Babel Street - Experts & Thought Leaders

Babel Street, an advanced multi-lingual search and data analytics company, has announced that it has formalised a partnership with the National Center for Spectator Sports Safety and Security (NCS4) during its participation at the Project Stadia Sports Security Senior Management Training Course that took place at Interpol Headquarters in Lyon, France last week. Safety And Security Of Sporting Events “We believe that the safety and security of fans and participants of sporting events around the world is paramount to the enjoyment of the games” said Jeff Chapman, CEO of Babel Street. “As we have demonstrated first hand at various world events, including the Super Bowl and baseball’s World Series, our technology assists security professionals in making timely and potentially life-saving decisions. Through our partnership with NCS4 and Project Stadia, we aim to bring this critical capability to the rest of the world.” From September 12-14, the NCS4, in collaboration with INTERPOL Project Stadia, delivered an all-new, three day Sports Security Executive Management course at Interpol General Secretariat in Lyon, France.  During the event, Babel Street showcased its unique venue safety capabilities to nearly 100 security professionals and Interpol partner organizations, and through this partnership, it will continue to deliver this training globally over the next year.   Recently, Babel Street was awarded the prestigious Golden Eagle award by The National Center for Spectator Sports Safety and Security, for the use of Babel X to assist event officials in maintaining situational awareness and security of the Super Bowl XLIX facilities.   Data Analytics Software Solutions Babel Street is a provider of advanced multi-lingual search and data analytics software solutions.  The company enables customers with the ability to identify, analyze, and report on critical information pertaining to their organization.  Through Babel Street’s world class technology, users access and analyze millions of multi-lingual and geo-enabled data points emanating from public sources in more than 200 languages at near real-time.  By delivering this wealth of information in a single pane of glass, Babel Street helps organizations coordinate research across teams and identify patterns and risks earlier, while also reducing the time and number of tools needed to create actionable insights.  The company currently serves many of the world’s leading brands in financial services, transportation, entertainment, sports, higher education, hospitality, and government. Babel Street is privately held and is headquartered in Washington, DC, with offices in London, Canberra, and San Francisco. 

Babel Street®, an advanced multi-lingual search and analytics technology company, has announced that the company will participate in the upcoming American Society for Industrial Security’s Annual Seminar and Exhibits event (ASIS 2017), which will be held between 25th-28th September in Dallas, Texas. Search For Information Across Hundreds Of Languages With 2.5 Exabytes (2.5 Trillion GBs) of data generated online every day in numerous outlets and hundreds of languages, organizations often struggle to pinpoint the specific information relevant to their corporate security. Babel Street’s core technology, Babel X, brings organizations an unprecedented access to billions of social media postings and blogs, hundreds of millions of unique websites, thousands of diverse news sources, as well as unprecedented access to deep and dark web sites, and commercially available data sources. The key benefit of Babel X is 360° situational awareness that informs decision-making in the rapidly changing world of corporate security. To the end, Babel X uniquely enables organizations to search quickly and persistently for critical information across hundreds of languages.  Virtual Data Interpretation A virtual data interpreter with network analysis capabilities, Babel X yields answers and insights in easy-to-consume formats from any computer, device, or smartphone with an Internet connection and a web browser. “Security professionals often don’t know what they are missing when it comes to piecing together their threat intelligence landscape, so we want to make it clearer for them,” said Jeff Chapman, CEO of Babel Street. “With less than fifty percent of the internet in English, there is a lot being communicated, even with symbols and emojis, that can provide important insight or answers for organizations. Add to that, many are limiting their searches to English words found only via indexed websites or a few social platforms. We want to help these professionals understand that what they are missing is likely hiding in plain sight. They just need a platform that enables them to find answers instead searching for them.” Recently, Babel Street was awarded the prestigious Golden Eagle award by The National Center for Spectator Sports Safety and Security (NCS4) for using Babel X to assist event officials in maintaining situational awareness and security of the Super Bowl XLIX facilities. The sports industry is one of many recognizing the value of informational situational awareness for an industry’s security posture.

