Because single prompts are not reliable enough for business, we need to move to something called protocols. An AI protocol is like a detailed recipe or a set of instructions for your AI. It tells the AI exactly how to behave and what to do every time it performs a specific task. Instead of hoping an employee writes a good prompt, you design a protocol that guides the AI to a successful result automatically. This is the most important change happening in enterprise AI today. We are moving from simply talking to an AI to actually designing how it works. A protocol ensures the AI operates safely and consistently. As we shift from prompts to protocols, the tools we use for enterprise AI will also change. The new generation of tools will look more like system builders or visual editors. These tools will allow you to create protocols without needing to be a programmer. You will be able to drag and drop different rules, connect to approved data sources, and set clear boundaries for the AI’s behavior. Think of it like drawing a flowchart that the AI has to follow. To design a good AI protocol: A Clear Role: First, you must define the AI’s specific job. Is its role to help the customer service team answer questions, or is it supposed to help the marketing team write emails? Firm Boundaries: Next, you set clear limits. The protocol should state what the AI is never allowed to do, like giving legal advice or sharing private employee information. Approved Information: You need to tell the AI where to get its information. The protocol can direct the AI to use only the official company knowledge base or specific, approved documents. A Consistent Tone: The protocol should also define how the AI communicates. Should it be formal and professional, or should it be more friendly and conversational?
Contextual payments research reveals $240 billion e‑commerce opportunity through agentic commerce, programmable money integration, and infrastructure‑driven transactions across multiple industry sectors
This U.S. Payments Forum’s latest white paper explores the transformative potential of contextual payments within the realms of artificial intelligence (AI), 5G wireless technology, and internet of things (IoT). Contextual payments enable the promise of seamless transactions embedded within everyday activities, leveraging advanced technologies to enhance user experience and operational efficiency. By integrating AIdriven decision-making, high-speed 5G connectivity, and IoT-enabled devices, contextual payments offer an opportunity for a potentially frictionless and secure payment process that aligns with consumer behavior and preferences. The paper describes use cases, including smart retail, autonomous vehicles, smart homes, and healthcare, illustrating how these technologies can revolutionize commerce. Also addressed are critical considerations such as security, consumer consent, and infrastructure requirements. The white paper goal is to provide a broad overview to help orient and assist stakeholders considering how to navigate the complexities and opportunities of this innovative payment ecosystem. In conclusion, the combination of AI, 5G, and IoT in contextual commerce payments is set to transform the landscape of digital transactions across retail, housing, mobility, entertainment, and other sectors. Technology synergies will drive unparalleled levels of convenience and personalization in a secure way. Bringing this convenience to the consumer will shift transactional responsibilities from consumers to the infrastructure, requiring effective management of complex back-end systems to ensure seamless experiences. This white paper serves as a wide-ranging guide for helping stakeholders to better understand, prepare for, adopt, and leverage the transformative power of contextual payments and agentic commerce, highlighting stakeholder considerations such as infrastructure requirements, security, and authentication. Technological convergence offers vast opportunities for innovation in contextual payments.
Fiserv to enhance Clover with mobile ordering and payment platform CardFree’s customized order, pay, and loyalty solutions tailored to restaurants
Fiserv has acquired CardFree, an all-in-one platform empowering merchants with customized order, pay, and loyalty solutions. This transaction enhances the capabilities of Clover®, the world’s smartest point-of-sale solution, to support small businesses as they grow into larger, multi-location merchants with complex technical needs. CardFree’s platform will be fully integrated into both the Clover and Commerce Hub ecosystems, adding capabilities such as drive-through software, kiosk and sub-inventory enablement, and providing third-party software integration support in loyalty, delivery services, and property management. CardFree is a versatile, frictionless, easy-to-use mobile ordering and payment platform with patented technology that integrates across the whole order, pay, and loyalty ecosystem. CardFree integrates with nearly all POS systems and payment processors on the market – enabling merchants to use one checkout process for all orders, including third-party delivery. Takis Georgakopoulos, Chief Operating Officer, Fiserv said “Integrating CardFree’s technology into Clover enhances our platform’s scalability and flexibility, empowering hospitality businesses to drive growth through elevated customer experiences.”
