The banking industry is in the midst of a radical shift. Rapid consumer adoption of digital banking services has accelerated the industry’s move from legacy systems and antiquated processes to modernized infrastructure and services. At the same time, surges in fraud have captured the attention of legislators, shining a light on the need for tightening regulations to better protect consumer data. All of this points to one thing – financial institutions (FIs) have their work cut out for them.
Having the right strategies, processes and technology in place to verify customer identities safely and quickly will be critical to success as fraud risk continues to increase, regulatory pressures tighten and attracting and retaining customers becomes more and more difficult. However, the banking industry faces the most challenging identity verification conditions of any industry, due to several factors.
Highly complex and in some cases, outdated technical infrastructure. Many FIs run older core banking software systems that are not only complex and costly but also challenging to integrate with new technology.
Reliance on Machine Learning (ML) models without transparency into decisioning. As one of the most heavily regulated industries, banking has firm requirements for transparency and an ability to explain decisions to regulators. Most ML models in use today lack the closed-loop feedback that FIs need to explain decision-making, which has been a limiting factor for the use of automation within banking. Using ML within the banking sector requires a careful approach that balances automation needs while still leveraging rules-based systems combined with human intelligence.
Faster payments limit response time. The rise of faster payments, such as Real Time Payments in the US, is leading to major fraud risk because their inherent speed limits the window of time banks have to intervene in the transaction process.
The growing threat and elusive nature of Synthetic Identity Fraud (SIF). Fueled by a significant volume of data breaches, criminals can bombard verification systems with plausible-looking identities, requiring advanced verification strategies to protect against SIF.
Mounting regulatory pressures. FIs are both experiencing and expecting tougher compliance requirements and oversight from the likes of the Consumer Financial Protection Bureau. High levels of fraud linked to the Paycheck Protection Program are likely to be a catalyst for state and federal regulators to seek more accountability on the part of FIs and lenders.
Competing with digital challengers means addressing these obstacles, beginning with a digital onboarding process that safely and quickly verifies customer identities. Just as important is ongoing verification, or authentication. Opening a fraudulent account is a risk, but an account takeover of an existing account is also a threat. And, as open banking becomes more prevalent, FIs must ensure that account data sharing and payment initiation are authorized by the correct party. As embedded finance grows, where payments and banking are increasingly embedded in other activities outside of core banking experiences, the importance of identity verification will only grow.
As banks and FIs accelerate digital transformation, effective identity verification hinges on:
Multiple Layers of Intelligence. Solutions that “orchestrate” multiple dynamic data sets, not only detect and deter fraud but also deliver a seamless customer experience based on decisioning that is easy to explain and defend. With multiple layers at the heart of the identity verification process, legitimate customers are identified more quickly and accurately. Additionally, step-up verification methods are used only when necessary.
Machine Learning + Human Intelligence. By applying machine learning to the identity verification process, businesses have the power to analyze massive amounts of digital transaction data, create efficiencies and recognize patterns that can improve decision making.
Data Transparency. An effective identity verification solution should provide a continuous data feedback loop to help businesses understand and explain to regulators and customers why decisions were made. With data transparency and actionable scoring intelligence, FIs can explain to regulators and consumers why certain decisions were made, better assess risk and fine-tune identity verification processes to best fit their business needs.
Customization. Every FI is different and should verify differently based on its unique needs. This includes the ability to tweak and tune identity verification settings in real-time, without the help of IT. FIs need the ability to act quickly as they anticipate attacks, adapt to systemic changes in human behavior, and respond to the emergence of new customer segments, profiles and needs.
With growing consumer demand for seamless digital experiences, leading FIs have turned to IDology to bring a strategic focus and effective identity verification to their digital transformation initiatives. To learn more, download our Digital Identity Verification Sector Spotlight on Banking.