Webinar - Feb 12th - Harnessing Data and AI to Fight Financial Crime in Payments
Harnessing Data and AI to Fight Financial Crime in Payments🚀 Join us for an insightful webinar hosted by Microsoft, in collaboration with our partners Quantexa, iPiD, and EY. We'll explore the latest trends in financial crime within the payments industry, including progress on the EU's Verification of Payee (VOP) deadline and its implications. 🌐 Event Details: 📅 February 12th, 2025 🕒 11:00 AM – 11:45 AM CET Don't miss out on this golden opportunity to fortify your knowledge and network with industry leaders. Secure your spot now! 🔗 Sign Up Now: Harnessing Data and AI to Fight Financial Crime in Payments #Microsoft #MicrosoftVirtualBriefing #Data #Financial #Crime #Payments #Qalliancespowered
📣Upcoming Webinar: The Biggest Challenges in Data Quality: How Far Can AI Go to Solve Them? 📣
In this webinar, Dan Onions, Global Head of Data Management at Quantexa, and Martin Maisey, Head of Data Management EMEA, will delve into the pressing question on every data professional's mind: "How can AI help me?" Unlock the full potential of your data strategy: As AI technologies, particularly LLMs, become increasingly integral to data management strategies, ensuring the quality and reliability of these systems' outputs is paramount. Our experts will explore the critical role of foundational data quality in harnessing AI effectively and responsibly, and address key challenges, such as achieving consistency and accuracy in AI-generated outputs and aligning them with regulatory standards already on the horizon. Attendees will gain insights into practical applications of AI in the real world, understanding how to make AI outputs on data trustworthy across the entire organization. Register Your Place Here: The Biggest Challenges in Data Quality: How Far Can AI Go to Solve Them? (quantexa.com)
QuanCon24 On-Demand: Tackling Financial Crime and Fraud In The Era Of AI
About QuanCon24 In an era of disruption – from supply chain disruption, geopolitics, cost of living, and elections – organizations face a multitude of critical decisions that can lead to increased risk, missed opportunities, or dead ends. Organizations must evolve to make fast confident decisions to become efficient, resilient, and reach goals before the competition. But so much more is possible with the right data in the right context. Now, you can watch our key sessions on-demand. Watch now. About this session This expert panel, moderated by Quantexa’s Chief Marketing Officer Matt Hooper, focused on how macroeconomic shifts are impacting risk and governance across industries. It featured four industry trailblazers: Jocelyn Norval, Global TM and Screening Lead, ING Kai Schrimpf, Head of Monitoring and Screening Controls, Morgan Stanley Mark Cheeseman, Chief Executive Officer, Public Sector Fraud Authority Neil Jones, Head of 1st Line Financial Crime, Danske Bank There is a multitude of socioeconomic factors that are impacting the ecosystem of financial and economic crime activity: the reshaping of the governance, risk, and compliance landscape; an impactful year from a political perspective across the world; ongoing market volatility for the last few years – to name a few. But AI and innovative technologies hold some answers to overcoming these challenges and effectively tackling financial crime and fraud in a consistently evolving landscape. Join Matt Hooper, Chief Marketing Officer at Quantexa, and experts at private and public sector organizations from across the globe to discover how the transformative power of generative AI and new technologies can counter financial and economic crime. Key topics: The importance of taking a holistic and integrated approach to tackling economic crime and embracing AI How the experts are looking at technology to meet today’s demands and future-proofing approaches The innovative work around counter fraud and anti-money laundering and lessons learned from the experts’ decision intelligence journeys The potential and future vision for organizations to continue fighting economic crime, challenges and opportunities that may arise, and why public-private partnerships are integral to success Watch Tackling Financial Crime and Fraud In The Era Of AI on-demand and discover our key sessions from QuanCon24.KPMG: AI boosts supply chain agility
Artificial Intelligence (AI) has the potential to enhance supply chain agility, according to a new KPMG report titled “Raise Your AI Short Game to Boost Supply Chain Agility.” The report emphasizes that businesses are grappling with compound volatility, necessitating the need for supply chain flexibility. AI emerges as a technology that can help companies anticipate market volatility, make complex network decisions, and achieve business objectives in the short term. In fact, 57% of the executives who participated in the 2023 KPMG Global Tech survey, stated that AI will help them achieve their short-term goals. Read more here … https://outlookseries.com/A0769/Services/3395_KPMG_AI_boosts_supply_chain_agility.htm Quantexa's Donna Goodwin shares her thoughts …