FinCEN encourages cross-border sharing of information between and among financial institutions, including appropriate foreign ones
The Financial Crimes Enforcement Network (FinCEN) issued guidance that it said aims to encourage appropriate, voluntary cross-border sharing of information between and among financial institutions, including appropriate foreign ones. This information sharing can help financial institutions combat money laundering, terrorist financing and illicit finance activity involving drug trafficking organizations, foreign terrorist organizations and fraudsters. “The guidance clarifies that while financial institutions are prohibited from sharing Suspicious Activity Reports (SARs), as well as information that would reveal the existence of a SAR, the Bank Secrecy Act and its implementing regulations generally do not prohibit cross-border information sharing,” the release said. In the guidance, FinCEN said that financial institutions are better able to detect and combat illicit finance activity if they share information rather than keeping it siloed. This information can include, when appropriate, transaction records, customer and account information, and investigative materials, according to the guidance.
Bank of America sees tokenization as the next phase in the evolution of investment products, describing it as “mutual fund 3.0”
Bank of America (BAC) sees tokenization, the creation of a virtual investment vehicle on the blockchain linked to a tangible asset, as the next phase in the evolution of investment products, describing it as “mutual fund 3.0,” the Wall Street bank said in a Friday report.
Just as mutual funds first emerged in 1924 and exchange-traded funds (ETFs) reshaped investing in the 2000s, blockchain technology could underpin a new generation of financial vehicles, analysts led by Craig Siegenthaler wrote. Real-world asset (RWA) tokenization is advancing quickly. The bank noted that firms like Securitize are working with managers including BlackRock (BLK), Apollo, KKR and Hamilton Lane to issue tokenized funds. Asset manager WisdomTree (WT) built its own tokenization engine, giving it the ability to offer more than a dozen tokenized funds. According to data provider RWA.xyz the value of real-word assets represented on-chain exceeds $28 billion, largely in private credit and Treasuries. Still, regulation remains a headwind. The GENIUS and Clarity Acts address stablecoins, but leave many questions about tokenized funds unresolved. Still, the bank argues, the advantages of tokenization will drive adoption over time despite limited access for U.S. investors today. The case for tokenized equities is weaker because U.S. brokers already offer commission-free stock and exchange-traded fund (ETF) trading after Robinhood’s (HOOD) disruption in 2019, the analysts wrote. That shift pushed firms toward monetizing client cash and order flow, making tokenized versions of these assets less compelling, the bank’s analysts said. But tokenized money market funds, powered by smart contracts, could upend those cash sweep economics and open new revenue models. Distribution is still the bottleneck. Platforms offering tokenized funds remain rare, though online brokers like Robinhood, Public and eToro (ETOR) are well positioned given their crypto businesses and younger, self-custody- oriented client bases. Coinbase (COIN) may also emerge as a partner as it expands beyond pure crypto, the report added. Bank of America expects tokenized money market funds to lead adoption thanks to their attractive yields relative to stablecoins, which cannot pay interest under the Genius Act, with private credit and high yield likely to follow.
Citi Ventures invests in Spinwheel’s credential-less technology that requires only two data fields – to provide real-time, verified consumer credit data to process payments as part existing workflow, via APIs
Spinwheel, the agentic AI-powered credit data and payments platform, announced a strategic investment from Citi Ventures. The funding will support Spinwheel’s continued go-to-market growth, expand its agentic AI platform, and build out its data sets and product offerings. In addition, Citi Ventures will advise Spinwheel on product use cases that matter most to the largest financial institutions. “Spinwheel is rewiring how real-time credit data can be combined with payments infrastructure to manage consumer credit, and this aligns closely with Citi Ventures’ vision for the future of finance,” said Arvind Purushotham, Head of Citi Ventures. “We assessed the credit data landscape as part of our due diligence, and Spinwheel’s innovative platform is a leader in how U.S. consumer credit information is accessed and managed.” Spinwheel partners with lenders, marketplaces, personal financial management platforms, and other leading financial companies to provide real-time, verified consumer credit data to process payments as part of their clients’ existing workflow and operations via APIs. The company’s proprietary, credential-less technology requires only two data fields – phone number and date of birth – streamlining and simplifying user actions and delivering a more complete consumer credit profile.
