Also Read: EXL Partners with NVIDIA to Advance Fraud Detection and Transaction Intelligence

“We’ve done the work on the backend to make our data AI-ready, build the retrieval infrastructure, and partner with best-in-class AI providers, so that customers can simply put S&P Global to work in the platforms they already use. As agentic workflows become the norm, we deliver value by ensuring that customers can access our data seamlessly and accurately, wherever they work.” Highlighting the strategic security benefits for regulated markets, Frank O’Dowd, Chief Revenue & Commercial Officer of Cohere, added, “By combining S&P Global’s financial intelligence with Cohere’s enterprise‑grade sovereign AI platform, we’re giving financial institutions a secure foundation to build agentic workflows wherever their data lives that deliver measurable impact. Regulated industries need AI they can trust with their most sensitive workloads, and they want it deeply connected to the proprietary data that drives their business. This collaboration marks a major step forward in how the global financial ecosystem puts high‑trust AI to work.”

Read More: S&P Global Expands AI Ecosystem Reach with Cohere to Power Trusted, Agentic Workflows for Financial Institutions

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“For years, analysts modeling esoteric deals had to either force them into templates that don’t fit or rebuild everything from scratch in a spreadsheet,” said Altin Kadareja, Co-Founder and CEO of Cardo AI. “The tools simply weren’t built to model a deal across its full lifecycle, through ramp-up and reinvestment, against live market data. That’s the problem we solved.”

As private credit has expanded into data center financings, cell tower deals, buy-now-pay-later receivables, music and other royalty rights, and other esoteric assets, the tools used to model these structures have not kept pace. Analysts have been left to adapt legacy engines built for public ABS deals.

The new tool brings structured-credit modeling rigor, waterfalls, tranching, eligibility tests, covenants, and cash flow simulation, to the asset-based and specialty finance collateral that legacy engines were never built for. Purpose-built for esoteric and non-standard asset classes, it pulls live market data directly into cash flow simulation, accrual, covenant monitoring, and stress testing, and lets teams model deal structures across their entire lifecycle, not just the steady state.

Also Read: Kion Advances FinOps+ With Anthropic Token Spend Management and Automated Governance Controls

During the ramp-up phase, analysts can model the structure as collateral is acquired toward target par, testing how partial portfolios, warehouse financing, and timing affect the waterfall before a deal is fully invested. Through the reinvestment period, the tool models the redeployment of principal proceeds into new collateral under the deal’s eligibility criteria and reinvestment rules, so projected cash flows reflect how the structure is actually managed over time, rather than assuming a static, fully-ramped pool.

Cardo AI’s Reference Rates module supports SOFR, SONIA, EURIBOR, and custom adjusted indices such as “EURIBOR 3M + 20bps.” Powered by Bloomberg data, the module replaces batch uploads with live forward-curve data pulled directly into cash flow simulations and daily accrual calculations, so pricing reflects current market conditions rather than the last manual refresh. The engine accepts forward curves, interest-rate stresses, and custom yield-curve inputs per index and tenor combination, allowing analysts to run portfolio stress tests against live market curves instead of static estimates.

“Insurance investors must run independent scenario analyses to meet regulatory requirements, but today they only have access to static cash flows, which limits their ability to meet those requirements,” said Marco Masotto, Head of Product of Cardo AI. “Bringing live curves and full-lifecycle modeling into a single engine gives them the dynamic cash flows those analyses depend on.”

Source: BusinessWire

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“Credit managers have always faced the same fundamental challenge: The intelligence and data that informs their decisions and the systems that execute them have lived in different worlds,” said Kent Collier, Founder and CEO of Octus. “With Sky Road, we began collapsing that gap and embedding Octus intelligence and data directly into portfolio management systems. With LevPro joining our suite, we expect to further serve credit managers at every stage of their journey, from the firm launching its first CLO to the multi-strategy platform managing billions in complex credit vehicles. That is what it means to be the essential credit platform.”

The transaction will advance a vision Octus has been executing since its acquisition of Sky Road in June 2025: A single, vertically integrated platform where credit professionals can move from market intelligence to investment-decision analytics to trade workflow and portfolio management and monitoring without losing context or stitching together point solutions from multiple vendors.

Also Read: Airwallex Acquires Leapfin, Expanding Financial Lifecycle Capabilities

“LevPro was built on a simple belief that front-office software should work for credit managers, not against them,” said Ryan Barrows, CEO of LevPro. “Upon closing, joining the Octus ecosystem will mean our clients have access to the deepest credit intelligence and data in the market, natively connected to the workflows they rely on every day. Once combined, we expect credit managers to get something they have never had before in a single platform that takes them seamlessly from market signal to executed trade.”

