Economic uncertainty has created a perfect storm for an increase in financial crimes. For organizations that are still performing AML/KYC compliance checks without assistance from articiial intelligence (AI), the time has come to rethink that unsustainable approach. Financial criminals have long been using AI to attack financial networks, and until FIs started using the same technology to fight back, they will always be playing catch up. If yo...

Maintaining complete records of school staff and students is essential for managing daily school operations, and accurate student headcounts are vital for receiving correct federal funding. One solution is to assign a unique ID for use across the school system, but students' names must be matched with their unique IDs while still maintaining their privacy. This becomes challenging when many students have the same or similar names. During this...

Human Language Technology (HLT) cannot be “future proofed” because the target is organic, ever changing, human language. Like a weather forecast, a static model is only accurate at a point in time. What we need is the NLP equivalent of a weather app pulling in streaming live weather data. Adaptation is the future of HLT: continuously learning models that are quickly spun up with an annotation effort to “crawl”; then ada...

Capably matching names and other personally identifiable information (PII) is critical to any effective compliance screening system: failure puts reputation, finances, and ethics on the line. Unfortunately, globalization coupled with the economic impact of the pandemic is testing screening systems like never before. As applications pour in, these systems are being asked to process key identity data in a huge variety of languages at unprecedent...

PRACTICAL AI FOR HUMAN LANGUAGE More than ever, it is imperative that intelligence systems stay on top of the increasing load of data. AI and machine learning are the only practical solution. This year’s Human Language Technology Conference brings together experts in computational linguistics, artificial intelligence, machine learning (ML), and data science to discuss their first-hand successes and failures and share lessons learned from...