A Historic Surge in Gen AI for Financial Services Exactly one year ago, Google Cloud shared a list of 101 enterprise-grade generative AI use cases. In 2025, that number has exploded to 601, many of them transforming how financial services are delivered, personalized, and embedded into everyday life. From neobanks in Mexico like Albo to global institutions like Citi and Deutsche Bank, financial players are reimagining operations and customer experience through AI. But beneath this rapid evolution lies another structural shift: the rise of embedded financial services, supercharged by generative AI. As generative AI automates, predicts, and personalizes at scale, embedded finance is no longer just a SaaS buzzword. It’s becoming the default delivery model — deeply woven into ecosystems via APIs, Banking-as-a-Service (BaaS), and embedded finance enablers. As Nitin Mittal, Global AI Leader at Deloitte, noted in the State of Generative AI in the Enterprise report: “We’re at a tipping point where generative AI will define competitive advantage — not just in how financial products are built, but how they learn, evolve, and serve end users contextually.” This article explores the convergence of generative AI and embedded finance, unpacking how it’s reshaping fintech infrastructure, powering real-time decision-making, and enabling seamless financial interactions in non-financial platforms. From Monolithic Banks to Modular Money: Embedded Finance 2.0 Embedded finance was already gaining ground with the rise of digital wallets, contextual lending, and invisible payments. But what the 601 generative AI use cases make clear is this: AI is not just an add-on; it is the new operating system for embedded finance. Take Fundwell, for example — an AI-powered lending platform that connects businesses to ideal funding solutions. What used to take weeks in traditional bank pipelines now takes minutes, thanks to AI analyzing financial health and matching loan options in real time. This is embedded finance in action: finance delivered at the point of need, invisible yet intelligent. Similarly, Banco Rendimento has enabled 24/7 international money transfers via WhatsApp using generative AI. No human agent required. This isn’t just automation — it’s AI-mediated financial embedding into everyday communication platforms. These are not isolated examples. They reflect a broader trend: AI is making embedded finance context-aware, conversational, and proactive. AI + BaaS = A New Embedded Finance Stack At the core of this evolution lies a powerful stack: Embedded finance software solutions offer plug-and-play APIs for payments, lending, and KYC. Banking-as-a-Service (BaaS) providers deliver the regulatory and compliance plumbing. Generative AI agents now sit on top — interpreting user intent, generating documents, offering advice, and orchestrating transactions. Let’s break this down: 1. Embedded Finance Enablers Get Smarter Companies like Discover Financial, Scotiabank, and Safe Rate are layering AI assistants on top of existing banking APIs. These assistants do everything from generating mortgage quotes in seconds to guiding customers through onboarding and approval processes. By doing so, they turn generic embedded finance offerings into hyper-personalized financial experiences — a massive leap in customer stickiness and LTV (lifetime value). As Wolters Kluwer points out “GenAI specializes in making repetitive processes like data exploration and analysis almost instantaneous. Finance teams can reclaim their time on data exploration, driver-based analysis, creating charts, and crafting commentary for reports and instead focus on driving the business.” Ankur Patel, CEO of Multimodal, put it in a conversation with Illuminate Financial: “Generative AI is quickly becoming a necessity in finance — not just enhancing workflows, but opening entirely new revenue streams.” 2. Digital Wallets & Payments Go Proactive Embedded finance software that powers digital wallets is also evolving. Dojo, for instance, is combining Google Cloud’s Vertex AI with embedded payment rails to offer real-time, conversational analytics — transforming raw transaction data into customer insights. For merchants, this means intelligent payments with embedded insights. For customers, it means faster checkouts, personalized offers, and intuitive interfaces. 3. BaaS Platforms Gain AI-Powered Decisioning A new generation of BaaS platforms is integrating AI into backend services like fraud detection, underwriting, and compliance. Cloudwalk, a Brazilian fintech unicorn, used generative AI to power fraud analysis and credit scoring models — helping it grow its customer base by 200% while turning a profit. This is a prime example of how AI doesn’t just make BaaS smarter — it makes it scalable, secure, and profitable. Use Case Deep Dive: Where AI and Embedded Finance Intersect Let’s explore some specific real-world examples from the report that illustrate how AI and embedded finance converge: 💡 Case 1: Figure & Real-Time LendingFigure, a fintech offering home equity lines of credit, uses Gemini’s multimodal models to power lending chatbots. These bots interact with customers, guide them through form submissions, and issue approvals — often in real time.→ Embedded finance outcome: Customers access credit within other platforms, like real estate portals or banking superapps, without ever stepping into a branch. 💡 Case 2: Banco Covalto’s Instant CreditMexico’s Banco Covalto reduced credit approval response times by over 90% with generative AI. Embedded within its mobile banking experience, AI evaluates creditworthiness and issues decisions in seconds.