🎥 Webinar: Why Entity Resolution & Graph Based Analytics is Crucial for Modern Fraud Detection
4:00 PM BST | 5:00PM CEST | 11:00AM EDT Save your seat Join Clark Frogley, Global Head of Fraud Solutions, and Shyam Bhatt, Head of Fraud Solutions at Quantexa for a webinar exploring why Entity Resolution and Graph-Based Analytics is crucial for modern fraud detection, and how to apply these tools. Insurance fraud doesn’t happen in isolation — and detecting it shouldn’t either. Modern insurance fraud demands modern detection. Insurers now need to evolve their fraud strategies and move beyond claim-by-claim analysis to uncover wider schemes that span across claims, policies, and entities, through entity resolution and networks. Join Quantexa's fraud experts for a live demo and in-depth conversation on how advanced entity resolution and network analytics are powering a new era of contextual decision intelligence. During the session, you'll explore how cutting-edge software is enabling insurers to uncover hidden fraud rings, spot anomalies earlier, and scale their defences — all in real-time and without extensive manual investigation. By attending this webinar, we will explore: Learn how moving beyond traditional, siloed claim-by-claim analysis to entity-centric, graph-based approaches can uncover complex fraud schemes that span multiple claims, policies, and actors. Experience a hands-on demonstration showing how cutting-edge software uses contextual decision intelligence to detect hidden fraud rings, spot anomalies earlier, and reduce reliance on manual investigation. Gain insights into the advanced technology stack enabling scalable, real-time fraud detection — including practical applications for fraud analysts, data scientists, and technology leaders. Save your seat Community resources to explore 👋Join the Insurance Fraud User Group: 📖 From the Community Library: Investigating Network Fraud: 4 Key Areas for Investigators Handling Large Networks for Investigations & Tasks The changing shape of fraud in the UK market - ABI Fraud Statistics Lessons Learned from a Streaming Lending Fraud Project Optimizing Entity Resolution and Graph Expansion
Quantexa Recognized as a “Luminary” in Celent’s 2024 P&C Insurance Fraud Detection Solutions Report
We are thrilled to share that Quantexa’s Fraud Detection solution has been recognized as a "Luminary" in Celent’s 2024 P&C Insurance Fraud Detection Solutions Report. This prestigious recognition underscores our leadership and innovation in the insurance industry. Our Fraud Detection solution, powered by advanced AI and machine learning technologies, continues to set new standards in the fight against insurance fraud. Celent’s recognition highlights not only the strength of our technology but also the significant impact we are making in helping insurers around the world protect their businesses from fraud. This achievement is a testament to the power of our platform and reinforces the value we deliver to our clients. We are proud to be at the forefront of insurance fraud detection and look forward to continuing our journey of innovation. Read more about the annoucement please read the press release here.
Join the Conversation: Highlights from Solution & Industry User Groups 💬
Did you miss out on the latest discussions in our Financial Crime, Insurance, KYC and Data Management Specialist User Groups? Here's what you might have missed: Join a group to stay up to date: 💵 Financial Crime 🛡️ Insurance 🙋♀️ KYC - Know Your Customer 💻 Data Management
Fraud for Thought: The Emerging Threat of Synthetics in Insurance
In a compelling interview from my "Fraud for Thought" podcast, we dive deep into the world of fraud prevention with who has decades of experience in the field - particularly with regards to emerging digital fraud typologies. We explored one of those such themes - Synthetics - and the risk it now poses to the insurance industry. Below are key excerpts highlighting some of the most crucial insights shared during the discussion. On Emerging Threats in Identify Theft & Synthetic Fraud… Alex: What recent and emerging trends are you seeing used by cyber criminals with regards to identity theft and synthetic fraud? Steve: It's been interesting to see the shift take place from the financial sector to the insurance space. Fraudsters will always go where the money is and they realize that's the insurance space. The insurance space, while very mature from an organizational perspective, has always dealt with fraud. But not like the fraud the financial sector has seen.We're seeing these threat actors coming into the insurance space with things such as synthetic identity, deep fakes, and generative AI - being targeted by technology that it just hasn't quite seen yet.The banking sector has been seeing it for the last five or six years and the insurance base is now seeing it. And it's what I call the 'fraud tsunami' where they're seeing the waves come in and that's the fraudsters kind of playing with things, understanding the insurance first of all, understanding that insurance is where the money really is, what the controls are, what the program is, and then they'll launch their attacks with technology.We're seeing a lot of things like bot attacks now that are being used and scripted to apply for a policies for example. Whether they are successful or not, it doesn't really matter to them. It's a testing strategy for them to understand again what the controls are that insurance has in place, to see what they get through. And if they get a policy applied, they may not do anything with it for awhile. They may just sit on it and again understand how the program works, where the control gaps are, what the thresholds are. We call those accounts 'sleeper accounts': they sit there and wait for the activity on the synthetic side.So you're seeing traditional identity theft and you're seeing synthetic identities that are now being, and have been used, groomed, and matured in the financial sector now moving into the insurance space. I was speaking with a large insurance provider and discussing some synthetic identity identifiers and they quickly ran their identifier and found a $5,000,000 life insurance policy that they paid out to an individual that does not exist. They started looking more and more into it and found roughly $40 million in death benefits they paid out to individuals who never lived.That is a huge red flag for the insurance industry: that this threat is coming to them, into their space and will start to expand and land as they move forward. Key takeaway : The utilization of technologies like deep fakes and generative AI by fraudsters is of paramount concern to Quantexa's insurance customers who are taking a proactive stance in preventing and combatting such threats. They are exploring the accessibility of Gen AI tools to fraudsters and the potential implications. On Adapting Tactics with Technology… Alex: From what you've seen, how are insurance companies adapting their tactics to help defeat the fraudster and what strategies and technologies are they putting in place to enhance that capability? Steve: To combat technology, you need technology. The old days of the human firewalls, like massive fraud shops of hundreds of analysts working reports and cues (that really produced a lot of false positives) is no longer sustainable or scalable. Especially with the level of fraud that is coming to the insurance space; it will be equivalent to what the financial sector saw in the last two decades. So, you have to have the appropriate technology. It's pretty easy. The insurance companies just need to look to the banking sector again, what do they do? It's about account onboarding, right? You want to keep the bad guys out of your account at all costs because once they're in the account, then it's very difficult to mitigate them and it's expensive to move them out of out of your portfolio. You're looking at things at the onboarding stage, which is what I call a proactive stance versus reactive. To get into the proactive stance where you eliminate the fraud threat altogether you don't approve the application for the policy, you deny them at the door; but how do you do that? How do you prove fraud intent? This may look like fraud, but until they do something, is it really fraud? Just because I'm carrying a firearm doesn't mean I'm going to go out and commit a homicide, but when I do, then then it becomes a homicide. And so it's very difficult for individual for banks and technology to determine what we call the intent. They're looking at things and tying the data together, such as device information and behavioral biometrics. We're looking at non-traditional data sets instead of your traditional data sets like credit bureaus or large data aggregators. You're looking for things that that would help you tie things together, which ties in the concept of entity resolution. How do you tie all that technology together? How do you tie the data that you've obtained through those technology into a workable queue for your analyst? Because the false positive rate can be somewhere in the 95 percentile. You have to understand the data you're trying to acquire, what you're going to do with it, and then how to use that data in the truth data format to retrain your models and tighten your defenses. Key takeaway: Quantexa customers are going beyond identifying and probing fraud among their existing clientele to preemptively thwart dealings with dubious clients. This requires a proactive approach to refraining from underwriting policies for potentially fraudulent individuals intending to exploit their services. On Balancing Security and Convenience… Alex: How are some of those technologies helping insurers strike that balance between customer convenience and the stringent validation that should be in place when it comes to identity verification? Steve: It's most important to understand the connections with the data (right back to entity resolution) - understanding that these are transnational groups that are attacking at scale. When you attack at scale there are relationships and connections between those online applications or between those accounts. The trick is to understand what those relationships look like and so you know you're looking at again mentioned device identification for example, individuals who try to spoof their computers. Synthetics have been groomed in the financial sector for the last 20 years, which are truly just data points. Now what we've seen is deep fakes are creating now both visual and audio for the actual synthetic identity: now the synthetic identity has a face and a voice. You've seen a lot of the technology come around about liveliness checks, send us a picture of a selfie, turn your head, go on Webex, go on Teams, whatever it might be to prove that you really are a human. The technology has progressed so quickly in the last two years that's easily defeating most technology that the banks and insurance companies have in place to defend. Banks have been doing that for awhile now through organized groups. The insurance companies do have some organizations within their within their scope of business and the analysts and investigators do talk to each other. But I believe it's very much in an informal structure. There needs to be some kind of formalized structure to take all this data, put it all together and say, we know this is a bad actor because they attacked insurance company A and inform insurance Company B, right? The banks