Quantexa's AI Roundup - 2023
In July 2023, Quantexa announced a significant investment into its Artificial Intelligence (AI) capabilities (Quantexa Bringing Total Investment in AI R&D to over $250M by 2027). Since this announcement, there has been significant advancement in the AI space, and growth in some of the core AI capabilities at Quantexa. Alongside the significant growth of the NLP capability, Quantexa’s Analytical Innovation team have completed the MVPs of their three flagship products which are now released under experimental. These tools use Quantexa networks to uncover insights: the Entity Resolution AI suite; Q-Knowledge Graph and Shell Company Detection. In this round up post, we introduce the three products and demonstrate how they can add value to your Quantexa deployment. The Entity Resolution (ER) AI Suite The ER AI suite provides a series of tools for analysing the outputs of Quantexa’s ER product and provides suggestions for improving the configurations powering the ER using AI. In particular, the tool can detect overlinking and underlinking in Quantexa Entities and their root causes. The overlinking detection tool is powered by machine learning with features based on the qualities of the Entity’s constituent record-compound graph (read more about using the Entity Quality Overlinking tool for the first time). These graph-based features include the use of several complex graph algorithms (e.g., the Stoer-Wagner algorithm) to find shapes which are indicative of overlinking. Such shapes include ‘bridges’ in the network which incorrectly link Entities together, as well as graphs with very long paths. Statistical techniques can then be applied to determine what compounds or data points may be leading to this overlinking. The underlinking tool uses sophisticated graph algorithms to find ‘Super-Entities’ – Entities which should be formed of several existing Entities. This helps the user to identify template changes to merge such entities together in future ER runs. Q-Knowledge Graph Q-Knowledge Graph is a series of tools for analysing large-scale Quantexa Entity and Document graphs. It scales to billions of nodes and edges and uses sophisticated optimisation techniques to provide extremely fast implementations of core graph transformations and algorithms (including page rank). Not only does the tool provide access to commonly used graph algorithms out of the box (for example, PageRank) – it also provides a connection to common graph learning libraries such as PyG. This enables several use cases across Risk, KYC and MDM and has already been deployed for transactional use cases in a global bank. It will also be a core back-end component of a number of upcoming Quantexa AI products. Shell Company Detection The Shell company detection tool uses machine learning to identify shell companies, using characteristics of the local ego-networks of the companies. The model uses a combination of structural features (e.g., links to known shell directors); temporal features (e.g., patterns of director resignation) and static features (including the size of the corresponding corporate registry Document). For more information, see What can Network structure tell us about risk? The current model is built specifically for the UK and Singapore and can encapsulate some behaviours specific to shells in these jurisdictions. Models focused on other jurisdictions are coming this year. Upcoming AI releases The NLP team at Quantexa are also developing a machine learning pipeline called Text2Networks for working with unstructured data, which will be available in the next major release of Quantexa. The Text2Networks pipeline is a highly-configurable pipeline of ML models for mapping any unstructured textual data into a graph. The pipeline detects, labels and organizes people, places, and things in the real world – the supported Entity types include People, Locations, Companies and Geo-political organizations. With text2networks integrated into the core Quantexa product, our users will be able to incorporate any textual data source that is important for their business. Concrete example could include global news, intelligence reports, and Suspicious Activity Reports (SARs). There are several tools in development, including further tooling within the ER quality suite and Q-Knowledge Graph, as well as other risk models such as the SME detection tool which will be coming in later releases of Quantexa. To keep up with the latest releases, be sure to follow our Release Announcements topic.Gen AI and the evolving role of marketing - Capgemini
