Information and Analytics about Embedded Finance, BaaS and Open Banking

Artificial Intelligence (AI) continues to dominate the fintech industry in 2025, with firms seeking innovative ways to integrate it into their operations. As this technology evolves, understanding the risks and challenges surrounding AI in financial decision-making becomes increasingly vital, as stated in The Fintech Times. While AI’s potential is immense, experts caution against relying on it without proper testing and oversight. Mohamed Elgendy, co-founder and CEO of AI testing firm Kolena, underscores the danger of AI failures in financial decisions, noting that they can lead to serious consequences, ranging from faulty loan approvals to market-impacting algorithmic trading errors. He advocates for rigorous AI testing, emphasizing that organizations need to develop systematic frameworks to evaluate AI performance across various scenarios. «The solution isn’t to use AI less, but rather to test it more rigorously,» Elgendy says. He stresses that continuous validation, comprehensive testing, and human oversight are essential to avoid failures that could affect customers’ financial outcomes. Adam Ennamli, Chief Risk and Security Officer at General Bank of Canada, shares a similar view, highlighting the existential risks posed by AI failures, such as financial losses, market distrust, and regulatory penalties. «When AI tells you what you want to hear, you tend to ‘forget’ or at least minimise the risks that come with automation dependence,» Ennamli warns. He advises financial institutions to maintain flexibility in automated systems while ensuring proper human oversight, particularly in complex situations where human judgment remains essential. Satayan Mahajan, CEO of Datalign Advisory, stresses that AI’s vast potential in the financial sector requires equally robust preparations. Drawing on past examples, such as the 2010 Flash Crash and the 2019 Apple credit card algorithm controversy, Mahajan emphasizes the need for responsible AI development. «Failures in the financial industry are expensive and generate low trust with consumers,» he says. AI’s rapid advancement in the financial sector demands a matching leap in compliance, risk management, and institutional investment. Michael Gilfix, Chief Product and Engineering Officer at KX, argues that to successfully apply AI in financial decision-making, firms must implement strong monitoring processes. He explains that robust monitoring detects algorithm drift or bias, triggering necessary recalibrations to maintain AI performance. Gilfix also suggests that firms must decide whether they want AI to automate decisions or merely offer recommendations to human decision-makers. This flexibility ensures that AI is a tool within a broader strategy for improving business outcomes. Finally, Jay Zigmont, PhD, CFP, founder of Childfree Wealth, reflects on the importance of quality assurance in AI. He points out that human advisors make mistakes daily, and it is essential to ensure that AI undergoes the same rigorous scrutiny. «AI is only as good as its programming, training, and quality assurance,» he concludes, raising the question of whether humans would perform better if held to the same quality assurance standards. While AI offers tremendous opportunities in financial decision-making, experts emphasize that firms must prioritize testing, oversight, and continuous monitoring to mitigate the risks associated with its deployment. The balance between leveraging AI’s capabilities and maintaining human judgment is key to navigating the complexities of AI in finance.

