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Fraud & Security Intelligence | Innovation | Risk Management
Liz Goldberg 0
The cost of fraud: Protecting public funds with AI

Government productivity and transparency are hot topics, with trust in public institutions declining worldwide and global public debt levels nearing 100 percent of global gross domestic product. Managing fraud, waste and abuse (FWA) is key to public sector productivity. The British Government estimates that £39.8 billion to £58.5 billion of

Fraud & Security Intelligence | Innovation
Seema Rathor 0
From data to decisions: What sets the intelligent bank apart

Banks face increasing vulnerabilities, including fraud, cyberattacks, regulatory pressures and rapidly evolving customer behaviors. To remain secure and resilient, financial institutions must do more than simply adopt new technologies – they must build intelligent, adaptive systems. This is where a data and AI platform becomes a critical engine – not

Advanced Analytics | Artificial Intelligence | SAS Events
Becky Graebe 0
On trust and responsible innovation: ‘Right now is an all-in moment’

Since AI is advancing faster than regulation and innovation is outpacing understanding, two principles must rise above the noise: trust and responsible innovation. That was the central message for industry leaders during another day of SAS Innovate 2025. Show host and recently named Chief Operating Officer Gavin Day said this

Analytics | Artificial Intelligence | Risk Management
Reyk Mikles 0
Comply, compete or collapse: The new rules of risk modeling

The financial services industry is undergoing a period of profound change, driven by a dynamic economic landscape, increased regulatory scrutiny, changing consumer behavior and rapid technological advances. Banks operating in this environment are under increasing pressure to transform their risk modeling and decision-making ecosystems in order to remain competitive. This

Artificial Intelligence | Fraud & Security Intelligence | Machine Learning
Josh Beck 0
Threat modeling for agentic systems

As agentic AI systems evolve through protocols like MCP and A2A, traditional security practices must be adapted to address new risks such as goal misalignment and tool instruction abuse. This article explores practical threat modeling strategies, including goal alignment cascades and distinguishing between parameter-only vs. instruction-enabled tool calls.

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