The banking sector is in the midst of a radical shift from legacy traditional systems to modernized infrastructures. Customer adoption of digital financial services is accelerating the growth of this industry with a prediction to reach $10.3 trillion by 2028. The concurrent surge in fraud, however, is grasping the attention of legislators. Therefore, they are strengthening regulations for handling customer data and preventing criminal activities.
As the fraud risks continue to increase, regulatory pressure is equally tightening. Therefore, banks need to perform efficient ID verification of customers. Synthetic identity fraud leads to suspicious activities in digital banking operations, which require the upgradation of IDV controls. This blog covers the challenges banks face during customer verification and how AI-powered identity authentication solutions help counter them.
Challenges Banks Face During Customer Verification
The banking sector is most exposed to criminal threats as they involve a huge of transactions on a regular basis. Similarly, its digitization is another catalyst for increasing fraud. Criminals use spoof attacks, the act where fraudsters disguise themselves as legitimate customers either by creating facial masks, phishing calls, and others, to trick online banking systems. In return, they steer clear of identity verification and exploit financial services for their malicious intentions.
Banks strive to tailor their operations to customer demands such as convenience and data security. For this, they are integrating identity theft protection mechanisms into their onboarding processes. However, while performing ID verification, they face several challenges. The factors behind them involve:
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Elusive Nature of Counterfeit Identities
The growing threat of synthetic identity fraud and criminals deploying sophisticated camouflaging techniques is one of the major factors behind criminal activities. Data breaches fuel the creation of counterfeit profiles. Criminals can then bombard ID verification with plausible-looking customer identities. Therefore, banks require more efficient IDV solutions to prevent this type of fraud.
Outdated and Complex Infrastructures
Financial institutions using the old banking methods such as physical check cashing and transactions are more prone to inadequate identity authentication. As the core long-in-use systems are complex, it further leads to customer drop-offs. All of these factors not only make the integration of digital IDV technology challenging but also increase the costs of manual data handling.
Touchless Transactions
The rise in customer demand regarding digital payments is leading to a massive increase in fraud. The speed of transactions makes it challenging to ensure the person requesting them holds a legitimate identity.
Use of Machine Learning (ML) Models Without Transparency
The banking sector is one of the most highly regulated industries among other financial institutions. As per the legal standards, service providers need to ensure transparency and are liable to answer for any suspicious activity. In order to cope with the digitally evolving financial landscape, banks are using inefficient ML models. This practice hinders the decision-making and automation of identity verification services. Therefore, banks require efficient AI-powered IDV solutions to retain a balance between transparency and digitization.
Mounting Regulatory Strictness
Financial institutions are experiencing mounting regulatory pressures both in terms of identity verification and customer data handling. Increasing fraud risks are diverting the attention of legal bodies. Therefore, banks require efficient customer identification mechanisms to ensure accountability and adherence to KYC/AML/CFT regulations.
Identity Verification Services – Secure Ways for Automation of Banking Operations
Upgrading financial services while embracing digitization means experiencing new obstacles, predominantly creating a digital onboarding process with efficient identity authentication and fraud prevention tactics. Where creating counterfeit profiles is a threat, account takeover is equally making digital banking services vulnerable. Therefore, financial institutions are in dire need of enhancing their fraud prevention controls. As a result, they can ensure that the legitimate customer is requesting a money transfer, payment for shopping, or other such activities.
Identity verification facilitates the growth of digital banking services by providing a secure financial landscape. These AI-powered IDV solutions hinge on the following to safeguard this industry from external criminal threats:
- Uses biometric identity verification systems to authenticate customers from multiple layers of intelligence such as facial, voice, gesture, iris/retina, and other biological/behavioral analysis
- Automates customer onboarding by increasing banking systems’ capability to analyze huge datasets through machine learning algorithms
- Offer data transparency along with efficient risk assessment and ongoing activity monitoring
Final Verdict
Identity theft comes in various forms and is tricky to detect by using manual identification mechanisms. Fraud risks harm the integrity of banks while increasing their exposure to regulatory scrutiny and hefty penalties. Customer experience is another aspect banks need to consider while transforming their services. Complex and riks-involved operations are sure to drive away users. Therefore, to strike a balance between fraud prevention and convenient financial services, digital ID verification is banks’ reliable bet.
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