions must rely on restrictive and unclear score-based identity verification models without insight into the decision-making data. These “black box” solutions lack data intelligence transparency, using standard engine logic across customers and industries.

A robust identity verification solution should include a continuous data feedback loop, enabling institutions to explain the rationale behind their decisions to regulators and consumers. This approach allows financial institutions to evaluate risk better and adjust identity verification processes to meet their needs. Achieving this is nearly impossible with systems dependent on “black box” algorithms and minimal governance of changes between companies.

Embrace Technology

Machine learning and AI significantly boost digital identity capabilities by enhancing security and accelerating response to threat indicators. With their ability to learn, these technologies can adapt and react to potential threats faster than humans, fostering a human-machine collaboration that enhances process speed and accuracy.

Biometric Authentication

Biometrics use a person’s distinct physical characteristics to verify and confirm their identity, employing facial, iris,  retina, voice, and fingerprint recognition technologies. After the initial setup, these methods offer clients significant convenience by eliminating the need for passwords or security questions.

However, biometrics have their flaws. Fake biometric data can be created. Consider how your photos are shared online and your voice can be recorded without your knowledge. Hackers can steal fingerprints from databases. If these assets fall into the wrong hands, it can be easier to deceive certain institutions.

Knowledge-Based Authentication

Knowledge-based authentication verifies an individual’s identity by asking security questions. Typically, these questions are designed to be easy for the individual to answer but difficult for others. Examples include the number of dogs you own and the name of your favorite instructor.

A time limit on responding to the questions adds a layer of security to KBA. Its greatest advantage is being the most user-friendly verification method. However, the main drawback is that answers can often be discovered through traditional social engineering and social networking.

Endnote

As the financial sector transitions to a post-pandemic era, fraud attempts are expected to increase, paralleling rising customer expectations. Identity verification will become both an operational requirement and a moral duty, ensuring the safety of financial institutions and consumers in a complex digital landscape.