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The 2026 Tearsheet AI Innovation Awards: Recognizing the Builders of AI-Powered Finance

AI is moving from a promising capability to a core layer of financial services infrastructure, with banks, fintechs, and technology providers racing to turn experimentation into meaningful applications.

The Tearsheet AI Innovation Awards recognize the organizations using AI to rethink products, processes, customer interactions, and the broader future of finance.

This year’s winners represent the companies moving beyond the hype — applying AI in ways that create tangible value and shape where financial services go next.

2026 Winners of the AI Innovation Awards

Best Chatbot: Fifth Third Bank

Fifth Third Bank earns the Best Chatbot Award for transforming its AI assistant from a traditional support bot into a conversational entry point for digital banking. Jeanie, embedded within the bank’s mobile app used by more than 2.4 million monthly customers, helps users complete more than 150 banking tasks through natural-language interactions, from replacing a debit card and disputing transactions to sending money and finding a banker. The results have been measurable: intent recognition has improved from roughly 20% to 90%, while self-service resolution has climbed from 3% to 42%, enabling more customers to resolve issues without changing channels. Fifth Third has also expanded Jeanie’s Spanish-language self-service capabilities, making the experience more accessible to a broader customer base. Rather than treating AI as a standalone feature, the bank has woven it into the core customer journey, creating a simpler, more intuitive digital banking experience while laying the groundwork for more agentic interactions in the future.

Data Innovation Award: Plaid

Plaid wins the Data Innovation Award for redefining how financial data is transformed into actionable intelligence across lending, fraud prevention, and financial decision-making. The company has built AI foundation models and network intelligence that interpret real-time financial behaviour across its ecosystem of more than 12,000 financial institutions and 9,000 apps, enabling more accurate credit, fraud, and payment risk decisions. Its transaction foundation model improved income classification accuracy by 48%, its sequential model reduced credit default risk by 13.6% at the same approval rate, while LendScore, Plaid’s real-time cash flow-based credit risk score, reduced lending risk by 41% without sacrificing approvals. By building an intelligence layer on top of financial data, Plaid is enabling institutions to make faster, fairer, and more accurate decisions.

AI Startup of the Year: Titan

Titan wins the AI Startup of the Year Award for building AI specifically for the realities of regulated banking. The company has developed a banking-native AI platform that combines domain-specific models, a proprietary banking context layer, and governed AI agents to automate workflows across risk, compliance, underwriting, and operations while maintaining auditability and regulatory oversight. Since emerging from stealth in late 2025, Titan has tripled its annual recurring revenue as financial institutions increasingly replace ungoverned AI tools with a platform designed to be explainable, traceable, and examiner-ready, demonstrating that AI adoption in banking requires not just intelligence, but governance.

AI Company of the Year: Casap 

Casap takes home the AI Company of the Year Award for applying agentic AI to one of the most operationally complex challenges in financial services: payment disputes and first-party fraud. Rather than simply routing cases, the platform automates the entire dispute lifecycle – from claim intake and evidence gathering to fraud detection, chargeback filing, and customer communications – while maintaining regulatory compliance and a fully auditable record of every decision. At Chartway Federal Credit Union, average dispute resolution times dropped from up to 90 days to 12 days, per-claim costs fell nearly 90%, write-offs declined 72%, and chargeback win rates improved 95%. Founded in 2023 by former Robinhood and Chime product leaders, Casap has brought advanced, enterprise-grade AI capabilities to credit unions, regional banks, and fintechs, showing how agentic AI can fundamentally modernize complex banking operations.

Best Alternative Data Provider: Carpe

Carpe wins the Best Alternative Data Provider Award for helping insurers make faster, more informed underwriting decisions with AI-driven intelligence built specifically for small commercial insurance. The platform continuously analyzes signals from company websites, review platforms, social media, and commercial sources to build a real-time view of more than 50 million businesses, covering roughly 90% of insurable U.S. small businesses. Insurers have reduced underwriting touches by 20%, cut review times by 15-30 minutes per application, lowered adverse selection by 40%, and improved loss ratios by 1.5 points. By embedding real-time alternative data directly into underwriting workflows, Carpe gives carriers a more accurate picture of business risk, helping them quote faster, segment more precisely, and improve underwriting performance without compromising risk discipline.

Best Use of Agentic AI: Intuit

Intuit wins the Best Use of Agentic AI Award for turning QuickBooks into a connected intelligence layer that functions as an autonomous financial operating system for small businesses. Powered by Intuit Intelligence, embedded AI agents work across accounting, payroll, payments, invoicing, cash flow, and tax to proactively execute end-to-end workflows, helping businesses get paid faster, simplify compliance, and reduce manual work, all while human experts ensure quality. Users save an average of 13 hours per month; AI-powered invoicing helps businesses get paid four days faster, and the Accounting Agent cuts reconciliation time by 66% while improving accuracy. By embedding autonomous AI across core financial workflows, Intuit has shown that agentic AI is evolving from a productivity tool into an operating layer that gives businesses the clarity, control, and confidence to run and grow, with the ability to run parts of a business actively.

