Latest news with #frauddetection
Finextra
27-05-2025
- Business
- Finextra
Training AI Agents Like Behavioral Scientists to Excel at Preventing Scams and Fraud: By Roy Zur
As scams become more advanced and personalized, the tactics used to manipulate individuals are increasingly rooted in behavioral psychology. What once required blunt deception now relies on nuance: fraudsters exploit victims' fears, biases, and emotional vulnerabilities with surgical precision. With fraudsters now equipped with generative AI tools and attacking with psychologically driven tactics, it's not enough for banks to rely solely on traditional fraud detection systems. AI agents need to do more than flag suspicious transactions to keep up. They must be trained to understand people (both victims and scammers) and have the capabilities to deliver personalized insights, warnings, and conversations to help customers recognize and break free from a scammer's influence. Some of the world's largest financial institutions are beginning to realize that this training is necessary. In-house behavioral science teams like those led by Elizabeth Huppert, PhD, from JPMorganChase are now working hand-in-hand with fraud operations teams. The goal: to design technically accurate and psychologically effective intervention strategies. At Charm Security, after years of analyzing transactional data and behavioral patterns, we've learned that warning people that they're being scammed is very different from convincing them of it. The main challenge is moving from detection to effective prevention to 'Break the Scam Spell.' This shift reflects a broader truth: modern scam prevention is as much a psychological challenge as a technological one. Fraudsters know how to apply social engineering to induce urgency and exploit confirmation bias. If banks want to stay ahead of today's fraudsters, their AI tools must do more than transform back-office functions. They must be able to detect anomalies and respond with empathy, clarity, and personalized engagement. To achieve this goal, we must train AI models to think like behavioral scientists. In practice, this means simulating scam scenarios, reverse-engineering past incidents to understand emotional triggers, training AI with billions of scam identifiers, and clustering users by behavioral risk profiles, similar to how credit risk is modeled. Some banks have begun exploring real-time conversational interfaces that interact with customers during transactions. Instead of simply blocking a suspicious payment, these tools initiate a dialogue, explaining the risk and giving the customer a chance to reconsider. Early results suggest this approach significantly improves both scam prevention and customer satisfaction while mitigating reputational risk and lowering the false positive rates in certain cases. Of course, not all interventions are created equal. Poorly executed friction, like generic prompts, scripted questions, or robotic messaging, can erode trust. Worse, it can cause vulnerable users to disengage entirely or allow scammers to take advantage of the predictable scripts to manipulate their victims. This is where psychology matters most. A well-trained AI agent should know how to de-escalate, listen, and guide a user back to safety without shame or confusion. Ultimately, the future of scam prevention will depend on advanced AI models constantly trained on the latest scam trends and human vulnerabilities, increasing their ability to detect and intervene in real time. Banks that treat customer protection as a human challenge, compared to a compliance one, will be best positioned to lead. Training AI agents like behavioral scientists may sound unconventional, but in today's threat landscape, it's one of the most effective moves a bank can make.
Entrepreneur
22-05-2025
- Business
- Entrepreneur
B2B SaaS Firm Data Sutram Raises USD 9 Mn Series A from B Capital and Lightspeed
The Mumbai-based startup will use the funds to expand its AI-driven fraud detection platform across new sectors and enter international markets in the Middle East and Southeast Asia. You're reading Entrepreneur India, an international franchise of Entrepreneur Media. Mumbai-based B2B SaaS startup Data Sutram has raised USD 9 million in a Series A funding round co-led by B Capital and Lightspeed. The funds will be deployed to expand the company's fraud detection and risk intelligence platform into sectors such as cryptocurrency, real-time payments, gaming, e-commerce, and insurance, while also strengthening AI capabilities and enabling international expansion into the Middle East and Southeast Asia. The round marks a significant milestone in Data Sutram's growth journey. The company had previously raised USD 3 million in September 2023, led by Singularity Growth Fund, and USD 2.07 million in February 2022 from Varanium Capital and Yatra Angel Network. Founded in 2018 by Rajit Bhattacharya, Ankit Das, and Aisik Paul, Data Sutram offers a RegTech-focused AI platform that helps financial institutions combat fraud, improve customer onboarding, and reduce risk across the lifecycle of lending, payments, and insurance. Its proprietary Trust Score analyses millions of digital footprints to detect synthetic identities, identity theft, and collusion, offering a 360-degree customer risk profile. The platform has already processed over 110 million individual identities, aiding leading banks, NBFCs, and fintechs in India in reducing NPAs and improving approval rates. "With this investment, we're entering the next phase of our mission to build a financial ecosystem based on trust," said Rajit Bhattacharya, Co-founder and CEO of Data Sutram. "Our goal is to ensure every transaction is secure. We believe our Trust Score will eventually underwrite every transaction. This funding enables us to enhance our product, expand globally, and serve more businesses seeking AI-driven risk intelligence." Karan Mohla, General Partner at B Capital, commented, "We view Data Sutram as a category-defining RegTech leader in India. Their ability to combine real-time analytics with external intelligence is reshaping fraud prevention and compliance." Hemant Mohapatra, Partner at Lightspeed, added, "In a digitised financial landscape, the need for intelligent, scalable fraud prevention is critical. Data Sutram's sector adaptability and compliance-first approach make them a strong partner for global financial services." With a growing demand for secure and intelligent fraud mitigation tools, Data Sutram is poised to redefine how institutions safeguard trust in digital transactions—both in India and beyond.