Artificial intelligence (AI) is rapidly reshaping the financial industry, transforming risk management practices and enhancing compliance efforts, as outlined in Fintech Global News. The integration of technologies such as machine learning (ML), deep learning (DL), and generative AI (GenAI) is accelerating decision-making processes while improving the accuracy of traditionally human-dominated tasks. As highlighted by Moody’s, AI is proving to be invaluable in the realm of Know Your Customer (KYC) procedures and enhanced due diligence. It aids in complex functions like intelligent screening and risk monitoring, thereby bolstering prevention and detection capabilities. By enabling financial institutions (FIs) to access vast, often fragmented data, AI promotes greater transparency and efficiency, ultimately improving compliance operations. Olivier Morlet, a Money Laundering Reporting Officer (MLRO) and member of the Global Coalition to Fight Financial Crime (GCFFC), and Francis Marinier, Moody’s Industry Practice Lead, have discussed AI’s transformative impact in two crucial areas: regulatory compliance, especially in Ultimate Beneficial Owner (UBO) discovery, and social responsibility. AI is revolutionizing data analysis and pattern recognition, both vital for identifying UBOs. The technology allows for rapid analysis of complex ownership data and can extract key information from unstructured texts through natural language processing (NLP). This enables AI to identify hidden ownership structures that would typically be difficult to uncover using manual methods. As global registers of beneficial ownership remain inconsistent, AI’s ability to reveal these concealed connections is essential. Furthermore, AI-driven solutions can automate the process of identifying beneficial owners by cross-referencing various data sources. Through techniques such as entity resolution, AI can recognize when multiple records refer to the same entity, making data integration more straightforward and enhancing the accuracy of ownership mapping. This is especially valuable in light of the challenges posed by inconsistent global beneficial ownership registers. Social Network Analysis (SNA) powered by AI is another powerful tool in uncovering UBOs. By mapping complex ownership structures and identifying key influencers within networks, SNA helps to reveal potential UBO links that might otherwise go unnoticed. This technology also supports investigations into financial flows, aligning with the «follow the money» principle to trace funds across intricate networks. AI technologies like Optical Character Recognition (OCR) and NLP are also pivotal in managing unstructured data, such as PDFs. These technologies convert unstructured data into structured, searchable formats, facilitating the tracking of ownership chains and improving the quality of data required for effective AI/ML models. Moreover, public-private partnerships (PPPs) play a crucial role in the development and deployment of AI/ML tools for financial crime prevention. The continued collaboration between regulators and financial institutions ensures that AI/ML technologies are used ethically and effectively, addressing the complex technical, legal, and practical challenges associated with their implementation. A key concern in the application of AI/ML in compliance is mitigating biases. Transparent methodologies are essential to ensure that AI processes are open to examination, reducing risks related to model training and ensuring fairness and equity in the application of AI tools. AI is significantly advancing the compliance landscape within the financial sector. By fostering innovation and leveraging data-driven tools, financial institutions can better navigate the complexities of modern financial systems, enhancing regulatory compliance and enabling more strategic decision-making.

Tesla (TSLA) is once again pushing the boundaries of innovation—not just in the automotive industry but also in financial technology. The company is quietly integrating fintech solutions into its ecosystem, setting the stage for a future where vehicles serve as financial hubs, according to TSLA News. This strategic move could reshape consumer interactions with finance, making transactions more seamless and automated. Tesla has introduced a beta program for its digital wallet and cryptocurrency project, leveraging blockchain technology. This feature allows Tesla owners to process payments directly from their vehicles, offering a new level of convenience. From tolls and parking fees to peer-to-peer transactions, Tesla’s digital wallet could revolutionize the way financial transactions are conducted on the move. Tesla is also investing in AI-driven financial platforms, which could transform wealth management by offering automated, personalized financial advice. Machine learning algorithms can tailor financial strategies for users, making sophisticated asset management more accessible to a broader audience. By incorporating blockchain and AI technologies, Tesla is streamlining financial transactions and reducing costs associated with traditional banking. This shift has the potential to democratize financial services, making them more efficient and accessible worldwide. Tesla’s fintech solutions could contribute to sustainability by minimizing the need for physical banking infrastructure. Less paper, fewer in-person bank visits, and reduced reliance on cash transactions all lead to a smaller carbon footprint. Moreover, by promoting EV adoption with integrated financial tools, Tesla continues to drive the transition away from fossil fuels. Tesla’s AI-powered financial tools have the potential to increase financial literacy and inclusivity. With real-time financial insights, users can make more informed decisions, breaking down barriers that have historically limited access to wealth management services. While Tesla’s fintech expansion presents exciting opportunities, it also comes with challenges: Adoption Barriers: Consumers may be slow to shift from traditional banking methods to Tesla’s integrated financial ecosystem. Regulatory Hurdles: Entering the financial sector means navigating strict financial regulations across different markets. Security Concerns: Blockchain technology enhances security, but cybersecurity risks remain a challenge in fintech adoption. Tesla’s fintech push could inspire other automakers to integrate financial solutions into their vehicles, leading to an industry-wide transformation. As digital currencies gain traction and AI-driven finance becomes the norm, Tesla is positioning itself at the forefront of this revolution. In the words of Valerie Johnson, «Tesla’s ventures into financial technology signify a burgeoning era where technology not only serves traditional roles but becomes an integral part of our financial and daily lives.» By merging mobility, technology, and finance, Tesla is not just shaping the future of transportation—it’s redefining how we interact with money itself.