→ Embedded finance outcome: Instant loans offered where users need them — directly inside mobile channels. 💡 Case 3: Apex Fintech & Frictionless InvestingApex Fintech Solutions is deploying Google Cloud tools to enable embedded investing capabilities — think Robinhood-like features, but white-labeled and AI-optimized for partner platforms.→ Embedded finance outcome: Investing made available across consumer apps, from budgeting tools to e-commerce platforms. The Strategic Opportunity: What This Means for Fintech Founders & SaaS Leaders Whether you’re building a neobank, a B2B SaaS platform, or an e-commerce app, this AI-embedded finance convergence is rewriting the competitive landscape. ✅ For FintechsYou can now differentiate on intelligence. Not just speed or fees. Embedding AI agents into your financial workflows allows for context-aware product offerings — think real-time underwriting, conversational tax filing, or predictive savings nudges. ✅ For SaaS PlatformsWant to offer embedded payroll advances or invoice factoring? AI-powered finance enablers now let you do that without hiring a compliance team or becoming a bank. Using platforms like Synapse, Unit, or Treasury Prime (and soon their AI-enhanced versions), you can integrate embedded finance features with full explainability and KYC guardrails. ✅ For Traditional BanksThe AI-BaaS combo presents both a threat and an opportunity. Banks like ING, Citi, and Commerzbank are leaning in — deploying internal AI agents to support underwriting, call summaries, and risk analysis. The forward-thinking ones are now acting as embedded finance providers themselves, opening up their infrastructure as APIs and enriching them with AI tools to support partners across ecosystems.

The global payments landscape is undergoing a rapid transformation, moving away from cash and checks toward digital and instant payment solutions, as highlighted in the Fintech Magazine. With 82% of consumers expressing interest in instant payments and 92% of merchants anticipating significant value from these technologies, financial institutions must adapt swiftly to meet evolving demands. Discover is positioning itself at the forefront of this shift, balancing innovation with security while preparing for emerging trends like Central Bank Digital Currencies (CBDCs). In an exclusive interview with Fintech Magazine, Tribh Grewal, Director of International Product Strategy and Business Development at Discover, shared insights into the company’s strategy for the future of payments. Evolving Instant Payments Infrastructure As digital payments gain traction, instant transactions are becoming a cornerstone in major markets. Tribh Grewal explains Discover’s approach: «Modernising payments infrastructure is important for companies that want to stay competitive and meet evolving expectations. At Discover® Network, we are embracing technology solutions and forging partnerships to meet our customer’s needs.» Discover has strengthened its foundation through strategic collaborations with fintech firms like Nium, Fyorin, and Pax2pay, enabling secure and scalable global payments. Additionally, partnerships with Bluecode will expand mobile payment acceptance worldwide, facilitating cross-border transactions. Preparing for Central Bank Digital Currencies (CBDCs) With central banks worldwide exploring CBDC pilots, including the European Central Bank’s potential Digital Euro, Discover is preparing for the opportunities and challenges these innovations present. «While CBDCs offer the promise of greater transparency, more streamlined settlement processes, and enhanced regulatory oversight, they also place pressure on private networks to adapt to maintain interoperability and competitive flexibility,» Grewal noted. Discover is investing in scalable and interoperable solutions, focusing on modular architectures and API-driven frameworks to support future CBDC integration. Combating Fraud in Real-Time Payments As instant payments grow, so do fraud risks. Discover’s 2024 Payments State of the Union study highlights the increasing need for strong security measures. «Sitting uniquely at the intersection between issuers and acquirers, we have the advantage of being able to detect fraud trends at scale,» Grewal explained. The company’s Enhanced Decisioning system helps merchants reduce false declines while blocking fraudulent transactions. Discover also collaborates with industry partners through initiatives like the High Brand Risk program, targeting sectors such as online gambling and cryptocurrency to enhance security. The Future of Cross-Border Instant Payments Cross-border payments face challenges like regulatory fragmentation and legacy systems, but industry efforts such as Project Nexus and SEPA OCT Inst are improving interoperability. «Advancements in technology, fintech companies, blockchain, and new regulatory frameworks are facilitating international payments, which is beneficial for businesses and individuals,» Grewal stated. Discover’s partnership with Fyorin introduces B2B virtual cards, simplifying cross-border transactions by reducing costs and streamlining reconciliation. Looking ahead, data analytics and network intelligence will play a crucial role in optimizing global payments. Discover is driving innovation in instant payments, CBDC readiness, fraud prevention, and cross-border transactions, ensuring it remains a leader in the evolving financial ecosystem. As Grewal emphasizes, collaboration and technology will be key to shaping the future of payments.