National Financial Literacy Day on Capitol Hill features Pelican Invests — a digital platform that helps families stretch every dollar, explore smarter ways to pay for school, access investment advice, and discover funding opportunities
Pelican Invests, , proudly participated in Financial Literacy Day on Capitol Hill, hosted by the Jump$tart Coalition and presented on behalf of this year’s honorary co-hosts, U.S. Representatives Young Kim (R-CA-40) and Joyce Beatty (D-OH-3), co-chairs of the House Financial Literacy and Wealth Creation Caucus.. The annual event brings together policymakers, educators, nonprofits, and industry leaders to spotlight the urgent need for stronger financial education nationwide. Exhibitors include major financial services organizations as well as mission-driven innovators like Pelican Invests. At the event, Pelican Invests showcased its unique and award-winning approach to financial empowerment, which includes:
Penny the Pelican Plans Ahead — a #1 best-selling children’s book that helps kids and families start the conversation about money, savings, and planning for the future.
Pelican Invests Platform — a digital platform that helps families stretch every dollar, explore smarter ways to pay for school, access investment advice, and discover funding opportunities through its comprehensive library of tools and mobile app.
Financial Literacy Content for Schools — K-12 resources and scenario-based curriculum designed to support educators in building financial confidence and skills in the classroom.
PNC to acquire FirstBank, bolstering PNC’s national presence in high-growth markets of Colorado and Arizona, leveraging a community-based model
FirstBank, with $26.8 billion in assets as of June 30, 2025, provides commercial and retail banking services across Colorado and Arizona. FirstBank operates 95 branches, with a leading position in Colorado and a substantial presence in Arizona. The addition of FirstBank’s strong presence in these fast-growing markets will reinforce PNC as a leading national bank in the United States. The combination will propel Colorado to one of PNC’s top markets nationwide, more than tripling PNC’s branch network in the state to 120. PNC will become #1 in Denver in both retail deposit share1 (20%) and branch share (14%). Denver will become one of PNC’s largest markets for commercial and business banking. The transaction will also grow PNC’s presence in Arizona to more than 70 branches, adding 13 FirstBank branches. Building on FirstBank’s local relationships, PNC intends to expand its corporate and private banking franchises as well. “FirstBank is the standout branch banking franchise in Colorado and Arizona, with a proud legacy built over generations by its founders, management, and employees,” said William S. Demchak, chairman and chief executive officer of PNC. “Its deep retail deposit base, unrivaled branch network in Colorado, growing presence in Arizona, and trusted community relationships make it an ideal partner for PNC.” The addition of FirstBank is part of PNC’s strategy to scale its franchise through organic growth and strategic acquisition. Over the last decade, PNC has consistently achieved double-digit revenue growth in new and acquired markets, bringing the best of PNC’s people, products, and services to customers, including significant investments in branch expansion, marketing and technology. FirstBank has a multi-generational commitment to supporting the communities in which it serves, including its sponsorship of Colorado Gives Day, which has raised over $500 million for local nonprofits. PNC intends to build on that tradition to improve quality of life and spur economic empowerment through strategic investments, community development and employee volunteerism. Over the last three years, PNC’s Community Benefits Plan (CBP) has deployed more than $85 billion nationwide in support of affordable housing, economic development and small businesses, contributing $3.4 billion in Colorado and in Arizona. PNC Grow Up Great®, a more than $500 million initiative to prepare children from birth to age 5 for success in school and life through high-quality bilingual early childhood education programs and resources, has also fostered more than 1.2 million employee volunteer hours. “For decades, FirstBank has been proud to serve Colorado and Arizona with a strong community focus, deep customer relationships and dedicated commitment to our employees,” said Kevin Classen, chief executive officer of FirstBank. “In PNC, we have found a partner that not only values this legacy but is committed to building on it. Their scale, technology and breadth of financial services will allow us to offer even more to our customers, while ensuring that our employees and communities continue to thrive.”