The global maritime surveillance market is projected to grow from $21.9 billion in 2023 to $ 42.7 billion by 2033. This growth is being driven by increasing global trade, maritime security concerns, and the adoption of advanced surveillance technologies such as radars, drones, and satellite monitoring systems. Moreover, the global shipping industry is now on the frontlines of a new kind of conflict — one defined by economic coercion, shadow fleets, and contested logistics – a durable competition where adversaries seek control and influence over global supply chains. As tariff regimes expand and national security policies increasingly target commercial vessels, maritime operators are being forced to navigate a risk environment shaped more by geopolitics than wind and weather. Infrastructure of global trade Trade disruptions are no longer accidental by products of diplomacy — they are deliberate policy levers. Tariff escalation between the U.S. and China, sanctions on Russian oil, and Houthi attacks in the Red Sea are not isolated threats; they signal a new normal in which governments treat the shipping industry as a tactical asset. From China's military-civil fusion shipbuilding policies to LOGINK, its state-run maritime surveillance network, the very infrastructure of global trade is becoming entangled in nation-state agendas. Contested logistics: Struggle for global economic stability The current maritime threat landscape involving contested logistics contains strategic positioning The current maritime threat landscape involving contested logistics encompasses strategic positioning across critical chokepoints and infrastructure. The statistics are sobering: major shipping companies reported traffic through the Suez Canal dropped by 66% as of September 2024 due to Houthi attacks, with J.P. Morgan estimating shipping costs have surged significantly, particularly from Asia to Europe, nearly five-fold. Regional maritime security issues These developments illustrate how foundational industries, such as shipbuilding, semiconductors, and rare earth minerals, have become battlegrounds in a broader geopolitical struggle where a cascade of effects have the potential to destroy economies. For example, a military blockade of Taiwan — where Taiwan Semiconductor Manufacturing Corporation operates — would impact every company dependent on advanced semiconductors. This interconnectedness means that what may, on the surface, appear to be regional maritime security issues, can be much more — the potential for global economic disruption across multiple industries.  Monitoring of Arctic fleet movements Shadow fleets operated by sanctioned states rely on tactics such as false flagging, frequent ownership changes New threat vectors are coming into focus as the seas expand. As the polar ice caps melt, new Arctic shipping lanes are opening, with a large portion of traffic driven by Russian vessels. These routes present unique surveillance challenges due to their remote nature and the limited presence of traditional maritime enforcement bodies. Monitoring of Arctic fleet movements and infrastructure developments is essential for maintaining security in this emerging corridor. Concerns about dual-use capabilities and strategic readiness Shadow fleets, illicit networks, and military-grade commercial vessels represent real risks, posing challenges in the areas of regulatory compliance, insurance viability, and operational safety. Shadow fleets operated by sanctioned states rely on tactics such as false flagging, frequent ownership changes, and manipulations of the Automatic Identification System (AIS). By turning off transponders, spoofing locations, or falsifying data, these vessels can effectively vanish from traditional tracking systems. This disappearance makes ships harder for authorities to trace and easier for adversaries to exploit for sanctions evasions and/or covert logistics. China's commercial fleets increasingly mirror military standards, raising concerns about dual-use capabilities and strategic readiness under the guise of trade. The need for a new risk framework To navigate this new threat landscape on the high seas, organizations must adopt a new kind of visibility For logistics and shipping pioneers, these implications are profound. This is no longer about simply avoiding sanctioned cargo — it's about forecasting how governments will act and how quickly those actions can alter operations. Vessels may be commandeered, sanctioned, or rerouted without warning. Insurance may evaporate. Contracts may become liabilities. To navigate this new threat landscape on the high seas, organizations must adopt a new kind of visibility — one that models the cascading effects of tariffs, military requisition policies, and enforcement shifts. This is where Open-Source Intelligence (OSINT) becomes indispensable. Real-time context on geopolitical risks OSINT draws from publicly available data -- including satellite imagery, port registries, and social media — to provide real-time context on geopolitical risks. It can be used to track vessel flagging and ownership changes, monitor transshipment hubs, and surface anomalies in crew rosters and employment histories — indicators often tied to sanctions evasion or illicit activity. AIS anomaly detection reveals when ships "go dark." Satellite imagery exposes vessels operating without transponders. Tracking shifts in vessels' flagging or changes in crew manifests can signal risk before it hits operations. Early indicators of disruption OSINT supports risk modeling by revealing trends like flag-of-convenience usage, secondary insurance For insurers and regulators, OSINT supports risk modeling by revealing trends such as flag-of-convenience usage, secondary insurance underwriting in high-risk zones, and affiliations with known bad actors.  OSINT doesn't just enhance compliance — it enables foresight, empowering industry players to anticipate when and where governments will act. Now, tariff announcements, sanction designations, and strategic military exercises are not isolated datapoints — they're potentially early indicators of disruption. Maritime situational awareness is a business imperative The age of separating business risk from political risk is over. Global shipping is now a domain of contested logistics where the rules can change as fast as a sanctions update or new enforcement directive. Companies that integrate OSINT into their operational planning gain the ability to model and mitigate threats proactively. Those that don't may find themselves caught in the wake of potential financial, operational, and reputational harm. The shipping industry needs access to the same kind of threat modeling governments use to act. In an era of growing complexity, the role of OSINT in securing global shipping networks cannot be overstated.

