Socure, the provider of artificial intelligence (AI) for digital identity verification, compliance, and fraud prevention, announced the launch of the company’s AI-powered assistant for its Global Watchlist Screening and Monitoring solution.
This AI-driven assistant transforms watchlist screening by improving “how organizations handle sanctions, politically exposed persons (PEP), and adverse media matches.”
Socure’s solution aims to deliver speed, accuracy, and efficiency by reducing false positives, “accelerating case reviews, and improving analyst decision-making.”
Traditional watchlist screening is said to be plagued by inefficiencies that strain compliance teams—”high false positives, time-consuming manual reviews, and regulatory complexity.”
Financial institutions, fintechs, and global organizations face pressure to comply with evolving “restrictions from agencies like OFAC, with penalties for non-compliance exceeding $8 billion globally over the past two years.”
Socure’s Global Watchlist Screening and Monitoring solution “introduces a patent-pending, two-stage scoring system providing dual controls.”
The first stage assigns a Name Match Score, creating a candidate pool by assessing how closely “a customer’s name aligns with watchlist entries.”
This is then enriched with additional personally identifiable information (PII) for “a clearer risk assessment.”
In the second stage, an Entity Correlation Score replicates an analyst’s decision-making process, “evaluating the likelihood that the source list and the matched entity are the same.”
This step strengthens regulatory compliance by “minimizing false positives and negatives, significantly reducing the need for manual reviews, and streamlines compliance.”
For each match, the AI Copilot transforms operational workflows “by creating consistency in process, reducing human subjectivity, and ensuring standardized documentation.”
By clearly articulating disqualification criteria in plain language, the AI Copilot is said to remove “the burden on analysts to manually craft decision narratives, instead delivering clear, structured explanations.”
Analysts remain in control to “confirm or override results, with all actions logged for transparency and compliance.”
Additional Features in the Solution include:
- Real-Time Analysis – Instantly processes potential matches in just two seconds.
- Contextual Understanding – Powered by Natural Language Reasoning (NLR), the AI Copilot recognizes multiple aliases, contextual identifiers, and cultural variations, reducing false positives.
- Streamlined Decision-Making – Accepts or rejects matches using AI-supported reasoning, with the ability to add investigative notes quickly.
- Regulator-Ready Documentation – Generates audit-ready reports in an intuitive, streamlined interface.
By leveraging the new AI Copilot and advanced entity correlation, Socure’s solution delivers “efficiency in watchlist screening, significantly reducing false positives, streamlining reviews, and cutting operational costs.”
Key results include:
- 78% reduction in manual reviews – Reduce the number of flagged identities and false positives with improved accuracy, reducing unnecessary manual reviews and enabling analysts to focus on true risks and high-value, strategic tasks.
- 80% faster case reviews – Reduce average review time from 10-15 minutes to 2-3 minutes, allowing more cases to be processed daily and improving overall team productivity.
- Up to 60% cost reduction – Reduce compliance operational costs by using AI narratives as templates for standardized investigations, creating consistent reviews that lower quality control costs by minimizing variability and errors.
In a real-world test, AI Copilot flagged a case where “Paolo Garcea” and “Isabel Paola Garcia” showed 88% name similarity, which would traditionally trigger a manual review.
However, the system identified critical “mismatches in gender, ethnicity, and location, correctly classifying the alert as a likely false positive—saving time, reducing unnecessary escalations, and improving operational efficiency.”
Lili App Inc. (Lili) is a financial platform designed “specifically for businesses, offering a combination of advanced business banking with built-in accounting and tax preparation software to help business owners better streamline and simplify their finances.”
As a fast-growing business banking platform, “processing a high volume of transactions monthly, its team faced a critical scaling challenge.”
With regulatory requirements intensifying across the fintech industry and an estimated 70% increase in entities on global watchlists since 2020, they needed “a better way to manage screening requirements during rapid growth.”
Lili’s analysts spent hours reviewing “an increasing number of potential matches, many of which turned out to be false positives.”
Lili reportedly improved their watchlist screening process, “achieving a 78% reduction in manual reviews, stronger audit trails, and the ability to reallocate analyst time to more strategic risk-mitigation efforts.”
Most importantly, it was noted that Lili was able to “maintain compliance with evolving regulatory requirements.”