FirstBank’s straightforward, community-based model—anchored by regional leaders in local markets—mirrors PNC’s local approach to banking and will allow PNC to bring all the capabilities of a large national bank to FirstBank’s clients.
Microsoft’s analog optical computer built with smartphone components achieves 100x faster performance and energy efficiency to solve complex banking optimization problems
Microsoft CEO Satya Nadella praised a breakthrough by the company’s research division, highlighting a prototype analog optical computer built with smartphone components that could reshape how industries solve complex problems. According to a Microsoft blog, the research team spent four years developing the analog optical computer, or AOC, using readily available parts such as micro-LED lights, smartphone camera sensors and optical lenses. Unlike traditional digital computers, which process binary data, the AOC uses light as a medium for computation. Microsoft said the prototype could be up to 100 times faster and 100 times more energy efficient at solving certain optimization problems compared to today’s digital systems, with the potential to run AI workloads at a fraction of the energy used by GPUs. The research team tested the AOC on optimization problems in both banking and healthcare. In collaboration with Barclays, the system helped simulate complex transaction settlements involving thousands of parties and tens of thousands of trades. In healthcare, researchers used the AOC’s digital twin to reconstruct MRI scans, suggesting future versions of the device could cut scanning times from 30 minutes to five. The team also mapped early machine learning tasks onto the system, showing potential for the AOC to one day run large language models with lower costs and energy consumption. Francesca Parmigiani, Microsoft principal research manager leading the project, said that the device is not yet a general-purpose computer but could solve a wide range of practical problems. Microsoft also said that it is sharing its optimization solver algorithm and a digital twin of the AOC so other organizations can test the system virtually and propose new applications.
Banks shift from KYC to KYAI, adopting algorithmic transparency with model inventories, explainability, bias monitoring, and audit logs to meet regulation and trust demands
In order to explain and defend AI-powered KYC decisions, banks should follow a 10-point checklist when picking and deploying any AI KYC tool: Model inventory: Transitioning to KYAI requires financial firms to integrate systems and processes that offer visibility into AI’s decision-making logic. Before that can happen, every AI model used within the organization must be cataloged. This inventory includes details like purpose, scope, input data, model design, and deployment status. Explainability: Explainable AI ensures that business users, regulators, and customers understand how outputs are generated. Whether through statistical metrics or visual explanations, the objective is to demystify the decision-making process. Risk assessment and classification: Risk assessment and classification provides the foundation for AI governance by systematically evaluating and categorizing AI systems based on their potential impact and regulatory requirements. This component enables institutions to allocate resources effectively and apply appropriate controls.Audit logs: Audit trails serve as the backbone of KYAI compliance. Every decision must leave breadcrumbs that regulators and internal stakeholders can trace. These logs should highlight data points, model iterations, and the reasoning behind predictions. Ideally, audits should be conducted pre-deployment and on an ongoing basis once the model is up and running. Validation and testing: Model validation and testing ensures ongoing model performance and reliability through comprehensive testing protocols, including back testing, stress testing, and challenger model frameworks. Real-time bias monitoring: KYAI ensures tools are in place to monitor for bias or anomalies in production models. For example, systems can flag when a fraud detection algorithm disproportionately targets transactions from certain regions. Model cards: Inspired by food nutrition labels, “model cards” summarize an AI model’s purpose, strengths, limitations, data sources, and potential biases. These concise documents provide an accessible overview for both regulators and team members. Updated governance frameworks: As AI models are adopted and integrated, it will be essential to continually revamp AI-specific governance policies into your existing structures. Define roles and responsibilities to monitor adherence to explainability, audit, and risk standards. Communicate with customers: Transparent decision-making builds greater customer trust. A client declined for a loan, for example, can be shown an objective explanation of why and how to improve their chances in the future. Monitor and evolve: KYAI is not a static, set it and forget it process. Teams should regularly monitor results and test accuracy, evaluate governance frameworks after new deployments and adjust processes in line with evolving regulatory requirements.