A survey conducted by Blackhawk Network finds the average shopper plans to spend almost half of their holiday budget to buy gift cards this year versus only 39% in 2023. The global gift card market was valued at $1.3 billion USD in 2023, and it is projected to reach more than $5.2 billion USD by 2032. Fraud - a growing concern While gift cards continue to be top of mind for consumers for streamlined gifting, gift card fraud is a growing concern for consumers and businesses alike. According to the U.S. Department of Homeland Security’s Homeland Security Investigations (HSI) unit, gift card fraud, perpetrated by Chinese and other organized retail theft (ORT) rings, can be attributed to losses in the hundreds of millions of dollars globally, and is being used to fund other illicit crimes such as drug and human trafficking. The retailers implement procedures to mitigate attacks. Using data insights to detect emerging threats and identify hidden connections is among the ways retailers can protect the integrity of their gift card programs. How gift card fraud is manifested Typical physical gift card scheme involves purchasing items using stolen credit cards  Gift card fraud occurs both at physical locations and online. A typical physical gift card scheme involves purchasing items using stolen credit cards and then returning the items for store credit or gift cards. While some stores have strict and well-enforced return policies to ensure that only customers entitled to refunds receive them, fraudsters employ fake tracking ID (FTID) tactics that focus on bypassing identification checks during returns, enabling them to return stolen merchandise or exploit refund policies.  They use a combination of fake IDs and altered receipts or rely on lax return processes to achieve their goals. Once gift cards are obtained, criminals can sell them at a discount or use them for personal purchases, effectively converting stolen goods or false claims into untraceable funds. Tactics to convince consumers One tactic involves draining a gift card by obtaining the barcode, Card Verification Value (CVV) number, personal identification number (PIN), or activation code from beneath the slim cardboard packaging. Once they obtain the code(s) from physical cards, they reseal them, monitor online for consumers to buy and load the cards, then spend the balances before the consumers can. Some merchants have sought to combat this by keeping store-branded gift cards behind the checkout counter, handing them out after purchase. However, this approach can be costly and inconvenient for both retailers and customers, as it requires additional resources for in-store management and potentially slows the purchasing process. Other online tactics involve people who misrepresent themselves in a variety of phishing scams to convince consumers to purchase gift cards, then provide the card details to others who then drain the cards. Scammers tell the victim which gift card to buy (and where). They might say to put money on a card for an online store, a streaming service, or a specific retail store. These scammers often work as part of an organized crime network. Retailers leveraging open info, AI, to combat gift card fraud Retailers are empowered to improve the monitoring and analysis of gift card transaction patterns A growing number of retailers are leveraging publicly available (PAI) and hard-to-reach data and analytics to extract key insights that help fight various forms of gift card fraud and stay ahead of evolving fraud tactics. With such tools, retailers are empowered to improve the monitoring and analysis of gift card transaction patterns, identify anomalies, and implement proactive measures to prevent fraudulent activities before they can impact consumers and sales revenues. Retailers need this type of approach in their efforts to battle scammers, who continue to refine tactics for draining gift cards and committing other types of retail fraud. Beyond simply refining their techniques, fraudsters continue to advance their use of technology to commit their crimes. For example, cybercriminals also use bots to perform brute force attacks on gift card websites. They are increasingly using AI to perpetrate gift card fraud. Leveraging Latest AI And LLMs Retailers need to continually upgrade their fraud-fighting strategies and technologies as well. They can lean into PAI and analytics, in conjunction with existing security operations and investigations, to safeguard the integrity of their gift card programs and demonstrate their commitment to customers, reinforcing brand trust. In addition to leveraging the latest versions of AI and large language models (LLMs), retailers can take advantage of open-source intelligence (OSINT). By leveraging PAI and difficult-to-obtain data with analytics, brands are using OSINT to more quickly seize on evolving threat patterns to recognize current and shifting fraud schemes and stay ahead of evolving fraud tactics. In this way, the AI operates as a resource multiplier, compiling and processing data at faster-than-human speeds, while enabling the ability to extract actionable insights at scale. Users can make more accurate and timely decisions. Retailers need to upgrade their fraud-fighting strategies and