Deep Learning for Third Party Risk Identification and Evaluation at Dow Jones
Deep Learning for Third Party Risk Identification and Evaluation at Dow Jones


Over 16 years Dow Jones is supplying Risk & Compliance data to banking and financial Institutions, corporate and governments, covering the world with defined, structured content sets of people and entities used to manage third-party risk: anti-money laundering, anti-bribery and corruption, sanctions or reputational risk. In order to achieve a comprehensive coverage guided by international regulation and guidance since 2002, we follow very high editorial standards and research methodologies, combined with state-of the-art machine learning techniques, to manage 30 risk categories 24 hours per day in over 70 languages.

In this presentation, we will focus on the natural language processing, information extraction and deep learning techniques, which Dow Jones leverages for Risk & Compliance data capturing and workflow efficiency improvement.

At Dow Jones, we wanted to apply a new approach to the existing content delivery pipeline with the objectives to:

Eliminate low-level, repeatable, manual processes, enabling researchers to focus on strategic tasks
Gain intelligence from global media and research tools, scanning and monitoring almost 2 million articles per week
Achieve near real-time risk data detection and delivery capabilities

We will explain how Dow Jones created AI-powered Risk & Compliance information extraction solution, that uses Natural Language Processing for risk profiles creation and management. The presentation will also highlight the unstructured data preprocessing stage, model selection criteria and neural networks parameter tuning processes to provide scalability and performance in order to achieve mentioned key objectives.


Victor Llorente is a technology product manager at Dow Jones, where he’s responsible for R&C data strategy applications in the professional information business. Victor has worked in several workflow automation and AI-driven projects using business process management engines, big data, and data science technologies using agile methodologies. He holds master’s degrees in computer engineering from Polytechnic University of Catalonia, Barcelona, and a degree in computer science from the Royal Institute of Technology, Stockholm, as well as an MBA from Instituto de Empresa, Madrid. Victor is a speaker at industry conferences — where he shares his knowledge and passion for technology and data.

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Consent to display content from - Youtube
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google