The majority of marketers (62%) believe that generative AI will augment human creativity, enhancing unique human qualities such as intuition, emotion, and context understanding. Organizations already investing in generative AI for marketing dedicate 62% of their total marketing technology budget towards it, seeing this breakthrough technology as a catalyst for creativity and innovation in marketing. That’s according to Capgemini Research Institute’s latest report ‘Generative AI and the evolving role of marketing: A CMO’s Playbook’, which reveals that half of organizations have already set aside specific budgets and almost half (47%) have allocated teams for the implementation of generative AI in marketing. Quantexa's Matt Hooper weighs in: Capgemini: 60% Integrating Generative AI Into MarketingGartner: 39% of Organizations Currently Use AI in the Finance Function
Sixty-eight percent of finance organizations are using AI or plan to use the technology, according to a recent survey of finance leaders by Gartner, Inc. A May 2023 survey of 133 finance leaders found that 39 percent of respondents are using AI/machine learning (ML), and an additional 29% of respondents said AI/ML is planned (see Figure 1). Read more here: Gartner: 39% of Organizations Currently Use AI in the Finance FunctionGoogle Banking Survey: C-Suites & Boards More Involved in Tech Decisions with AI
New research explored the sentiment towards generative AI (gen AI) in banking among North American banking executives and consumers. The study, based on a survey of 350 banking executives responsible for genAI decisioning and more than 2,000 banking consumers in the United States, found broad interest in gen AI technologies as a way to improve operations and the customer experience, while some barriers and risks remain. The majority (92%) of banking executives stated there is high demand for gen AI within the banking industry, with 95% stating it has the potential to transform the industry. Increased interest in gen AI is driving senior leadership, like C-suite executives and boards of directors, to get more involved in technology and IT decisions, according to almost all banking respondents (96%). Quantexa's Parsa Ghaffari weighs in: Google Banking Survey: C-Suites and Boards More Involved in Tech Decisions Due to Heightened Interest in Gen AIIDC Revenue for AI software Will Reach $279B in 2027
A recent forecast from International Data Corporation (IDC) shows that the worldwide artificial intelligence (AI) software market will grow from $64 billion in 2022 to nearly $251 billion in 2027 at a compound annual growth rate (CAGR) of 31.4%. The forecast for AI-centric software includes Artificial Intelligence Platforms, AI Applications, AI System Infrastructure Software (SIS), and AI Application Development and Deployment (AD&D) software (excluding AI platforms). However, it does not include Generative AI platforms and applications, which IDC recently forecast will generate revenues of $28.3 billion in 2027. A recent IDC survey found that, in the next 12 months, roughly a third of respondents believe that organizations will prefer to buy AI software from a vendor or use in-house support alongside vendor-supplied AI software for specific use cases or application areas. This indicates a growing demand for AI solutions and highlights the need for customized approaches based on individual business requirements. Quantexa's Parsa Ghaffari weighs in with his thoughts: IDC: Revenue for AI Software Will Reach $279B in 2027Gartner: CISOs Need to Champion AI TRiSM to Improve AI Results
By 2026, organizations that operationalize artificial intelligence (AI) transparency, trust and security will see their AI models achieve a 50% improvement in terms of adoption, business goals and user acceptance, according to Gartner, Inc. Speaking at the Gartner Security & Risk Management Summit in London today, Mark Horvath, VP Analyst at Gartner said, “CISOs can’t let AI control their organization. AI requires new forms of trust, risk and security management (TRiSM) that conventional controls don’t provide. Chief information security officers (CISOs) need to champion AI TRiSM to improve AI results, by, for example, increasing the speed of AI model-to-production, enabling better governance or rationalizing AI model portfolio, which can eliminate up to 80% of faulty and illegitimate information." Felix Hoddinot, Chief Analytics Officer with Quantexa added, “The TRiSM is a great model highlighting requirements for responsible AI solutions. Quantexa’s Decision Intelligence platform is a great way to achieve these requirements. The transparency delivered by our contextual AI approach drives trust and enables effective AI risk management. Quantexa’s unique capabilities to embedding data security within our Entity Resolution offering is more important now than ever as we deploy solutions with ever larger and more extensive data sets.” Read more here: Gartner: CISOs Need to Champion AI TRiSM to Improve AI Results