Meta is making a major push into artificial intelligence-powered humanoid robotics by forming a dedicated team within its Reality Labs hardware division, as highlighted in PYMNTS. According to a Bloomberg report on Friday (Feb. 14), the team will be led by Marc Whitten, the former CEO of General Motors’ Cruise self-driving unit, and will bring in about 100 engineers this year. The company’s focus will be on developing humanoid robots capable of performing household chores, as well as AI, sensors, and software that could be integrated into other robotic products manufactured by various companies. Meta’s Chief Technology Officer, Andrew Bosworth, highlighted the strategic importance of this move in an internal memo, stating: “The core technologies we’ve already invested in and built across Reality Labs and AI are complementary to developing the advancements needed for robotics.” While Meta has not provided an official comment to PYMNTS, reports indicate that the company anticipates humanoid robots will not become mainstream for several years but believes they will be a key focus area for both Meta and the broader tech industry. Meta’s announcement comes amid a wave of new developments in the robotics industry. Apple is reportedly working on both humanoid and non-humanoid robots for smart home applications, though its projects remain in the early proof-of-concept stage and are unlikely to reach mass production before 2028. Similarly, OpenAI has signaled its interest in robotics, having filed a trademark application covering robotic products and begun hiring for a dedicated robotics team earlier this month. Meanwhile, established robotics firms are gaining momentum. On Feb. 13, Apptronik announced that it raised $350 million to scale manufacturing of its AI-powered humanoid robot, Apollo, to meet rising industry demand. In January, 1x, a humanoid robotics firm, acquired startup Kind Humanoid to enhance its development efforts, emphasizing that robots need to be built to “live and learn among us.” With major tech companies and robotics firms accelerating their efforts, the AI-powered robotics space is shaping up to be a battleground for the next wave of innovation.

U.S. financial technology firms FIS and Affirm have joined forces to integrate buy-now-pay-later (BNPL) services into traditional bank debit cards, as outlined in FinTech Magazine. This partnership aims to help banks retain customers as more people turn to alternative payment methods. Through this collaboration, banks that use FIS’s transaction processing will be able to embed Affirm’s BNPL technology into their mobile apps and online banking platforms. Customers can then manage installment payments directly through their primary bank accounts rather than using separate services. Affirm’s network of 335,000 retailers will be accessible to bank customers, allowing merchants to offer specialised financing options, such as zero-interest payment plans and extended payment periods. This was previously only possible through direct relationships with BNPL providers. Under the partnership, FIS will remain the payment processor, while Affirm will handle credit assessments and payment collection. According to reports, credit decisions will be made in real-time at checkout, eliminating the need for separate applications. The move reflects shifting consumer payment preferences. Traditional banks are facing competition from fintech startups that offer flexible payment services. To stay relevant, banks participating in this programme can now offer both fortnightly and monthly payment plans through debit card programmes. Jim Johnson, Co-President of Banking Solutions at FIS, highlighted the importance of this shift: «Customer conversion and retention have become major priorities for card-issuing banks in our increasingly digitised economy, where consumers have endless options.» This partnership enables banks to compete with standalone BNPL providers while maintaining their direct customer relationships. The report suggests that such integration could reduce customer migration to alternative payment platforms. The BNPL system will run on existing banking infrastructure, with Affirm’s technology managing credit assessments and payment scheduling. Banks can introduce BNPL services without having to develop proprietary systems. Additionally, participating merchants may subsidise financing costs, allowing banks to offer zero-interest payment options to qualified customers. These merchant-funded offers could provide longer payment terms and higher credit limits than standard installment plans. Wayne Pommen, Chief Revenue Officer of Affirm, described the strategic reasoning behind the partnership: «Millions of consumers prefer using a debit card from their trusted financial institution, and we believe they should have easy access to exceptional credit options through their preferred payment method. That’s why, for the first time, we’re bringing Affirm’s proprietary underwriting technology and full suite of pay-over-time solutions to third-party issuers in partnership with FIS.» This partnership follows FIS’ launch of its Revenue Insight product, which leverages AI-powered predictive analytics to enhance risk management, cash flow, and financial operations. Seamus Smith, Group President of Automated Finance at FIS, emphasised the potential impact: “Revenue Insight, as part of the FIS Automated Finance suite, can revolutionise the way CFOs manage cash flow in today’s fast-paced environment. Our vision is to provide systems that turn finance from a cost centre into a growth partner, taking the friction out of finance through visibility, real-time insights, and innovation that maximises revenue and strengthens customer relationships.” The partnership between FIS and Affirm marks a significant evolution in digital banking. By integrating BNPL services into debit cards, traditional banks can retain customers, offer flexible payment options, and compete with emerging fintech companies. With real-time credit assessments and merchant-backed financing, this collaboration has the potential to reshape how consumers manage payments in the digital age.