technologies. Safeguarding gift cards, customer trust, and Brand integrity OSINT can inform retail security managers, loss prevention directors, fraud investigators, and others to help spot and deter gift card fraud. By using AI to detect patterns and anomalies, OSINT solutions can help fraud specialists spot patterns of suspicious activity that may indicate distinct instances of fraud. AI further helps fraud specialists identify members of ORT rings by uncovering hidden connections among seemingly unrelated individuals and transactions. The market for retail gift cards is large and continues to grow, and so too, is the gift card fraud threat. By adopting OSINT for fraud prevention, retailers can stay ahead of tech-savvy criminals, safeguarding gift card revenue streams as well as customer trust and brand integrity.

Security professionals are recognizing the intelligence value of leveraging publicly and commercially available information. This information can now be accessed more effectively from typically hard-to-reach regions. Also, the technological capabilities have matured in our age of artificial intelligence, machine learning, and data science. Intelligence has historically been based on classified data. However, today’s unclassified data, including open-source intelligence (OSINT), is increasingly being used to provide context and queuing for other types of intelligence. Advanced identity intelligence Babel Street is a technology company providing advanced identity intelligence and risk operations using an AI-enabled data-to-knowledge platform to unlock insights from a flood of data. The company provides advanced data analytics and intelligence for the world’s most trusted government and commercial organizations. Experts have predicted that by 2025 over 463 exabytes of data will be generated each day globally The sheer volume of data is growing exponentially. Experts have predicted that by 2025 over 463 exabytes of data will be generated each day globally. Not only are we seeing exponential growth in the volume of data, but there is also disparity in the veracity and the variety of data. This is being compounded by the ‘app economy’ in which data is created in a new format for every app added around the globe. Human language technology “The problem is that the data ‘junk’ and the ‘crown jewels’ are in the same bucket, and government and commercial entities need better and faster ways to extract intelligence from these torrents of data,” says Farid Moussa, VP, Strategy & Public Sector, Babel Street. Prior to joining Babel Street, Farid retired from the National Security Agency (NSA). He has guided video, image, speech, and text analytics (VISTA) and developed an appreciation for human language technology. An elusive source of data is the Dark Web, where every user, by design, is attempting to obfuscate their identity, and bad actors are hiding much better. “This presents a cat and mouse game – the cat must be smarter than the mouse, but the mouse is continually getting smarter,” says Moussa. Intelligence tools for data analysis SIGINT and HUMINT – while both vital – are also the most expensive forms of intelligence There are several intelligence tools for analyzing data. One of them is signals intelligence (SIGINT), which refers to electronic transmissions collected by ships, planes, ground sites, or satellites. Another is human intelligence (HUMINT), which is collected in a human-to-human fashion. Open-source intelligence (OSINT) is obtained by searching on topics or entities of interest that are publicly available on the Internet at large. Today, these various categories are often done in ‘silos of excellence.’  However, the best practice is using all forms together in a holistic fashion. SIGINT and HUMINT – while both vital – are also the most expensive forms of intelligence, while OSINT, which is growing in importance, is most cost-effective. All are vital forms of intelligence; OSINT is complementary and crucial to holistic intelligence practices. Holistic intelligence practices When it comes to physical security of people and places, OSINT has become a critical source of actionable information. Security directors leverage Publicly Available Information (PAI) to safeguard against threats to individuals, property, travel routes, and event sites. By monitoring PAI, security teams can detect and respond to potential dangers, including during and after events where thorough preparation is vital. Online information can contain warning signs of impending threats. It informs security professionals in uncovering digital traces, confirming intentions, and addressing risks across language barriers, ensuring proactive risk management for the protection of people and property. Role of Natural Language Processing (NLP) The Internet and social media were mostly English language by default, but that has changed exponentially Natural Language Processing (NLP) is a crucial capability that has evolved to recognize the richness and variety of words and names in multiple languages and scripts, and their use across cultures. Using machine learning and linguistics algorithms, the technology simultaneously considers numerous types of name variations. At one time, the Internet and social media were mostly English language by default, but that has changed exponentially.  