AI Product of the Year: Cascading AI

Cascading AI (Casca) wins the AI Product of the Year Award for reimagining small business lending with an AI-native loan origination platform. The platform embeds AI agents across the lending process, automating more than 100 manual steps, analyzing thousands of pages of financial documents in minutes, and performing over 40 credit and KYB checks while keeping humans in the loop. As a result, banks have automated up to 90% of lending workflows, reduced loan processing times from months to as little as one to four days, and increased lead conversions. By transforming one of banking’s most manual and time-intensive processes, Casca is making small business lending faster, more scalable, and more accessible.

Best AI Fraud & Risk Management Solution: SEON

SEON wins the Best AI Fraud & Risk Management Solution Award for rethinking fraud prevention around unified intelligence. Instead of layering AI onto fragmented systems, SEON brings together more than 900 real-time risk signals, explainable AI, fraud and AML workflows, and an open MCP architecture into a single platform, giving risk teams the context to catch AI-generated fraud and support both human and agentic risk decisions without adding friction to the customer experience. Its explainable AI cuts fraud investigations by more than 50%, while customers like TurboTenant have reduced payment fraud alerts requiring manual review by 80% while uncovering account takeover patterns their previous systems missed. By creating a shared intelligence layer for fraud and compliance, SEON is helping fintechs, eCommerce, and betting and gaming organizations make faster, more informed risk decisions in an increasingly AI-driven landscape.

Congratulations to this year’s finalists across the AI Innovation Awards categories:

  • Best Alternative Data Provider: Plaid
  • AI Startup of the Year: F2
  • Best Use of Agentic AI: nCino and Lili
  • AI Product of the Year: Intuit and Lili
  • Best AI Fraud & Risk Management Solution: Plaid and Carpe
  • Data Innovation Award: Teachers Federal Credit Union and Shield Financial Compliance
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Paper still defines payments’ last mile. J.P. Morgan Payments thinks AI and robotics can tackle that.

The dominant narrative in payments is real-time payments, stablecoins, instant payment rails, always-on cash flow, and near-seamless cross-border movement. But speed at the point of settlement doesn’t solve what happens before and after money moves.

One of the world’s largest payments businesses processed more than 130 million checks in 2025. Behind every check was a chain of envelopes, remittance slips, invoices, inconsistent formats, and manual reconciliation.

That’s the gap J.P. Morgan Payments is targeting with its multi-year effort, using AI, robotics, computer vision, and large language models to digitize and automate its lockbox operations. The project is about modernizing one of the most manual information-processing systems still embedded inside corporate payments.

“Checks are still a meaningful part of the U.S. payments landscape,” says Michelle Conklin, Head of Receivables and Public Sector at J.P. Morgan Payments. “The challenge is often not the check payment itself, but all of the manual work that comes with it: opening mail, extracting checks and remittance documents, capturing data, validating information, and handling exceptions.”

Michelle Conklin, Head of Receivables and Public Sector at J.P. Morgan Payments

“That is where we see a real opportunity to drive value,” she notes. “When we automate those steps with AI and robotics, we can scale more easily and make the process faster and more accurate. This is a reminder that innovation in payments is not only about faster settlement. It is also about removing friction from the end-to-end process, such as what we’re advancing in the lockbox space.”

When AI finally became good enough for the messy middle

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What Fifth Third’s invitation to Project Glasswing says about the bank’s role in the financial system

Banking scale has been measured in assets, deposits, and branches. In 2026, another metric may be emerging: how much of the country’s financial activity would be disrupted if your systems stopped working.

That helps explain why Fifth Third’s recent invitation to Anthropic’s Project Glasswing holds importance. The bank has been invited into an invite-only cybersecurity program that grants a small group of vetted partners early access to the Claude Mythos Preview model.

Project Glasswing is a controlled-access initiative, bringing together a limited set of trusted organizations to test advanced AI systems in real-world security environments. The focus is on detecting and helping remediate critical software vulnerabilities at scale. Anthropic has said its Mythos models have already identified more than 10,000 vulnerabilities in widely used, systemically important software, and Glasswing extends that capability to selected partners before wider deployment.

That signals the direction Fifth Third is moving in. The same week, it rolled out a refreshed small-business platform to over 240,000 customers.

From banking customers to orchestrating flows

Fifth Third’s new small-business offering is a digital banking upgrade built around speed and access – Early Pay brings forward incoming funds, digital lending speeds up capital access, Zelle shortens payment cycles, and tap-to-pay streamlines merchant acceptance. The unifying theme is flow.

After its merger with Comerica, Fifth Third now ranks as the 9th-largest U.S. bank with about $294 billion in assets, strengthening its footprint across several fast-growing commercial markets.

Scale matters, but operational density matters more. The more businesses, payrolls, government programs, and payment streams flowing through a bank, the more consequential its systems become.

Why Anthropic cares

Bryan Preston, Fifth Third’s Chief Financial Officer, attributed the bank’s inclusion in Project Glasswing to its role in administering Direct Express, processing payments for U.S. Customs, and handling large volumes of payroll activity across the country. 