As auto dealerships navigate 2025, financing trends continue to evolve in response to economic conditions, interest rates, and consumer demand, according to BradyMartz’s website. Affordability remains a top priority, making it essential for dealerships to stay ahead of financing developments to maintain sales and profitability. Here’s a breakdown of the key financing trends impacting the auto industry and how dealerships can adapt. 1. Interest Rates Stabilize—But Remain High Following the sharp increases of 2022-2023, interest rates have stabilized but remain elevated compared to pre-pandemic levels. This continues to challenge both dealerships and buyers. Key Implications: Higher borrowing costs for dealership floor plans necessitate smarter inventory management. Consumers may delay purchases or choose shorter loan terms to reduce interest expenses. Leasing could gain popularity as buyers seek lower monthly payments without long-term commitments. Dealership Strategies: Negotiate better floor plan financing terms with lenders. Offer promotional financing deals to ease affordability concerns. Educate customers on total loan costs versus monthly payments. 2. Longer Loan Terms & Creative Financing Solutions With vehicle prices still high, many buyers are opting for extended loan terms—some stretching to 84 months or more—to keep payments manageable. Emerging Trends: Lower down payment options to attract buyers. Growing interest in balloon loans (lower initial payments with a lump sum due later). Increased competition from credit unions and alternative lenders offering better rates. Dealership Adjustments: Partner with lenders to provide flexible financing options. Clearly explain the long-term costs of extended loans. Promote pre-owned financing for budget-conscious buyers. 3. Rising Demand for Pre-Owned & CPO Financing With new car prices averaging over $45,000, more buyers are turning to used and certified pre-owned (CPO) vehicles for affordability and reliability. Why It Matters: Lenders are expanding financing programs for used cars. CPO vehicles offer warranty protection without the new-car price tag. Action Steps for Dealerships: Highlight low-interest financing specials on used and CPO inventory. Educate buyers on CPO benefits (extended warranties, inspections). Provide in-house financing options for credit-challenged customers. 4. Digital & AI-Driven Financing Tools Gain Traction Technology is transforming auto financing, with AI-powered lending platforms and digital pre-approval tools becoming mainstream. Key Changes: Faster loan approvals via AI-driven credit analysis. More online financing applications, allowing pre-approvals before dealership visits. Customized loan offers based on real-time credit data. How Dealerships Benefit: Streamline approvals to enhance customer experience. Implement online pre-qualification tools to attract serious buyers. Use AI-powered loan matching to secure the best financing options. 5. Manufacturer Incentives & Dealer Financing Promotions To counter affordability challenges, automakers are expected to roll out more aggressive financing incentives in 2025. Expected Offers: 0% APR financing on select models. Cash rebates and trade-in bonuses to drive traffic. Dealer participation in subsidized financing programs. How to Leverage Incentives: Stay updated on OEM promotions and actively advertise them. Train sales teams to emphasize financing deals. Offer exclusive financing specials for loyal customers. Navigating high interest rates, inventory financing, and shifting consumer preferences presents challenges for auto dealerships. 