Swedish Buy Now, Pay Later (BNPL) leader Klarna has partnered with JPMorgan Payments to integrate its flexible financing solutions into JPMorgan’s merchant services, as stated in Fintech Global News. The collaboration is set to enhance Klarna’s accessibility, providing merchants with a broader range of payment options, including its interest-free BNPL solution. This move is expected to improve customer experience and drive sales for businesses utilizing JPMorgan Payments. Klarna has established itself as a leading BNPL provider, allowing consumers to split payments into interest-free installments while equipping merchants with tools to boost conversion rates and customer engagement. Beyond BNPL, Klarna has expanded into a full-scale shopping ecosystem, offering an app and AI-driven personal finance management features. JPMorgan Payments, a division of JPMorgan Chase, is one of the world’s largest payment processors, managing transactions worth over $2 trillion annually. The company provides end-to-end payment solutions, including acquiring, treasury services, and merchant processing, catering to businesses of all sizes. As part of the agreement, Klarna will also become a member of the JPMorgan Payments Partner Network, connecting businesses with various third-party payment solutions. This alliance is expected to accelerate Klarna’s market expansion and help the company reach new merchant segments. With Klarna reportedly planning an initial public offering (IPO) in April, this partnership could further strengthen its appeal to investors by showcasing its growth and integration into mainstream financial infrastructure. David Sykes, Klarna’s chief commercial officer, emphasized the significance of the partnership, stating, “By collaborating with JPMorgan Payments, we’re bringing our payment solutions to even more businesses and fast-tracking our ambition to make Klarna payments available everywhere, for everything.”

According to a recent report from Acrew Capital, in partnership with Money20/20, artificial intelligence (AI) is rapidly reshaping the financial industry, as stated in FF News. The report reveals that 76% of financial institutions have already integrated AI into their operations, signaling a major shift in how the sector leverages technology. At Money20/20 USA, industry experts Micky Tesfaye, Head of Content at Money20/20, and Lauren Kolodny, Co-founder of Acrew Capital, discussed the findings of the report. They emphasized AI’s accelerating role in fintech, from customer-facing solutions to fraud prevention. Kolodny highlighted the significance of Money20/20 as a partner in this research, stating, “Everybody attends.” The conference serves as a global hub where startups, banks, regulators, and investors exchange insights on emerging trends. Tesfaye noted that since the rise of ChatGPT, AI has dominated discussions at their events, reinforcing the need for structured analysis on its adoption. The report analyzed 221 leading financial institutions, tracking AI-related developments since January 2023. The findings include: 76% of financial institutions have launched AI initiatives. 51% have incorporated AI into customer-facing products. A total of 376 AI initiatives have been introduced in less than two years. Kolodny emphasized that AI is no longer in the experimental phase—it has become an integral part of financial services. Tesfaye echoed this sentiment, stating that AI’s adoption is happening at a much faster pace than many anticipated. AI is changing the competitive dynamics of the financial sector. Unlike previous tech waves, AI’s success depends on access to vast datasets, giving legacy institutions a key advantage. However, Kolodny pointed out that startups still have opportunities in areas where incumbents are slower to innovate. Two significant gaps identified in the report include: Agentic Payments: While digital assistants powered by AI are common, few companies have developed solutions that allow these assistants to execute payments autonomously. Gen-AI for Fraud Detection: Only 7% of companies surveyed currently use generative AI for fraud prevention, despite a 700% increase in deepfake-related fraud. This presents a major opportunity for AI-driven startups. Tesfaye highlighted the diversity of exhibitors at Money20/20 USA, including major players like OpenAI, Anthropic, and NVIDIA, alongside early-stage AI startups. This reflects the broad spectrum of companies shaping the future of AI in finance. As AI adoption accelerates, financial institutions are shifting from a purely competitive stance to one of collaboration. While incumbents are integrating AI at scale, challenges in compliance and fraud detection provide room for startups to partner with established players. Kolodny noted that regulatory clarity will be a key factor in AI’s future growth, particularly in sensitive areas like fraud prevention. As regulations evolve, AI’s role in finance is expected to expand even further. To encourage continued exploration of AI trends, Acrew Capital and Money20/20 have released a public database that allows fintech professionals to analyze AI adoption data. Kolodny encouraged industry participants to leverage these insights, while Tesfaye emphasized that this report is designed as a living resource to track AI’s evolving role in financial services. Despite claims that fintech is losing momentum, Kolodny stressed that AI is breathing new life into the industry. “AI has the potential to fundamentally rebuild financial infrastructure,” she said, and the data supports this transformation. Tesfaye concluded with a key takeaway: AI in financial services is not a distant future—it’s already here.