have made that mutual connection in a relationship to say, listen, we're going to free fall together versus looking at as a competitive disadvantage like sending a bad guy from us to them is better for them. That doesn't happen in the banking world these days. They work together from a consortium's perspective to identify those data sets. Key takeaway: Contemporary fraud is driven by transnational groups and advanced technologies like deep fakes. Combatting this demands sophisticated methods such as entity resolution to uncover patterns of fraudulent activity across online applications and accounts, in order to provide a comprehensive approach that balances stringent validation with customer convenience. Conclusion My discussion with Steve highlighted critical insights into the emerging threats facing the insurance sector. Fraudsters are increasingly using advanced technologies such as deep fakes and generative AI to exploit vulnerabilities. This shift necessitates a proactive approach from insurers to effectively counter these sophisticated attacks. Implementing advanced technologies is essential for detecting and preventing fraud before it impacts customers. As these threats evolve, industry collaboration becomes crucial for sharing intelligence and developing robust defenses. Staying informed about these emerging threats and the proactive measures needed to combat them is vital. By understanding and implementing the latest technological advancements, we can collectively safeguard against sophisticated fraud and ensure a secure and trustworthy insurance landscape. Let's work together to protect your interests and strengthen our defenses against these evolving threats. For more Fraud for Thought, visit the Quantexa website: Fraud for Thought It’s time to enhance your strategy to prevent and detect insurance fraud across the enterprise.Catch up on the latest from our solution & industry user groups 💬
Here's what you might have missed this month from our Data Management, Financial Crime, Insurance, and KYC Specialist User Groups: How Can Decision Intelligence Help Identify Medical Provider Facilitation & Collusion? Reimagining Monitoring and Detection Advancing Correspondent Banking Insights: Managing Respondent Banks Risk If you haven’t already, join a user group today to stay up to date: 💻 Data Management Open the door to a truly connected view across all your data assets from across internal and external sources, improve data quality, build applications, and take control of master data. 💵 Financial Crime Unlock value in order to make smarter and more informed risk and intelligence-based decisions. 🔍 KYC- Know Your Customer Shift back to the core purpose of KYC in understanding the risk associated with prospects, customers and their related activity across the life cycle. 🛡️ Insurance Brings together all things to do with insurance at Quantexa and looks to enable customers, partners, colleagues and insurance thought leaders to share expertise. Find more of the best from the Community this month in our monthly digest: Quantexa's AI roundup & the best from the Community in JanuaryHow Can Decision Intelligence Help Identify Medical Provider Facilitation & Collusion?
⚠ Year after year, we’ve sadly seen a rise in medical provider & billing scams costing the industry millions of $$$ each time! Fraud related to medical practitioners using malpractice, shell companies and straw ownerships of clinics is on the rise. We've recently seen many repeated trends, including a specific case totalling over $1m below 👇 ⚙ With the right #contextualdecisionintelligence technology, you can easily spot hidden patterns, connections and collusive networks. Connecting public records, corporate records, exclusions with internal payments, billing and claims data creates a #provider360 / #supplier360 approach to deliver intelligence to stop this before a big court case / significant losses. 👉 Previously disbarred medical practitioners setting up under new licenses and businesses 👉 Practitioners re-appearing a few years after convictions for bribery, corruption, forgery and tax fraud 👉 Shared location and contact details including family associations with risky clinics &/or practitioners 👉 Shell company registrations, multiple company filings and repeated dissolved companies 👉 Company directors with links to new practitioners not yet under investigation 👉 Business links to residential and temporary office addresses, for example medical manufacturers, pharmacies, physicians and more I would love to hear your thoughts on this? ++Catch up on the latest conversations from our Specialist User Groups 💬
Here's what you might have missed this month from our Data Management, Financial Crime, Insurance, and KYC groups: Don't miss our new 'A day in the life of... an Investigator' series 🔎 Entity Quality Management for Data Quality? A Tale of Two Investigations: Transforming Financial Crime Risk Monitoring and Investigations Investigating Network Fraud: 4 Key Areas for Investigators If you haven’t already, join a user group today to stay up to date: 💻 Data Management Open the door to a truly connected view across all your data assets from across internal and external sources, improve data quality, build applications, and take control of master data. 💵 Financial Crime Unlock value in order to make smarter and more informed risk and intelligence-based decisions. 🔍 KYC- Know Your Customer Shift back to the core purpose of KYC in understanding the risk associated with prospects, customers and their related activity across the life cycle. 🛡️ Insurance Brings together all things to do with insurance at Quantexa and looks to enable customers, partners, colleagues and insurance thought leaders to share expertise. Find more of the best from the Community this month in our monthly digest: 📚A day in the life of a... Technical Lead & Best of Community from November