The rise of generative AI in software development promises to revolutionize productivity, but for the banking sector, this shift comes with hidden risks, as stated in FinTech Futures. While AI can accelerate coding processes, experts warn that over-reliance on AI-generated code without deep technical oversight could lead to inefficiencies, security vulnerabilities, and a looming skills crisis. Dharmesh Mistry, a seasoned programmer with decades of experience in banking technology, draws parallels between today’s AI-driven coding and past shifts in programming paradigms. «I wrote my first code at 12 on a mainframe, and by 17, I was a junior programmer at Lloyds Bank,»Mistry recalls. «Back then, transitioning from low-level languages like C to high-level tools like Visual Basic (VB) was a productivity game-changer—but it came at a cost.» While VB made Windows app development accessible, Mistry observed that programmers who relied solely on it struggled with complex system-level challenges. «Programmers working exclusively in VB couldn’t solve intricate problems because they lacked fundamental knowledge of how the Windows OS worked. The best solutions still came from experienced C developers who understood the underlying system.» AI and the Future of Banking Software Today, large language models (LLMs) offer a similar promise: faster, more efficient coding. However, Mistry warns that banks must not overlook the need for «system programmers»—developers with deep architectural expertise who can supervise AI-generated code. «AI will make programmers more productive, but we still need those who truly understand the system,» he says. «They must ensure AI-generated solutions are performant, secure, and resource-efficient—not just functionally correct.» Without this expertise, banks risk accumulating technical debt—much like the current shortage of COBOL programmers maintaining legacy systems. The Urgent Need for Investment in Deep Technical Skills Mistry emphasizes that banks must proactively train the next generation of system programmers rather than assuming AI will replace the need for expertise. «It will be tempting for companies to cut costs by relying solely on AI, but that’s a dangerous gamble. Banks that maintain a core of deeply skilled programmers will avoid the crisis awaiting those who neglect expertise in favor of automation.» His warning is clear: AI is a tool, not a replacement for knowledge. The financial institutions that invest in system-level programming skills today will be the ones best positioned to harness AI’s potential without falling into technical insolvency tomorrow.

Spendesk, a leading spend management and procurement platform for mid-market businesses, has announced a company-wide partnership with Dust, a European AI specialist, to deploy secure, custom AI agents across its operations, as outlined in Fintech Global News. The collaboration aims to enhance efficiency, streamline AI tool usage, and ensure compliance with data protection regulations in the UK and Europe. A Unified AI Strategy for Greater Efficiency Previously, different teams at Spendesk used various AI tools independently, leading to fragmented workflows and security concerns. By adopting Dust’s platform, Spendesk now centralizes its AI strategy, eliminating silos and reinforcing data security. Since 2017, Spendesk has integrated AI into its operations, developing over 15 AI-powered features—including tools that pre-fill more than 2 million accounting fields monthly. However, the company recognized the need for a more scalable and secure approach, prompting this partnership. Dust’s Role: Secure, Custom AI Agents for Every Team Dust’s platform enables businesses to build role-specific AI agents that integrate with tools like Notion, Intercom, and Slack while maintaining strict data protection. The solution allows non-technical employees to create personalized AI assistants tailored to their workflows, fostering innovation and productivity. Rodolphe Ardant, Spendesk Founder: “It’s impossible to use Spendesk without interacting with AI. We’ve implemented no fewer than 15 AI-powered features since 2017, predicting and pre-filling more than 2 million accounting fields each month.” Axel Demazy, Spendesk CEO: “As UK businesses continue to navigate an evolving regulatory and economic landscape, secure AI adoption has never been more crucial. At Spendesk, we found ourselves vetting contracts with individual AI assistants one by one. It wasn’t scalable or cost-effective. It also meant that teams more hesitant to experiment with AI were left behind, unsure of how these tools could support their work or comply with internal policies and local regulations.” Rodolphe Ardant, on the partnership’s impact: “This partnership gives our teams the most powerful productivity tool we’ve ever put in their hands. Internal efficiency translates directly into faster innovation for our customers, helping us deliver both the most in-demand spend management features and the next generation of AI-first capabilities. By partnering with a fellow French innovator committed to data security, we’re proving that European tech can lead in AI while staying true to our values of privacy and user empowerment.” Gabriel Hubert, Dust CEO: “We built Dust to help companies create AI agents that are truly useful and trusted by their teams. Spendesk had the vision and urgency to move early, and together we’ve shown what’s possible when AI is deployed thoughtfully and securely at scale.” By choosing Dust, a European provider, Spendesk reinforces its dedication to data privacy and regional compliance. The partnership highlights the potential for European tech to lead in AI innovation while adhering to strict regulatory standards.This collaboration positions Spendesk as a forward-thinking FinTech leader, embracing AI at scale while maintaining security and efficiency.