“LevPro’s clients are exactly the kind of forward-thinking credit managers we built this ecosystem for,” said John Borse, Head of Octus Sky Road. “They will gain direct access to Sky Road’s compliance and optimization platform and to the breadth of Octus intelligence and data while Sky Road clients will especially benefit from LevPro’s exceptional proprietary and embedded workflows. This is truly a game changer for our industry.”

The intelligence and data advantage that sets a new bar for the industry

What distinguishes the Octus platform from every other portfolio management system offering in the market is the intelligence and data layer underneath it. Octus’ global team of more than 250 financial analysts, legal analysts and expert journalists produces over 60,000 stories annually, covering 6,600+ companies across the full credit lifecycle, from primary issuance through distressed restructuring.

That intelligence is already natively embedded into Sky Road, where research management, real-time news alerts, public and private company financials via Octus Fundamentals and the FinDox document management repository are accessible directly within the portfolio management workflow. Upon closing, LevPro clients will gain access to the same layer. No other portfolio management system or order management system provider offers this depth of proprietary, expert-verified intelligence as a native capability rather than a third-party feed.

Serving private credit’s most critical workflow gap

The combination will also address a longstanding gap in the private credit market. As private credit has grown into one of the most dynamic segments in global finance, managers have been forced to manage deal origination in CRM tools, underwriting in spreadsheets and portfolio oversight in systems designed for public markets.

LevPro’s private credit module, encompassing sourcing CRM, deal pipeline management, IC approval workflows and funding and allocations, will sit within the same ecosystem as Sky Road’s institutional-grade portfolio management and Octus’ first-to-market deal origination intelligence. For the first time, a private credit manager will be able to move from Octus deal intelligence alongside fundamental and covenant data to LevPro deal capture to Sky Road portfolio monitoring without leaving a single platform family.

Source: BusinessWire

The post Octus Signs Definitive Agreement to Acquire LevPro, Advancing Vision for a Market-Leading, Vertically Integrated Platform for CLO and Private Credit Managers appeared first on ITDigest.

Also Read: Bank of America Set to Launch Global Cross-Border Real-Time Payments Solution

“Every financial institution is sitting on decades of transaction data that holds the answer to their biggest challenges fraud, risk, underwriting, customer experience. By integrating the Build Your Own Transaction Foundation Model developer example with EXL’s deep financial services expertise, financial institutions create a shared intelligence fabric that drives smarter decisions and better customer outcomes.” Emphasizing how the alliance eliminates traditional organizational silos, Vikas Sharma, head of banking and capital markets at EXL, added, “The next frontier of enterprise AI is built on unified transaction intelligence. For years, firms have built separate models for fraud, underwriting, risk and customer engagement, but the future belongs to institutions that can create a unified intelligence layer across all transaction activity. By leveraging this new blueprint with EXL’s deep domain expertise and AI engineering capabilities, we are helping clients build that foundation faster and at enterprise scale.” Ultimately, this expanded roadmap empowers regulated organizations to confidently scale enterprise AI and production-ready agentic workflows.

Read More: EXL announces integration with NVIDIA Transaction Foundation Model workflow to help financial institutions build next-generation AI for fraud, risk and transaction intelligence

The post EXL Partners with NVIDIA to Advance Fraud Detection and Transaction Intelligence appeared first on ITDigest.

The acquisition strengthens Airwallex’s comprehensive suite of solutions, allowing businesses to seamlessly transition operational transaction data into GAAP-ready financials. Integrating Leapfin’s deep expertise in revenue accounting with Airwallex’s global infrastructure will offer global finance teams a strong foundation for the entire record-to-report process. The companies plan to launch new product capabilities in the coming months, building on Leapfin’s technology to simplify reconciliation, revenue recognition, and other record-to-report processes.

“Finance teams today are managing unprecedented complexity, operating across multiple entities, currencies, and fragmented data systems,” said Jack Zhang, CEO and Co-founder of Airwallex. “Leapfin has solved a notoriously difficult engineering problem by turning messy transactional data into an auditable, single source of truth. Bringing Leapfin’s powerful data engine and accounting AI agents into the Airwallex ecosystem allows us to close the loop on the entire financial lifecycle, from accepting payments to closing the books.”

Also Read: Clerri Integrates Patient Financing Through New Cherry Partnership

Airwallex’s infrastructure processes over $266 billion in annual transaction volume and serves more than 250,000 customers globally. The addition of Leapfin ensures that these high-growth businesses can accelerate reconciliation, eliminate manual spreadsheets, and automate revenue recognition logic at a global scale.