The auto finance industry is undergoing significant changes, driven by technology, economic pressures, and shifting consumer behaviors, according to Prodigital. Drawing insights from key industry events such as the AFSA Vehicle Finance Conference, AFS East, and reports from leading sources like McKinsey, Auto Finance News, Experian, and Moody’s, we highlight seven critical trends shaping auto finance today. 1. The Rise of Fintech and Digital Transformation Fintech is revolutionizing auto finance across various aspects of the loan lifecycle, including: AI-driven loan approvals and alternative data usage Digital loan processing Enhanced purchase transparency Streamlined dealer connections Improved fraud prevention and servicing The industry is embracing these advancements to enhance efficiency and customer experience, especially in challenging financial times. 2. Subprime Market Fluctuations Auto loan delinquencies were anticipated, and their rise is now evident. Industry experts, as discussed in a recent webinar on auto finance threats, note that subprime borrowers are often reliable due to their dependence on vehicles for daily life. However, major subprime lenders like American Car Center and U.S. Auto Sales have closed, forcing dealers to seek new lending partners. According to Auto Finance News, these developments continue to reshape the subprime lending landscape. 3. Rising Prices, Interest Rates, and Loan Payments Experian’s Q1 2023 State of the Automotive Finance Market Report states that the average new car payment has reached $725. Additionally, Edmunds reports that nearly 15% of drivers who financed a car late last year are paying over $1,000 monthly. High interest rates are keeping payments elevated, making it harder for non-prime borrowers to upgrade vehicles, despite falling used car prices. 4. Repossession Trends Although delinquencies are increasing, non-prime borrowers are making significant efforts to avoid repossession. Losing a vehicle can mean losing a job, particularly in areas without reliable public transportation. With federal student loan repayments resuming, industry players are preparing for potential impacts on auto loan delinquency rates. 5. Longer Loan Terms as a Solution To help borrowers manage payments, auto lenders are extending loan terms. Reuters reports that new car loans spanning 73-84 months accounted for 34.4% of the market in 2022, up from 28.6% in 2018. While this approach provides short-term relief, it also increases the risk of borrowers being underwater on their loans, a trend likely to persist amid high interest rates. 6. Enhanced Agent Coaching and Training Auto finance leaders are grappling with training and retaining loan servicing agents. As voiced at multiple industry conferences, common challenges include ensuring agents communicate effectively and follow compliance guidelines. AI-driven solutions such as real-time agent assistance, automated call notes, and AI-based call scoring are becoming essential tools for improving efficiency and agent performance. Additionally, creative incentives—like Girl Scout cookies, as highlighted in a recent webinar—can play a surprising role in motivation. 7. Delinquencies on the Rise Moody’s reports that auto loan delinquencies reached 7.3% in Q2 2023, surpassing pre-COVID levels. CNN further cites Moody’s warning that delinquencies could peak between 9% and 10% in 2024, compared to 7% pre-pandemic. With both auto and credit card payments under strain, the industry is bracing for continued financial stress among consumers. Auto finance professionals must stay vigilant in an evolving landscape influenced by fintech innovations, shifting market dynamics, and economic pressures. By leveraging technology, adapting repayment structures, and proactively addressing delinquencies, industry players can navigate these trends effectively.