April 24, 2025 — Klarna has secured a deal with eBay to bring its flexible payment solutions to millions of shoppers in the United States, according to Finextra. The move follows the success of Klarna’s «Buy Now, Pay Later» (BNPL) services in other key markets, including the UK, Austria, France, Italy, the Netherlands, and Spain. With this expansion, US customers can now use Klarna’s Pay in 4 option—allowing them to split payments into four interest-free installments—as well as Financing, which provides extended payment plans for larger purchases. A Strategic Move for Klarna and eBay The US market is already Klarna’s largest revenue generator, and this partnership with eBay is expected to further strengthen its position. Meanwhile, eBay continues to enhance its payment flexibility to attract and retain customers. Avritti Khandurie Mittal, VP & General Manager of Global Payments and Financial Services at eBay, stated: “We’ve been very pleased with the positive customer and business impact Klarna has delivered in some of our key markets including the U.K. and Europe, and we’re now excited to give millions of U.S. shoppers more flexible and affordable ways to pay on eBay.” In addition to BNPL services, Klarna has introduced its resell feature to US eBay users. This tool allows shoppers to easily list past Klarna purchases on eBay, with pre-filled descriptions and images for faster selling. Since its launch in December 2024, the feature has generated over 500,000 eBay listingsthrough Klarna’s app. The partnership underscores the growing demand for flexible payment solutions in e-commerce, as both companies aim to provide seamless shopping and selling experiences. As Klarna continues to expand its US footprint, further integrations with major retailers could be on the horizon. For now, eBay shoppers can enjoy greater financial flexibility while Klarna strengthens its dominance in the BNPL space.

Embedded finance is transforming how consumers and businesses interact with financial services. By integrating payments, lending, insurance, and investment solutions directly into non-financial platforms, companies are reshaping the banking landscape, as stated in The Fintech Times. As this trend grows, could embedded finance be the key for neobanks to finally overtake traditional banks? Neobanks Gaining an Edge Neobanks have risen rapidly over the past decade, yet traditional banks still dominate market share. However, embedded finance may shift this balance. Luke Voiles, CEO of Pipe, believes embedded finance gives neobanks a significant advantage: “Embedded finance equips neobanks with powerful tools to enhance user experience and financial accessibility, differentiating them significantly from traditional banks. NPS satisfaction scores for traditional banks have been in the 20s and 30s. We’ve seen embedded capital hit the 70s, 80s, and even 90s. LTV and retention hinge on that customer experience. As customers come to expect that friendlier experience, it’s going to be a race to see who can implement it the fastest, and neobanks are likely to have an edge in agility.” Traditional Banks Playing Catch-Up Nick Botha, global payments lead at AutoRek, agrees that neobanks are better positioned to leverage embedded finance: “Neobanks are built with innovation and agility. With an established digital presence and seamless, consolidated platforms, they can integrate services into non-financial ecosystems—positioning them to not only compete but surpass traditional banks in reach.” Meanwhile, traditional banks face challenges in adapting due to legacy systems and slower digital transformation. Flexibility and Innovation Driving Success Meryem Habibi, CRO at Bitpace, highlights how embedded finance enables smoother transactions and crypto integrations: “Embedded finance gives neobanks a distinct advantage by letting them build seamless experiences where users can pay, invest, or settle funds without ever leaving the app. Unlike traditional banks tied to legacy infrastructure, neobanks can quickly adopt decentralized rails and blockchain-powered tools.” Steve Round, co-founder of SaaScada, notes that embedded finance enhances customer engagement: “Neobanks are already digital-first, making them ideal for embedded finance. By embedding banking services, they collect more data to deliver personalized products. However, they must choose between outsourcing financial services (quicker but restrictive) or building their own regulated infrastructure (more flexible but complex).” Alex Mifsud, CEO of Weavr, concludes that embedded finance’s real power lies in making financial services seamless: “Embedded finance is a new channel for delivering financial services, just like the web or mobile were. Neobanks that integrate finance into context-rich platforms—such as payroll or procurement—can create stickier ecosystems. While traditional banks dominate in balance sheets, neobanks can outpace them in user experience, relevance, and speed.”As embedded finance becomes mainstream, neobanks are well-positioned to leverage their agility and digital expertise. If they continue innovating while ensuring security and compliance, they may finally surpass traditional banks in customer adoption and market influence.

