Unlocking the power of Natural Language Processing in FinTech

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RegTech firm Moody’s Analytics recently took the opportunity to explain to its readers the power of natural language processing (NLP).

Every day, the digital world buzzes with hundreds of thousands of news stories. Meanwhile, global governmental bodies and agencies are constantly refining their databases and watchlists. Amidst this ocean of information, much of which is unstructured, lie invaluable insights crucial for businesses in understanding counterparty risks such as adverse media mentions or new sanctions database listings.

NLP, a cornerstone of AI, is rapidly evolving, ensuring that businesses can effectively interpret unstructured data. It empowers computers to grasp human language, both in written and spoken forms. While NLP isn’t novel, its development spanning over six decades has culminated in the vast array of digital assistants and chatbots we interact with today. The intricate world of NLP encompasses various facets like entity extraction, key phrase extraction, text classification, and semantic text similarity.

Entity extraction fundamentally transforms our approach to gleaning relevant information from textual data. It meticulously scans vast texts, recognising specific entities like individuals, organisations, or locations. Such capabilities are pivotal in enhancing Know Your Customer (KYC) processes by accurately spotting entities linked to financial misconduct or regulatory breaches.

Key phrase extraction helps businesses unlock rich insights from vast textual data. By identifying core keywords or phrases within documents, it succinctly captures vital information. Within realms like compliance and third-party risk management, it is instrumental in highlighting compliance-related keywords, potential risks, and other essential data points.

Classifying free text into predefined categories helps in its organisation and categorisation. Thus, content can be deemed risk relevant or not. Additionally, the realm of semantic text similarity delves deep into textual resemblance, understanding not just identical phrases but their underlying meanings. Such capabilities ensure businesses sidestep replicated content and consistently deliver fresh, valuable insights to their readership.

The accuracy of NLP hinges on vast training datasets. The richer the data exposed to the algorithm, the more robust its outcomes. Boasting a data reservoir that’s enriched daily from over 200,000 sources spanning 210 jurisdictions and 70+ languages, our database is a treasure trove of 19+ million curated profiles. For over a decade, NLP has been the cornerstone of our screening engine, addressing the complex challenge of dissecting both structured and unstructured data.

LLMs are AI juggernauts designed to simulate human-like text. By comprehending the subtleties of language, they forecast the next possible phrases in a sentence. Meanwhile, Gen AI introduces a dash of creativity in AI, crafting content that’s both coherent and tailored to specific needs. Our expertise in these domains enables businesses to elevate customer interactions, automate content, and derive profound insights.

Explainable AI (XAI) illuminates the intricacies of advanced AI systems, ensuring AI’s operations are transparent and comprehensible. In our journey, we’ve mastered explaining NLP models by unveiling the predictive prowess of words, ensuring businesses trust and adopt AI technologies, confident in their transparency and accountability.

Read the full post here.

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