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February 25.2025
3 Minutes Read

How BNY is Pioneering AI Agents to Transform Banking Services

Futuristic AI agents concept with mechanical brain inside a box.

How BNY is Pioneering AI Agent Management

When it comes to innovation in the financial sector, BNY (The Bank of New York), founded by Alexander Hamilton, stands out as a leader in harnessing AI technology. As one of the most regulated and data-driven industries, banks have historically been slow to adopt new technologies. However, BNY's ambitious plan to integrate AI agents into its operations signifies a transformative shift in how financial institutions engage with clients and manage internal processes.

The Case for Multi-Agent Systems in Banking

BNY has developed a system known as Eliza, its enterprise AI platform that now operates with a multi-agent architecture. According to Sarthak Pattanaik, head of BNY’s Artificial Intelligence Hub, this dynamic system encompasses around 13 agents, each with specific functions. These agents collaborate and negotiate—much like a team—to provide accurate product recommendations and streamline processes for the sales team. A major advantage here is that employees can access a breadth of insights without needing to contact multiple departments, thereby reducing the time spent on mundane information gathering.

Revolutionizing Client Interaction Through AI

As BNY embraces AI agents, the impact on client interaction becomes evident. Each agent within the Eliza platform is designed to enhance customer engagement by answering specific queries related to the bank's diverse products—from liquidity solutions to payment options. This technology provides comprehensive support for customer inquiries such as currency availability for credit card launches in foreign markets, thereby creating a more informed and responsive service environment.

Building a Culture Embracing AI

It’s not just the technology itself that makes BNY's approach noteworthy; it’s the ingrained culture that supports its adoption. The bank has made Eliza accessible to all of its 50,000 employees, facilitating an AI-ready environment where team members across various functions collaborate to build custom agents. This cultural shift is essential for success; as Leigh-Ann Russell, BNY’s CIO, emphasizes, AI must be viewed as a universal tool—not just for engineers but for every employee. This democratization of AI usage is driving productivity and enabling new forms of creativity within the bank.

Partnerships Fueling AI Development

BNY's collaboration with Microsoft Azure and its open-source integrative approach using tools like Autogen and LangChain are vital to the success of their AI initiatives. Eliza’s construction around existing technologies ensures robust guardrails are in place to responsibly manage AI output. Such partnerships furnish BNY with feedback loops for continuous improvement and applicability across the financial services sector, enabling the bank to remain ahead in an increasingly competitive landscape.

The Future Outlook for AI in Financial Services

Looking ahead, the potential for AI to revolutionize the financial industry is staggering. With projections estimating AI could contribute nearly $20 trillion to the global economy by 2030, institutions like BNY are not just adapting but reshaping the way they interact with both data and their clients. BNY is focused on transitioning from basic automation to more autonomous, insight-driven operations which will enhance efficiencies and improve risk management. As the banking landscape evolves, the ability to leverage innovative AI solutions will likely become a benchmark for success.

Concluding Thoughts

The journey BNY is undertaking with AI agents is emblematic of a broader trend in the financial services sector. As they unlock the power of AI, they are fundamentally changing how banking operations are conducted and how services are rendered. For those curious about the future of banking, the narrative of BNY's Eliza and its embrace of AI agents serves as an exciting case study into what is possible as technology and finance converge. By fostering an environment where AI is not restricted to select teams, BNY is paving the way for a more efficient, inclusive, and innovative financial framework. Embracing these advancements is not merely a choice for banks; it is an imperative for survival and growth.

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04.02.2025

Dataminr Raises $85 Million to Boost Generative AI for Real-Time Security

Update Dataminr's Bold Move into Generative AI Dataminr, a leader in real-time AI detection, has garnered attention by raising $85 million to enhance its generative AI capabilities. This funding aims to improve the way the organization detects threats and responds to crises, tapping into the versatile applications of AI technology to protect organizations across various sectors. The Need for Real-Time Threat Detection in a Fast-Paced World In an era where information travels faster than ever, the demand for real-time insights is critical. Whether it's natural disasters, political unrest, or cybersecurity threats, organizations face an overwhelming volume of data that can be challenging to sift through. Dataminr’s technology leverages AI to process this data and provide actionable insights that can significantly alter how organizations respond to emerging challenges. Understanding Generative AI: What It Means for Crisis Response Generative AI has become a buzzword in the tech landscape, referring to algorithms capable of creating new content from existing data. In the context of threat detection, this means AI can analyze trends, simulate potential risks, and create predictive models that inform decision-makers. Dataminr's investment positions them to innovate in how businesses and governments react to crises effectively. Enhancing AI Agents and Making Them More Agentic As AI technology evolves, so does the concept of agentic AI, which focuses on creating intelligent systems that can act autonomously within defined parameters. By refining their AI agents, Dataminr aims to enable organizations to respond more proactively to crises without needing constant human oversight. Insights from Rivals: How Other AI Leaders Are Evolving Dataminr isn’t the only player in the arena. Other tech giants like Microsoft and OpenAI are also investing heavily in AI-driven solutions for cybersecurity. Microsoft, for example, has been integrating AI agents into its platforms to automate threat detection and enhance security protocols. This competition will likely drive further innovation and shape the industry's future. Future Trends in Generative AI and Cybersecurity Looking ahead, several trends are likely to emerge as generative AI matures. As AI agents become more sophisticated, we may see a shift from reactive to proactive measures in crisis management. This evolution could include predictive analytics that help identify potential crises before they occur, fundamentally changing how organizations plan for uncertainties. Potential Risks in AI Implementation Despite its advantages, the use of AI in critical areas like threat detection brings its own set of challenges. Ethical considerations regarding data privacy and accountability must be part of the discussion, as organizations use AI to navigate sensitive information. Transparency in algorithms and equipping users with an understanding of AI’s limitations will be vital in fostering trust. Why Understanding These Trends Matters For stakeholders, whether in governments or private industries, recognizing the impact of AI advancements is crucial in making informed decisions. With the growing adoption of AI applications, understanding the nuances of agentic AI and how they influence crisis response is vital for safeguarding operations against potential threats. As Dataminr pushes its capabilities further into the realm of generative AI, it is setting a precedent for what the future of threat detection and crisis management could look like. The implications of this investment extend beyond the immediate benefits, shaping the conversations around how businesses leverage AI to navigate challenges effectively.

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