TechCrunch
07-05-2025
- Business
- TechCrunch
Stripe unveils AI foundation model for payments, reveals ‘deeper partnership' with Nvidia
Fintech giant Stripe announced Wednesday a slew of new product launches at its annual Stripe Sessions user event. The highlights include: a new AI foundation model for payments; stablecoin-powered accounts; a new Orchestration offering, and a recent migration with chip behemoth Nvidia. Stripe's payments foundation model has been trained on tens of billions of transactions, Emily Glassberg Sands, Stripe's head of information, said. So it 'captures hundreds of subtle signals about each payment' that other models would miss, she said. One use case is improved fraud detection. Stripe's previous models 'gradually' reduced card testing attacks by 80% over two years. Card testing attacks are a type of fraudulent activity in which someone tries to determine whether stolen card information is valid so that they can use it to make purchases. The company claims that its new foundation model increased its detection rate for such attacks on large businesses 'by 64% practically overnight.' She added, 'Previously, we couldn't take advantage of our vast data. Now, we can.' Stripe, of course, isn't the only fintech to have built a model using AI for fraud detection. Just one example is Sardine, which describes itself as an AI risk platform for fraud, compliance, and credit underwriting, in February raised a $70 million Series C funding round led by Activant Capital. Techcrunch event Exhibit at TechCrunch Sessions: AI Secure your spot at TC Sessions: AI and show 1,200+ decision-makers what you've built — without the big spend. Available through May 9 or while tables last. Exhibit at TechCrunch Sessions: AI Secure your spot at TC Sessions: AI and show 1,200+ decision-makers what you've built — without the big spend. Available through May 9 or while tables last. Berkeley, CA | BOOK NOW In an interview, Will Gaybrick, Stripe's president of product & business, told TechCrunch that Stripe's generalized model is via self-supervised learning, and thus discovers its own features. ' We have found over and over and over again in machine learning, generalized models outperform,' he said. 'A big part of that is agility. It just performs better and adapts better to changes in fraud patterns. Stripe also announced on Wednesday its intent to bring stablecoin-backed, multicurrency cards to businesses by partnering with other startups like Ramp, Squads and Airtm. With such cards, businesses across multiple countries will be able to 'operate in the same currency for the first time,' the companies claim. The move comes just three months after Stripe completed its acquisition of stablecoin platform Bridge. With Orchestration, Stripe said it can better help businesses set up, manage, and optimize performance across multiple payment providers from its dashboard – whether or not they use Stripe as a payment processor. Stripe also used the event to name numerous AI companies that use its billing product, including Windsurf, OpenAI, Anthropic, Cursor, Perplexity, and Eleven Labs. More recently, according to Vivek Sharma, Stripe's head of revenue automation, Nvidia migrated its 'entire subscriber base' to Stripe Billing in six weeks – a process that the fintech claims typically takes many months for a business to complete and marked the 'fastest-ever migration to Stripe Billing.' (Nvidia was already a customer of Stripe Payments). Other announcements by Stripe on Wednesday included:
