Finance
AI-powered decision intelligence is reshaping finance – SiliconANGLE
Artificial intelligence is reshaping financial services, driving automation, smarter decision-making and greater efficiency. As financial institutions seek greater transparency and reasoning in their AI applications, AI-powered decision intelligence is emerging as a critical capability.
According to theCUBE Research’s latest analysis, discussed in “The Next Frontiers of AI” podcast, emerging AI frameworks — most notably, retrieval-augmented generation models, causal knowledge graphs and AI reasoning — are reshaping how financial institutions navigate an increasingly complex, dynamic landscape.
The financial sector has long embraced cutting-edge technologies, leveraging AI to optimize risk management, automate processes and improve customer interactions, according to theCUBE Research’s Scott Hebner. However, as businesses look beyond traditional predictive models, they seek more advanced AI capabilities that provide greater transparency, reasoning and AI-powered decision intelligence.
Hebner, the podcast’s host, was joined by Jayeeta Putatunda, lead data scientist, director – AI center of excellence, at Fitch Group Inc., located on Wall Street. “Financial services have always led from the front in predictive analytics and deterministic models, but we must be cautious in our approach to gen AI,” she said. “Given the industry’s regulatory nature and the high stakes involved, we are adopting AI carefully, ensuring governance and risk control at every stage.”
How AI-powered decision intelligence is transforming finance
AI in financial services is rapidly evolving beyond basic automation and predictive analytics, according to Putatunda. Financial institutions increasingly focus on AI-powered decision intelligence to shape strategy and drive results.
“We need to solve use cases that actually drive the most value to our clients, users and even our internal teams,” Putatunda said. “If we can help with operational efficiency, reduce manual workload or enhance deep research, we will win in a significant way.”
Ensuring transparency and explainability is a key challenge in implementing AI in finance, according to Putatunda. Traditional AI models often function as “black boxes,” making it difficult for financial leaders to trace how decisions are made. As a result, many institutions are turning to AI-powered decision intelligence to improve visibility into the decision-making process.
“One of the biggest areas of concern is explainability,” Putatunda said. “In predictive models, we had processes to trace back decisions, conduct weight analysis and determine which inputs had the most impact. With AI, it becomes harder to establish that level of transparency.”
Building trust and governance in AI-driven finance
Trust remains critical in AI adoption within financial services, especially given the industry’s stringent regulatory requirements. The integration of knowledge graphs and causal AI can help enhance transparency, explainability and governance, according to Putatunda.
“Causal knowledge graphs create a dynamically adaptable data lineage that allows LLMs to ground their outputs in factual, explainable relationships,” she said. “This improves AI transparency and enhances compliance and governance frameworks.”
Additionally, AI models need to ensure they are free from biases and provide consistent, reproducible outputs. Unlike other industries, financial institutions require AI models that adhere to strict auditability and regulatory compliance measures, according to Putatunda.
“Financial firms need models that are not only accurate, but also auditable and traceable,” she said. “We must build a safe, sustainable AI pipeline that integrates human oversight at every stage.”
Looking ahead: The future of AI in financial services
The next wave of AI adoption in finance will focus on creating integrated AI ecosystems that combine multiple intelligent agents. These agents will collaborate on complex problem-solving, according to Putatunda.
“We need to move beyond single-task solutions and create goal-based AI agents that can dynamically retrieve and analyze information from multiple sources,” she said.
As RAG, causal AI and decision intelligence evolve, financial institutions can innovate while ensuring compliance and risk control. As AI technologies develop, they will redefine how financial services operate and set the stage for broader applications across industries.
For a deeper dive into this discussion, part of “The Next Frontiers of AI” podcast series, check out the full conversation:
Photo: SiliconANGLE
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Anne Arundel County is preparing to launch a new finance and e-procurement system to modernize county operations and improve how businesses interact with local government.
The new platform, called Harbor, is scheduled to go live in July and will replace the County’s legacy procurement system with a centralized cloud-based platform built on Oracle Fusion Cloud.
County officials say the new system is designed to streamline procurement and financial processes while making it easier for both existing and prospective vendors to do business with the County.
From the press release:
“Harbor is a much-needed upgrade that will streamline services for our county agencies and those who do business with the county,” said Anne Arundel County Chief Administrative Officer Christine Anderson.
The platform will serve as a single portal for supplier registration, bid opportunities, invoicing, payment tracking, and contract management, consolidating what had previously been spread across multiple systems. County leaders say the transition is part of a broader effort to modernize operations, improve efficiency, and lower barriers for businesses seeking to compete for county contracts.
For counties, procurement modernization remains an important operational priority as local governments look to improve transparency, strengthen vendor engagement, and simplify access for businesses of all sizes. Anne Arundel County has encouraged interested suppliers to review training materials and registration information ahead of the July launch.
Finance
Quadient Recognized as a Leader in the 2026 SPARK Matrix for Accounts Receivable Applications
Quadient demonstrates continued innovation in AI-driven invoice-to-cash automation and unified finance operations
Paris
Quadient (Euronext Paris: QDT), a global automation platform powering secure and sustainable business connections, announced today it has been recognized for the fifth consecutive year as a Leader in the 2026 SPARK Matrix™ for Accounts Receivable Applications by technology analyst and advisory firm QKS Group. Quadient strengthened its position in the report year-over-year, with a notable improvement in Technology Excellence, reflecting continued innovation in its AI-driven invoice-to-cash solution.
According to QKS Group, Quadient’s leadership position highlights its evolution into a comprehensive, AI-powered platform that delivers strong predictive accuracy and straight-through processing. The analyst firm also emphasized the capability of Quadient’s solutions to unify accounts receivable (AR) and accounts payable (AP), offering finance leaders greater visibility and insights into their business finances to make faster, better decisions on working capital management.
Earlier this month, Quadient announced the release of its new cash dashboard capability for AR and AP that allows finance teams to bring together traditionally siloed data in a single view. An AI assistant summarizes key metrics and provides analysis that helps finance leaders accelerate cash on hand, improve forecasting, reduce risk and uncover opportunities to optimize working capital.
“Quadient has established a strong position in the 2026 Accounts Receivable Automation market through its focus on intelligent automation, cash flow optimization and integrated financial operations,” said Sanjeevi C R, associate vice president, Enterprise Research at QKS Group. “The platform’s evolution from predictive analytics to AI-driven autonomous collections execution represents a meaningful step forward in reducing manual effort across the invoice-to-cash cycle. What differentiates Quadient is its ability to combine collections management, cash application, and payment processing with a unified accounts receivable and accounts payable ecosystem, providing finance leaders with a more holistic view of working capital performance. By enabling greater automation, enhanced cash flow visibility, and more efficient receivables operations, Quadient continues to deliver measurable value for organizations seeking to modernize their financial processes and improve liquidity management.”
QKS Group highlighted the following key strengths for Quadient AR:
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