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AI-powered decision intelligence is reshaping finance – SiliconANGLE

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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.

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“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.”

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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.

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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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Finance

How Does Debt Move Through the Global Financial System? – OpenMarkets

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How Does Debt Move Through the Global Financial System? – OpenMarkets

Repo markets are the plumbing behind sovereign debt distribution, ensuring bonds can be financed, hedged and reused as collateral.

The journey of sovereign debt begins with government auctions and syndications, where primary dealers (large banks) and wider market participants, such as buy-side institutions, purchase bonds, which are generally offered at a discount. Corporate bonds are similar, however, issued by a firm. 

To avoid utilizing the bank’s own capital and balance sheet, dealers “repo” the bonds – selling them to cash-rich institutions like money market funds with an agreement to buy them back at a specified future date (terms vary per market). While the cash bond market is an outright purchase or sale, the repo market is treated as a collateralized loan, meaning banks have to manage the associated credit risk of the underlying bond and counterparty during the term of the trade.

Government and corporate bonds, in addition to the risk positioning in outright markets, serve as collateral to finance longs/cover shorts for market participants and are utilized in margin calls. This plumbing further assists the breadth of market participants to cash reinvest, increase leverage, enhance returns and support market liquidity. The plumbing is sensitive to some friction: 

1. Balance Sheet Pressure

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Balance sheet pressure arises when capital requirements, deriving from the implementation of Basel Standards, such as the Leverage Ratio / GSIB / LCR / NSFR / HQLA / RWA / UMR, cause banks to actively manage their balance sheet accordingly in order to optimize each regulation. This allows them to increase balance sheet efficiency and reduce/increase exposures where required to manage dynamic regulatory constraints, thus requiring banks to tightly manage scenarios that impact their business. 

The varying legal structure of each bank means the impact of measures of regulation cause different weighted balance sheet challenges for each of the banks. It is not one-size fits all. As banks navigate these challenges, it can mean they have diverging strengths, in their product offerings, at various points in the year compared to their competition. Thus, there can be situations whereby banks will be less willing to intermediate trades even if they have the cash or bonds, as they are constrained by the regulations.

2. Liquidity Stress

Simultaneously, liquidity stress can manifest when a surge in demand for cash suddenly spikes, and a contraction in supply is encountered, i.e. lenders become nervous – for example, due to heavy bond issuance or tax deadlines – causing interest rates to surge as participants compete for a dwindling pool of available funding. Additionally, collateral scarcity and sudden spikes in demand for specific bonds can cause pressures.

There have been a number of stress periods over recent years in the financing markets, which have highlighted the need to keep a liquid and functioning collateral market. Localized liquidity gaps can rapidly evolve into broader market contagion in the outright and ultimately futures markets. Consequently, the accessibility of central bank facilities and connectivity to intermediating technology venues becomes increasingly important as the speed of execution accelerates with technological advances and the market moves to faster, and increasingly automated, execution.

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Finance

Downtown Cincinnati hotel gets final public approval, but private financing still in flux

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Downtown Cincinnati hotel gets final public approval, but private financing still in flux

CINCINNATI (Cincinnati Business Courier) – The plan to build a new $540 million, 700-room Marriott convention center hotel downtown got its final public approval Wednesday, with the Port of Greater Cincinnati Development Authority agreeing to sell $130 million in tax-exempt bonds to finance the project.

The closing on the financing, however, is not expected for another 60 to 90 days. The private financing is still being finalized, although good progress is being made, said Greg Hahn, vice president of public finance for the Port.

“It’s a tough project to finance,” Hahn said, adding that the city, county, state, the Cincinnati Center City Development Corp. and Atlanta-based private developer Portman Holdings have been working “to bring this to life.”

Read the full story from the Cincinnati Business Courier.

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Finance

How to make your offer stand out in a competitive housing market

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How to make your offer stand out in a competitive housing market

With the weather finally thawed and kids out of school, spring and summer are the busiest seasons for homebuying. This can mean more options to choose from on the market — but it can also mean more competition.

Going through the work of putting together an offer on a house you are excited about, only to get beat out by other buyers, can feel like a major letdown. So, how can you make your home offer stand out if you are wading into a hot housing market? From having your own affairs in order to being flexible and savvy in the offer you craft, here are some tricks you can implement to improve your odds of winning out.

Have everything in order before bidding

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