Kuady, a cutting-edge digital wallet solution focused on financial inclusion, has joined forces with BridgerPay, a global omnichannel payment orchestration platform, to enhance digital payment solutions for merchants across Latin America, as stated in Fintech Global. The partnership aims to improve the region’s digital payments landscape by offering businesses a frictionless and localized payment experience. Merchants in Chile, Peru, Mexico, Ecuador, and Argentina will now have greater access to streamlined and secure transactions through this collaboration. By integrating Kuady’s user-friendly digital wallet with BridgerPay’s platform, businesses will be able to optimize their payment processing systems, ultimately improving customer satisfaction and transaction efficiency. Launched in July 2024, Kuady is a next-generation digital wallet designed to revolutionize financial management for both merchants and users. The app offers a wide range of payment methods and financial services, simplifying transactions and fostering financial inclusion across the region. Meanwhile, BridgerPay connects businesses to over 1,000 integrated payment providers, allowing them to streamline and optimize payment processing through a single platform. Kuady CEO Lorenzo Pellegrino expressed excitement about the partnership, stating: “We are thrilled to integrate Kuady with BridgerPay, extending our secure and seamless payment solutions to even more businesses across Latin America. This partnership aligns with our mission to empower merchants with innovative financial tools that drive growth and customer satisfaction.” BridgerPay’s PSP Partnership Manager, Matthew Boundy, echoed Pellegrino’s enthusiasm, emphasizing the benefits of the collaboration: “At BridgerPay, we are dedicated to offering merchants the most flexible and effective payment solutions. By integrating Kuady, we are enhancing our platform’s ability to serve businesses in Latin America, providing them with a powerful tool to drive growth and improve the customer payment experience, and better approval & conversion rate that increases consumer acquisition.” With this partnership, Kuady and BridgerPay are set to transform digital payments in Latin America, offering merchants and consumers enhanced security, convenience, and efficiency. This collaboration marks a significant milestone in the evolution of financial technology in the region.

IBM has unveiled its 2025 Outlook for Banking and Financial Markets, shedding light on the evolving landscape of the banking sector, as highlighted in Fintech Global News. This annual forecast, published by the IBM Institute for Business Value, highlights the profound impact generative AI and emerging technologies will have on financial institutions worldwide. According to the study, generative AI is set for widespread adoption across the banking industry. While only 8% of banks had implemented the technology systematically last year, a staggering 78% are now integrating it in a more strategic and tactical manner. This shift signifies a transition from experimental pilot programs to full-scale deployment, underlining a broader movement towards agentic AI. As banks refine their service offerings, this new approach is expected to redefine customer interactions and operational efficiencies. The report also notes an increasing divide in financial performance among banks as they restructure their business models. Successful execution of these new strategies will determine the industry’s leaders, distinguishing them from competitors who fail to adapt. Additionally, 60% of surveyed banking CEOs recognize the importance of embracing automation-related risks to maintain a competitive edge. The integration of AI-driven automation is seen as crucial for optimizing operational processes, enhancing customer service, and strengthening risk management frameworks. Consumer preferences are also shifting toward digital banking solutions, with over 16% of global clients now favoring a fully digital-first banking experience. This trend signals a transition from conventional digital services to more advanced offerings, such as embedded finance solutions and tailored advisory services for high-net-worth individuals and small-to-medium enterprises. Commenting on the findings, Shanker Ramamurthy, IBM Consulting’s Global Managing Director for Banking & Financial Markets, stated: “We are seeing a significant shift in how generative AI is being deployed across the banking industry as institutions shift from broad experimentation to a strategic enterprise approach that prioritizes targeted applications of this powerful technology. As banks and other financial institutions around the world gear up for a pivotal year of investing in transformation, technology, and talent, we anticipate their efforts coalescing around initiatives using generative AI to level up customer experience, boost operational efficiency, reduce risks and modernize IT infrastructure.” IBM’s report is based on insights from C-suite executives, bank customer behavior trends, and economic data spanning key global markets, including the United States, Canada, the European Union, the United Kingdom, Japan, China, and India. The study provides valuable guidance for financial institutions navigating the dynamic shifts in the banking landscape.