These are not ordinary banking products. They are payment flows tied to government programs, public-sector operations, and employer payroll systems that millions of people depend on.

Basically, Fifth Third was selected because disruptions to its systems could ripple far beyond the bank itself.

The emerging hierarchy of banks

Size used to define banks – now their function does. The key distinction is between customer-facing banks and those that operate financial infrastructure.

Fifth Third’s recent announcements suggest it is moving toward the latter category.

The broader shift is that regional banks are increasingly being discussed alongside infrastructure providers, payment operators, government disbursement systems, and national cybersecurity efforts. Increasingly, a bank’s importance may be measured by systemic dependence on how critical an institution is to keeping the financial system smoothly functioning.

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The 3-Min Read: Why Anthropic is becoming AI’s reference point

In the span of just twelve months, Anthropic has shifted from being one of several frontier AI labs to a gravitational center of the industry. The change is driven by a compounding sequence of capital inflows, enterprise adoption, and infrastructure-scale positioning that increasingly resembles platform formation rather than startup growth.

The clearest signal came on May 28, 2026, when the company closed a $65 billion Series H round at a $965 billion post-money valuation, briefly making it the world’s most valuable AI startup ahead of OpenAI. Its valuation has climbed rapidly from $183 billion in Series F to $380 billion in Series G, and nearly doubled again in the latest round.

This momentum is being driven by strong enterprise demand. Anthropic now reports an annualized revenue run-rate above $47 billion, largely fueled by adoption of its Claude models in coding and agent-based workflows. Increasingly, Claude is being embedded into production systems where productivity gains translate directly into cost reduction.

Coding has become the primary growth engine, marking the second signal. Software development is now the operating layer of modern enterprises. As Claude moves deeper into these workflows, Anthropic’s identity shifts from product builder to infrastructure provider.

But rapid growth comes with pressure. The company is close to its first operating profit, yet compute costs remain heavy. In Q1 2026, it spent 71 cents for every dollar of revenue on compute, expected to improve to 56 cents in the next quarter. Efficiency is improving, but only because demand is rising fast enough to absorb training and inference costs. Yet Anthropic has also cautioned that planned infrastructure investments could make profitability difficult to sustain over the full year. This tension between scaling demand and managing compute costs is now a pressing challenge for frontier AI companies. Bankers and investors are increasingly focused on Anthropic’s token economics and compute costs, worried that rising AI usage costs could pressure margins and make it harder to justify its valuation after an IPO.

Which leads to the third signal: capital structure alignment. On June 1, Anthropic confidentially filed for an IPO, working with Morgan Stanley and Goldman Sachs, alongside J.P. Morgan Chase. Anthropic leadership notes that frontier model training requires sustained access to large-scale capital, and public markets are structurally better suited to that need. 

Alongside expansion, Anthropic is also moving carefully on safety and control. Through Project Glasswing, the company has scaled access to its Mythos cybersecurity model from roughly 50 organizations to 150 across more than 15 countries. The system has already helped identify more than 10,000 high- or critical-severity vulnerabilities in widely used software.

The same capabilities used to detect vulnerabilities could also be used to exploit them, so the model distribution is limited to vetted partners. Expansion happens through controlled channels rather than open release.

Anthropic is also exploring broader deployment of the model through discussions with the EU cybersecurity agency ENISA, which could extend access beyond the US and UK for the first time – widening its user base through institutional gatekeepers.

What Anthropic is becoming

These shifts show Anthropic evolving into three roles:

  1. A capital-scale company moving toward public-market size with trillion-dollar ambitions.
  2. An embedded intelligence layer inside enterprise systems, especially in software development.
  3. A controlled provider of high-risk AI systems, distributed through strict governance frameworks.

Anthropic is trying to scale and contain at the same time. The broader question is whether the economic and governance structures around frontier AI can scale at the same pace as the systems they are now trying to contain.

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What Citi Sky says about the reinvention of client relationship models in wealth management

Wealth management follows a familiar rhythm where advisors book meetings in advance, send market notes after the fact, and make decisions that move at the speed of inboxes and calendars.

Citi Wealth is aiming to break that cadence with Citi Sky, built in partnership with Google Cloud and Google DeepMind. The bank describes it as an always-on AI-powered member of the Citi Wealth team that can talk, respond, and surface insights in real time.

Citi’s Head of Wealth, Andy Sieg, says the intent is to move away from the fragmented experience clients have lived with for years. “For decades, managing your financial life meant navigating apps, calls, and meetings,” he said in a press release. “With Citi Sky, you simply ask – and act. This is the shift from interface to intelligence, from transactions to outcomes.”

The Citi-Google Cloud relationship extends beyond a typical vendor arrangement. While Google provides the underlying infrastructure and AI stack, the collaboration evolved into a deeper co-development effort. Teams from Google Cloud and Google DeepMind worked alongside Citi engineers to shape Citi Sky’s architecture, conversational experience, and guardrails, while Citi retains ownership of the client experience, data, and decisioning layer.

From infrastructure modernization to client-facing intelligence

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