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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IMF warns tokenization could bring crypto risks into global financial markets
Tokenization, the representation of real-life assets on a blockchain, could reshape both crypto markets and traditional finance, while introducing new risks that regulators are not yet equipped to manage, according to the International Monetary Fund (IMF).
In a new report, the IMF described tokenization as more than a technical upgrade to markets. By moving assets like money, bonds and funds onto shared blockchains, transactions can settle instantly, cutting out intermediaries and reducing delays that define today’s markets.
The IMF says the “atomic settlement” that tokenization brings to the financial world could lower counterparty risk and force firms to manage liquidity in real time.
“Stress events are likely to unfold faster, leaving less time for discretionary intervention,” the report reads. “Therefore, ensuring stability requires that tokenized asset management remains anchored in safe settlement assets, legally recognized finality, and robust governance arrangements.”
The report points to stablecoins — tokens whose value is pegged to a fiat currency — as a key bridge between crypto and traditional finance. These could become widely used settlement assets across tokenized platforms, the report said.
Still, their reliability depends on reserves and redemption systems, leaving them exposed to runs under stress.
The IMF also warned that faster, automated markets could amplify volatility, while smart contracts that trigger margin calls or liquidations may accelerate selloffs during downturns. Such rapid declines have been seen in crypto markets,
Tokenized assets also can move instantly across jurisdictions, complicating oversight and raising concerns about capital flight and currency substitution in emerging markets, the IMF wrote.
The organization called for clearer legal frameworks and stronger global coordination, arguing that without them, tokenized finance could deepen fragmentation rather than improve efficiency.
Tokenization has been a growing theme in the crypto sector. Real-world assets added to blockchain rails have already topped $23.2 billion according to DeFiLlama data. Excluding stablecoins, the majority of that figure is in the form of tokenized gold or money market funds.
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‘Hidden helpers’ supporting people struggling to manage their finances digitally
Some people are relying on potentially risky workarounds to manage their finances, a report has found.
Friends, family, carers and neighbours are spending hours each month patiently helping others with basic banking tasks, yet many “financial helpers” are doing so without any formal authority and help is often based on trust, according to a survey.
The research was led by consumer finance expert Faith Reynolds, with support from cash access and ATM network Link.
YouGov surveyed nearly 850 people across the UK who had helped someone with their banking or money management between December 2024 and December 2025.
The report found that people being helped often log in themselves with a helper beside them.
But a quarter (26%) of people surveyed said the person they help shares passcodes or security details with them.
And 17% said the people they help allow them to log in on their behalf on the helper’s device.
The report said: “Financial help is increasingly essential because, as branches have closed and banking has become digital, the responsibility for navigating complexity and preventing fraud has quietly shifted from institutions to individuals and families.”
More than half (54%) of people said they have no formal authority or access rights at all, meaning many people are relying on informal workarounds to provide the help needed.
While many helpers said they worry they will be accused of taking advantage of the person they are helping, 43% highlighted the risk of fraud and scams as a top concern for the person being helped.
Three in 10 (28%) said they had helped to stop or prevent scams or fraud.
The top tasks helpers selected include checking account balances, assisting with online payments or passcodes when shopping online, and making or scheduling payments.
To provide this support, financial helpers use mobile banking apps the most, followed by online banking via websites and ATMs.
The support provided is also not limited to banking, with 45% of helpers assisting others to use digital devices, 41% helping with managing utilities or bills, and 31% helping with using or setting up their television.
Nearly a third (31%) help setting up health appointments and 28% set up broadband or internet services.
Financial helpers are often fitting in helping alongside work and family commitments, such as children and jobs.
One helper told researchers they had been helping “about five years when their bank branch closed… They asked me for help after throwing their phone across the room because they couldn’t even log in.”
Another helper said: “Because of the rise of AI and scams, my father fell victim to this and couldn’t believe that the person wasn’t real.
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