In the world of finance, compliance stands as a steadfast pillar for regulated institutions. These institutions bear the weight of not only economic transactions, but also the responsibility of safeguarding the integrity of the financial system as a whole. But more than this, with regulators becoming more sophisticated at the same time as the compliance function becoming more automated, compliance teams need to select identity verification providers that they can trust—and therefore have to override only in exceptional circumstances.
The human-over-the-loop AI framework is a hybrid approach that allows regulated entities to take advantage of fully automated AI identity review, but retain human oversight where fraud is flagged or the exceptional case where users cannot complete the process.
In this blog post, we’ll look at the application of the human-over-the-loop AI model in Know Your Customer (KYC) requirements, why it is essential to use a human-over-the-loop model, and explore why it is important to select an AI-based KYC provider that has the lowest possible error rate.
Thanks for the complement
At its core, the human-over-the-loop AI framework places humans as the ultimate decision-makers where fraud is identified by the fully automated AI-driven solution, ensuring that AI machines augment the decision to reject a user rather than making the ultimate decision. Human oversight on the recommendation of the AI tool adds a layer of understanding, context, and ethical considerations that technology alone does not provide.
The human-over-the-loop AI model aligns seamlessly with KYC requirements. KYC, a cornerstone of financial regulations, mandates institutions to verify the identity of their customers to prevent fraud and illicit activities. Strong, well-built, and Zero Bias AI™-driven fully automated IDV solutions can identify sophisticated fraudsters and can defend against deepfake attacks. But as the AI gets more sophisticated, there is a temptation to rely entirely on it, rejecting applications that are flagged as potentially fraudulent without further consideration.
The AI-driven automated solution increases KYC efficiencies, allows a return on investment, and allows a stronger end user experience due to its reduced processing time. Using a human-over-the-loop reviewer to supplement the power of the AI helps ensure that people are not unfairly or incorrectly excluded by the automated IDV solution.
This approach holds paramount importance in ethical and regulatory adherence. Under privacy laws such as the GDPR, financial institutions often cannot reject applications based on AI alone but must have a human review as the final decision maker.
In addition to the legal requirement, ensuring that machines alone do not make decisions in isolation of human direction is a key ethical consideration for any responsible business that makes decisions with either a high severity or a high impact of harm. The Singaporean Model AI Governance Framework explains neatly why this is essential. The problems of human-out-of-the-loop algorithmic decisions are also graphically explained in Cathy O’Neil’s recent book Weapons of Math Destruction.
Thus, a human-over-the-loop framework to an otherwise fully automated IDV process is a legal and an ethical necessity. And it therefore follows that it is essential to select an IDV provider with the lowest possible false flag rate/false positives to reduce the manual review burden.
Welcome to the real world
Imagine a scenario where a regulated institution encounters a challenging identity verification case involving complex documentation and subtle nuances that the fully automated KYC solution was able to detect. Enter the human-over-the-loop AI framework. By involving human experts to review the recommendation of the AI, institutions can ensure that the interpretation of documents complements the algorithms.
In instances where AI might flag due to unique circumstances, human intervention provides the ethical and contextual understanding needed to make informed decisions, including perhaps asking the user to try again with different documents or to try an alternative identification route.
A regulated institution will want to choose the best possible AI-driven solution to ensure that the instances where humans have to step in and override the recommendations are the rare exception.
An extra layer of credibility
AI-driven fully automated identity verification can lead to enhanced accuracy which in turn leads to a reduction in false positives (false flags), saving valuable time and resources. Including human oversight further enhances the process and allows institutions to look after those genuine customers that are unable to complete the automated KYC process correctly. As institutions embrace this model, they foster a culture of trust and transparency both internally and with their customers.
When they embrace the human-over-the-loop AI model, institutions also enhance their regulatory compliance posture. Regulators value institutions that demonstrate a commitment to robust risk management and ethical conduct. This approach not only streamlines the compliance process, but also positions institutions as proactive stewards of the financial ecosystem.
Wrapping it all up
As regulated institutions move forward, the call to action is clear: embrace the human-over-the-loop AI framework not merely as a tool but as a philosophy. Adopting a high-performing, fully automated IDV solution is key to reduce manual review costs and processing times, but it must be adopted without losing the human touch.
About the post:
Images are generative AI-created. Prompt: human + computer double exposure. Tool: Midjourney.
About the author:
Peter Violaris is Global DPO and Head of Legal EMEA for IDVerse. Peter is a commercial technology lawyer with a particular focus on biometrics, privacy, and AI learning. Peter has been in the identity space for 6 years and before that worked for London law firms.