Babel Street’s world-class entity matching technology measures over 100 features to calculate the similarity of entities across multiple languages. Despite advances in data management and the cloud, there are still multiple challenges and complexities with integration of these data elements. Challenges include spelling variances/phonetics, language translation issues, criminal evasion, human error upon input, typos, etc. Accessing data from a scattered landscape While there have been advancements in cloud technologies, agencies utilizing open-source data are typically working within a highly scattered data landscape and must use a wide array of tools to get at the relevant pieces. This fragmentation makes it difficult to run analytics and apply AI and machine learning at scale in order to derive actionable insights.  Unstructured and relationship data are visualised through advanced link analysis As with many disciplines, artificial intelligence (AI) is changing the game when it comes to intelligence. NLP and AI algorithms are employed to enhance datasets for greater quality, usability, and completeness. Unstructured and relationship data are visualized through advanced link analysis, geographic heat maps, influential entity carousels, topic clouds, and patterns by time and day. Geographic heat maps The advanced algorithms accurately score and prioritize critical entities within the relationship network while providing the citations from which an AI/ML-based decision was made. “With the democratization of AI, the world is becoming flat,” says Moussa. “Just like the most prosperous countries, even the poorest countries have the most advanced capabilities to do damage. Third-world economies often present a scenario where the financial gain of nefarious schemes and low-to-no regulation combine to incentivize bad actors.” The Challenges of Name Matching Identity has been an ongoing challenge for intelligence analysis due to the vast complexity of linguistics, spelling and cultural variances, human error, as well as human evasion. Technology and data science approaches are maturing, however machine translation can still struggle with meaning. The best-of-breed natural language processing capabilities run against the data while it still is in its native language. This minimizes the occurrence of analytic errors caused by inaccurate machine translations. This minimizes the occurrence of analytic errors caused by inaccurate machine translations It’s tempting to think that name matching is like doing a keyword search. The complexity of language makes it more challenging. New names are constantly created, with multiple spellings and no set of rules to encompass how names are formed. They are variable across languages, scripts, cultures, and ethnicities. Culturally specific nicknames and aliases add to the complexity. Replacing human involvement The investigation of the Boston Marathon Bombing in 2013 spotlighted an example of the significance of intelligence analysis. Even though the FBI had issued a detain alert for Tamerlan Tsarnaev back in 2011, Tsarnaev managed to travel to Russia in January 2012; and in July 2012, he returned to Boston. He was not detained on either occasion because there were too many names on the lists, and Tsarnaev’s last name had been spelled differently from the way it was on travel documents, thus enabling him to get through security. With the Internet, social media, and the dark web, there’s been an exponential increase in public communications in various languages, adding significantly to the amount of analysis required to keep societies safe. Name matching, using AI, analyses multiple contextual data points across languages to arrive at matches. Name matching, using AI, analyzes multiple contextual data points across languages to arrive at matches A common misconception is that this technology will replace human intelligence. “It’s more accurate to recognize its role as a force-multiplier, allowing humans to focus on the on the harder problems and/or vetting the results of AI,” says Moussa. “The technology can efficiently analyze massive volumes of data and distill it into actionable information in a timely manner. It augments human capabilities, enabling analysis at speed and scale beyond human capacity, without replacing human involvement.” Commercial Technology to the rescue “When it comes to threat and identity intelligence, we face a risk-confidence gap, underscored by the challenge of integrating traditional tactics with the modern digital landscape,” adds Moussa. “We cannot ‘hire’ our way out of this problem. Instead, it is imperative that we adopt technology to scale our efforts and free humans to solve the harder problems that machines cannot solve yet.” The public sector loves to build things, but there are time-to-value and return-on-investment considerations to the ‘build or buy’ decision. When commercial technology can be leveraged by government, it frees resources up to work on problems that the commercial world hasn’t yet figured out, says Moussa. “The public and private sectors need to come together – one team, one nation, working together with mutual trust and collaboration,” he says.