Investigating Network Fraud: 4 Key Areas for Investigators
Following on from my article on why networks are important – I regularly talk with investigators on how best to identify and investigate organised network fraud. I am mindful that there are a lot of seasoned investigators out there so in this article I will be talking basics and from a perspective of using technology only to investigate network fraud. The first principle of investigating network fraud is to have all available data in the hands of the investigators – this sounds quite basic but often we speak to investigators who use different data sources, capabilities, and sources of alerts that are not integrated into one platform. The best technology platforms I have seen take a best of breed approach and provide the ability to integrate easily and onboard data as efficiently as possible to allow for greater data coverage and better investigator efficiency. The second principle is to think of fraudsters as business people, and from that lens we should understand that fraudsters want to “sweat their assets” (vehicles, synthetic IDs, group resources etc.) to make their business (illicit streams of money through fraud) as profitable as possible in the shortest time-frame whilst taking the minimum operational risk. Read the full article here (login required): https://community.quantexa.com/kb/articles/203-investigating-network-fraud If you are not a customer or a partner and would like to see the article, please comment below.Event Roundup: Global Insurance Fraud Summit - Edinburgh
This month, the Quantexa team and customers participated in the Global Insurance Fraud Summit (GIFS). This summit aims to bring together global consortia and insurance organisations as well as law enforcement such as the Insurance Fraud Enforcement Department (IFED) and Interpol. Quantexa and our customers participated in several panels and presentations. One consortium in Asia indicated the importance of bringing together technology, training and operational processes, with the rollout undertaken this time taking into account of all three for maximum benefit to its members. It was also great to hear from our Public Sector customer, who provided learnings on how to tackle fraud as there are commonalities between insurance fraud and public sector fraud. This organisation also stressed the importance of using data correctly in conjunction with accurate entities and networks, highlighting that they had saved close to £311m overall as an organisation. It was fascinating to hear from other countries on how they are tackling fraud, and to hear from David Glawe, the CEO of NICB. The key common threads throughout the majority of the presentations were: Fraud is commonplace across all territories with a huge victim or consumer impact Fraudsters are like business organisations, and like businesses have extended their supply chains, impact and networks globally The use of technology on the fraudster side is increasing, and only by insurance organisations doing the same can fraud be tackled sufficiently It was also great to hear the insurers’ view on these panels as well, with senior executives talking about the importance of a single customer view for use in multiple use cases as well as understanding that at the moment it is a tough financial climate due to inflation. There was an appetite to work together with bureaus, however this process needs to be easier either through the mechanisms of sharing data more easily or understanding global schemes or problems centrally. It was a great pleasure to take part in the Global Intelligence Sharing panel, and during this we discussed how can insurance organisations share more easily, and by sharing it won’t be as easy as sharing data globally due to the many different data sharing restrictions we have globally. Rather, we must start with understanding how we are sharing currently, what learnings we can take from there and then building on this to start sharing modus operandi or common trends.Check out the latest from our Specialist User Groups!
The Quantexa Specialist User Groups provide opportunities to network and join industry and solution focused conversations! Here's what you might have missed this month from our Data Management, Financial Crime, Insurance, and KYC groups: 🥇Quantexa Wins GOLD at Insurance Times Awards!🥇 Perspective: Addressing SEC-Identified AML Program Deficiencies at Broker-Dealers Chris Bagnall's 3-Part Series on Human Trafficking 📅 London Insurance: Quantexa, Accenture & Google Cloud - Contextual next-gen AI insurance market 📅 Allied Market Research Forecasts Insurance Fraud Detection Market CAGR 24% If you haven’t already why not join a user group today: 💻 Data Management Open the door to a truly connected view across all your data assets from across internal and external sources, improve data quality, build applications, and take control of master data. 💵 Financial Crime Unlock value in order to make smarter and more informed risk and intelligence-based decisions. 🔍 KYC- Know Your Customer Shift back to the core purpose of KYC in understanding the risk associated with prospects, customers and their related activity across the life cycle. 🛡️ Insurance Brings together all things to do with insurance at Quantexa and looks to enable customers, partners, colleagues and insurance thought leaders to share expertise. ❗️If you have a suggestion for another Specialist User Group you would like to see, please comment below 😊 Find more of the best content from across the Community in our monthly digest: What Happened on the Quantexa Community in September