In a sweeping crackdown on advertising fraud, Google announced that it used artificial intelligence to eliminate nearly half a billion scam ads in 2024 — a decisive move that aligns with growing demands from banks and lawmakers for tech platforms to take greater responsibility in fighting online scams, according to Finextra. As stated by the tech giant, AI-powered tools led to the suspension of 39.2 million advertiser accounts in the U.S. alone, more than three times the number suspended in 2023. The company attributed the success to more than 50 upgrades rolled out last year to its Large Language Models (LLMs). These upgrades enhanced Google’s ability to detect malicious behaviors and scam indicators during the early stages of account setup. “These updates sped up complex investigations, helping us identify bad actors and fraud signals — like illegitimate payment information — during account setup,” Google said. “This kept billions of policy-violating ads from ever showing to a consumer, while ensuring legitimate businesses can show ads to customers faster.” In response to the rise of AI-powered scams — particularly those using deepfake impersonations of public figures — Google bolstered its defenses and adapted its detection techniques. The company said it focused heavily on combating impersonation scams that falsely represent businesses and government officials. According to the Federal Trade Commission (FTC), such impersonation scams cost U.S. consumers $2.95 billion in 2024. “To fight back, we assembled a team of over 100 experts to develop countermeasures, such as updating our Misrepresentation policy to suspend advertisers that promote these scams,” the company stated. “As a result, we were able to permanently suspend more than 700,000 offending advertiser accounts. This led to a 90% drop in reports of this kind of scam ad last year.” Despite the impressive figures, Google — along with other tech giants like Meta — continues to face scrutiny. Critics argue that these platforms remain primary channels for scam operations, prompting calls from financial institutions and fintech companies for Big Tech to share liability and reimbursement responsibilities for victims of scams that originate on their services.

MoneyGram, a leading global payments network, has announced a strategic partnership with Plaid, the data connectivity platform behind some of the most widely used fintech tools, as stated in FF News. The collaboration aims to streamline the process of sending and receiving funds, especially across borders, by simplifying bank account authentication for U.S. customers. Through this partnership, U.S.-based MoneyGram customers can now utilize Plaid’s technology to securely link and verify their bank accounts, ensuring quicker and more reliable transfers for both domestic and international payments. The new integration enhances the MoneyGram Online (MGO) experience and is set to expand to additional markets later this year. “The MoneyGram network moves money for over 50 million customers each year, across nearly every country in the world,” said Anthony Soohoo, Chief Executive Officer of MoneyGram. “This partnership with Plaid expands our global capabilities to deliver faster, more secure payments for our customers. It’s a clear step forward in our mission to make cross-border payments seamless, affordable and secure for everyone.” The integration arrives at a time when consumer demand for fast, secure, and connected financial services is at an all-time high. A significant 75% of U.S. consumers now consider linking their bank accounts to financial apps essential, and over 85% of fintech users prefer pay-by-bank options due to their speed, simplicity, and security. “Plaid provides the most widely used and trusted network across digital financial services, covering thousands of financial institutions across the United States, Canada, Europe and the United Kingdom,” said Brian Dammeir, Head of Payments and Financial Management at Plaid. “Now, MoneyGram can leverage the power of the Plaid network to quickly and securely drive conversion, reduce bank returns and proactively prevent fraud.” The solution connects directly to Plaid’s robust ecosystem of financial institutions, offering secure, instant account verification. This complements MoneyGram’s comprehensive compliance and anti-fraud infrastructure, creating a seamless user experience for transferring funds globally. Built on a technology-first payment platform, MoneyGram’s network spans over 200 countries and territories, with approximately 450,000 retail locations and access to 5 billion digital endpoints. With this collaboration, MoneyGram continues to position itself at the forefront of innovation in the global remittance space, offering customers greater convenience and security through fintech-powered solutions.