“We started Leapfin to give finance teams a stronger foundation than disconnected legacy systems and manual workarounds,” said Ray Lau, CEO and Co-founder of Leapfin. “By joining forces with Airwallex, we have the backing of a global platform to accelerate our roadmap, scale our engineering resources, and deliver even greater value to the customers who trust us with their critical financial workflows.”

“Reliable financial AI cannot run on a swamp of spreadsheets; it requires structured, clean, and immutable data,” added Erik Yao, CTO and Co-founder of Leapfin. “With our automated subledger and accounting AI agents, we look forward to deeper product collaboration with the Airwallex team to build the future of finance technology.”

Leapfin’s core product, leadership, and engineering teams will continue operating seamlessly, ensuring continuity for existing customers while scaling capabilities under the Airwallex umbrella.

Source: BusinessWire

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According to Gartner, worldwide spending on AI is forecast to total $2.52 trillion in 2026, a 44% increase year-over-year. As that investment grows, organizations are struggling to understand how AI tools are being used across their business, how that usage is contributing to rising costs, and which projects are delivering real returns.

“AI spend is becoming more complex because it is not limited to engineering or AI teams. It is happening across the business, from marketing and sales to product and operations,” said Tatum Tummins, Senior Product Manager at Kion. “Customers are being pushed to invest in AI, but without visibility into which teams and projects are driving usage, they are left reacting to costs after the fact. As organizations begin to grapple with token economics and other AI consumption models, understanding the drivers behind token spend becomes just as important as tracking the bill itself. With Kion v3.16, we’re helping organizations bring that spend into view and manage it with the same governance framework they already use for cloud.”

Also Read: Finout Launches AI Agent Suite for Enterprise FinOps 

Kion FinOps+ v3.16 includes:

• Direct Integration with Anthropic, bringing AI provider spend into the same platform used for cloud cost management. Teams can view, allocate, budget, and report on AI usage costs alongside AWS, Azure, GCP, and OCI spend without relying on separate provider dashboards. Set budget thresholds and get notified before AI token costs exceed expectations. This gives organizations a clearer understanding of, and control over, AI token costs by individual users, teams, or business units, ultimately helping organizations begin their token economics journey. Teams can now more effectively manage their AI, Cloud, and SaaS spend through a unified financial management framework built for enterprise engineering and finance teams.
• Built on Kion’s native policy engine, Automation Policies gives teams a dedicated place to manage common cloud and AI hygiene tasks, including FinOps automation, with a set of out-of-the-box policies covering the most common use cases: automatically tagging resources, scheduling instances to power off during non-business hours, and deleting orphaned resources from sandbox environments to eliminate waste without manual intervention. One of the most popular, Auto-Tagging Resources, automatically applies tags at the cloud provider directly. These tags improve cost visibility in shared accounts and make it easier to identify resource ownership for teams and automated workflows, without ever relying on manual tagging efforts.
• SKU Meter in Spend Reports provides more granular visibility into cloud costs and aligns with the FOCUS specification. Teams can analyze spending based on provider-native pricing units, such as AWS Usage Type, Azure Meter Name, GCP SKU Description, and OCI SKU Name, and connect it directly to your invoice. This level of detail improves cost allocation, chargeback accuracy, invoice reconciliation, all in a single multi-cloud, FOCUS-compliant dimension.

“BeyondTrust operates across a complex multi-cloud and SaaS environment, and getting clear, consistent visibility into cloud spend has been a longstanding challenge. We chose Kion because of its organizational structure, tagging compliance capabilities, and the promise of its agentic AI assistant, Lux, which we believe will dramatically reduce the manual effort our finance and cloud teams spend on cost reporting and showback today. We’re early in our rollout, but the platform’s approach to cloud financial management is exactly what we’ve been looking for,” said Tara Vagalatos, SVP of Technology Operations, BeyondTrust.

Kion v3.16 advances the company’s FinOps+ approach by connecting AI token spend visibility with the automation, reporting, and governance capabilities teams need to modernize FinOps operations. By helping organizations better understand, govern, and act on cost data across cloud and AI investments, Kion is empowering teams to operationalize FinOps through AI-powered visibility, automation and intelligent cost management.

Source: BusinessWire

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The post ITDigest’s Weekly News Roundup Featuring Microsoft, NVIDIA, Experian, Mayo Clinic, NetApp and Cisco appeared first on ITDigest.

