We are literally overwhelmed by information - companies could be publishing information on new products or services, which is relevant for the competition, shareholders, their banks, and insurers. Newscasts could be reporting on an event such as fire of a production plant, creating a chain reaction from a claim on the insurance policy to the financial statements to the reputation of the plant itself.
Automated OSINT is a perfect source for new generation of solutions utilizing both supervised and unsupervised Machine Learning, a discipline of Artificial Intelligence. By computer managed source discovery, content extraction, semantic analysis, and threat/opportunity scenario detection and together with over 10 years of OSINT data archive, we are able to scan and collect up to 4 million articles per 1 day and in more than 17 languages. This gives us visibility on vast majority of the Internet media content and allows us to “take the pulse of the planet”.
Some of the typical use cases could be related to the topic of regulatory or compliance.
In a global economy, risks are global as well. And yet a trivial controversy by any third party poses a risk of financial loss or cause significant impacts on the company brand and reputation.
Nowadays, analysts can spend hours perusing the vast amount of publicly available information (PAI) on the internet and even longer reporting on it. But AOsint can screen this information through the Internet automatically for you and save your time and money.
AOsint engine can support Know Your Customer (KYC) compliance that is designed to protect companies against fraud, corruption, money laundering, and terrorist financing. How? This automated OSINT would recognize potential risky customers based on various risk categories such as Anti-Bribery and Corruption, Anti-Money Laundering, Informal Value Transfer System, and many others.
Moreover, you can scan the reputation of the chosen company by risk sentiments → negative, positive, or neutral. Typically, you can be mainly interested in those negative ones to track how the company's reputation is damaged and whether it can indicate any risks.