Traditional Know Your Customer (KYC) processes are no longer keeping pace with the speed and complexity of modern financial services, as highlighted in Fintech Global News. Manual methods and legacy systems are creating serious operational hurdles—and costing institutions time, money, and compliance credibility. Financial institutions have long relied on manual reviews to meet KYC and anti-money laundering (AML) requirements. But today, these outdated approaches are proving inefficient and expensive. According to Quantifind, onboarding a new corporate client costs an average of $2,598, and global banks take around 95 days to complete a full KYC review. That’s not just slow—it’s unsustainable. The False Positives Problem One of the biggest pain points? False positives. Legacy systems are notorious for flagging too many benign transactions. In fact, industry data shows that traditional rule-based transaction monitoring systems generate up to 90% false positives. This floods compliance teams with unnecessary alerts, wastes valuable time, and slows down real investigations. To make matters worse, over half of compliance professionals say they’re stretched too thin. A survey by Corporate Compliance Insights revealed that 53% of compliance officers feel they lack the resources to do their jobs effectively. The AI Solution: Smarter, Faster, More Scalable AI and machine learning are quickly emerging as game-changers in the KYC landscape. These technologies automate routine compliance tasks, reducing onboarding time and cost. AI-driven platforms can verify customer data instantly and accurately, giving compliance teams the freedom to focus on high-risk cases and strategic decisions. Even better, machine learning reduces false positives and boosts fraud detection by analyzing massive data sets and spotting complex patterns. The result? More accurate risk assessments—and less wasted effort. As Moody’s puts it: “AI’s role in KYC is set to expand, offering organisations significant benefits such as reduced costs, heightened accuracy, and an optimised customer experience.” At the forefront of this transformation is Quantifind, a top provider of AI-based KYC solutions. Its AI risk intelligence platform delivers real-time insights across areas such as: Negative news Sanctions and watchlists Politically exposed persons (PEPs) Corporate data The platform uses advanced “signal extraction” and risk modeling to generate precise risk scores from even unstructured data—something legacy systems struggle with. Clients are already seeing the impact. According to Quantifind, some institutions report up to 40% increases in efficiencycompared to older systems. One standout feature of Quantifind’s tech is its use of “name science.” By applying machine learning to name variations and linguistic patterns, the platform drastically improves entity resolution and reduces false positives. This matters in real-world applications. A Tier 1 global bank chose Quantifind after comparing multiple vendors, saying the company: “Beat out the competition with its strong data science foundation that leads to superior speed and accuracy.” Similarly, one of Canada’s Big Five banks reported impressive results: “Upwards of 40% productivity gains for investigations and 75% of high-risk cases automatically triaged.” Beyond Banking: Defense and Global Partnerships Quantifind’s capabilities aren’t limited to banking. The U.S. Department of Defense uses its technology to screen vendors and monitor ongoing risk. It’s also integrated with Oracle Financial Services Financial Crime and Compliance Management (FCCM), allowing seamless access to customer risk scores and reducing case review times. And through its partnership with OpenCorporates, Quantifind helps investigators uncover cross-border connections between companies and individuals—an essential tool in identifying complex financial crimes. As financial crime grows more sophisticated, AI and machine learning are becoming essential—not optional—for effective compliance. Forward-thinking institutions are transforming KYC from a regulatory burden into a strategic advantage. With platforms like Quantifind’s, they’re onboarding customers faster, detecting risk more accurately, and enhancing the overall customer experience. In today’s financial environment, smart compliance is more than a necessity—it’s a competitive edge.