Also Read: 2C2P by Antom Taps AWS and Generative AI to Scale Southeast Asia Payments Operations

Commenting on the milestone, Mark Monaco, head of Global Payments Solutions (GPS) at Bank of America, stated, “Around the world, policymakers and financial institutions share a common goal: making cross‑border payments faster, more transparent, more affordable, and more accessible. This new capability directly supports the G20 payment objectives while giving our clients a scalable, reliable way to move money globally—without adding operational complexity.” Furthermore, the platform integrates via host-to-host channels or application programming interfaces (APIs) to minimize technical overhead. Highlighting the system’s architecture, Daniel Stanton, Payments Product Head in GPS at Bank of America, added, “We designed this solution with simplicity, trust, and scale in mind. By combining established payment rails with real‑time capabilities and seamless integration, we’re giving clients a practical new option for global payments.”

Read More: Bank of America to Launch Cross-Border Real-Time Payments, Expanding Global Payment Choice

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Corporate credit analysts traditionally spend substantial operational windows collecting, normalizing, and verifying financial details extracted from disparate software systems. This manual, highly repetitive task often slows down corporate decision-making and elevates compliance and data entry risks. Credit Memo Builder resolves these foundational friction points directly, allowing institutional risk teams to reclaim valuable time and pivot their operational focus from administrative documentation toward strategic risk evaluations and qualitative borrower assessments.

“With Credit Memo Builder, our objective is to meaningfully improve what can often be a cumbersome credit workflow—cutting through fragmented data and enabling financial teams to operate with greater speed and consistency. By embedding AI to assist and streamline key steps in the process, we’re helping clients surface the right insights faster, while maintaining the rigor and control required for high-quality credit analysis.”

Also Read: Experian Expands Fraud Protection with Real-Time Debit Card Verification

Native Ecosystem Integration and Cognitive Data Synthesis

The underlying technical architecture of Credit Memo Builder is powered by the deep financial data, sovereign research, and macro analytics found within S&P RatingsDirect®, RiskGauge, and S&P Capital IQ Pro. Built using proprietary Cognitive Automation models and leveraging Kensho’s adaptive retrieval infrastructure, the environment unifies structured database variables and unstructured textual documents into a standardized, machine-assisted output. The system extracts and organizes details from internal repositories and public data environments—merging credit ratings, macroeconomic reports, financial statements, real-time news feeds, and earnings call transcripts into a comprehensive, analyst-ready dossier.

A primary functional attribute of Credit Memo Builder is its dynamic prompting framework, which provides a highly intuitive and predictive methodology for assembling complex underwriting files. The system emphasizes an intentional “analyst-in-the-loop” operational philosophy, granting users the flexibility to manually upload auxiliary client data and command iterative, AI-driven textual refinements to match institutional quality thresholds. To support compliance and auditability, the platform features built-in transparency mechanisms, delivering direct, in-line citations mapped back to foundational source documents alongside distinct logic tracks explaining how specific insights were computed.

Credit Memo Builder expands S&P Global Market Intelligence’s growing suite of agentic artificial intelligence tools, operating alongside the previously deployed CreditCompanion environment to deliver increased speed, consistency, and depth to institutional risk assessment workflows. S&P Global notes that Credit Memo Builder functions strictly as an analytical workflow platform and does not serve as a replacement for independent credit analysis or formal credit ratings managed by S&P Global Ratings.

The post S&P Global Launches AI Credit Memo Builder to Accelerate Credit Analysis appeared first on ITDigest.

Most enterprise FinOps teams are one or two practitioners governing hundreds of millions in annual spend across cloud, SaaS, Kubernetes, and AI infrastructure. The surface area expands every quarter. The headcount doesn’t. Finout Agents are built to close that gap and expand FinOps teams by 10X.

The Detector Agent watches for anomalies continuously, distinguishing signal from noise before escalating. The Investigator Agent traces every anomaly to root cause cross-referencing ownership lineage, spend history, and deployment records and produces a complete, source-backed case file. The Orchestrator Agent drives the fix: executing reversible remediations automatically and routing destructive actions to the right owner, with full context, via Slack or Jira.

Also Read: DXC Launches CoreIgnite to Accelerate Fintech Connectivity for Financial Institutions

“The bottleneck in FinOps has never been data it’s always been capacity to act on it,” said Roi Ravhon, CEO and Co-Founder of Finout. “Finout Agents are built on five years of enterprise cost data architecture. That’s what allows them to produce verdicts and drive fixes, not just surface more observations for an already-stretched team.”

Every agent operates on the MegaBill, Finout‘s patented unified data layer that consolidates spend across AWS, Azure, GCP, Kubernetes, Snowflake, OpenAI, Anthropic, and dozens of additional services into a single business-mapped cost model the same foundation that powers Billy, Finout’s AI FinOps assistant.

Source: BusinessWire

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