BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:PDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20251102T010000 TZOFFSETFROM:-0700 TZOFFSETTO:-0800 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:PST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20251125T202344Z UID:DA5570B3-4DCF-4CAC-9C9F-8FD9766A8E8F DTSTART;TZID=America/Los_Angeles:20251119T180000 DTEND;TZID=America/Los_Angeles:20251119T190000 DESCRIPTION:Hosted via Google Meet - https://meet.google.com/pqw-trcy-xpg\n \nThe financial industry is entering a new phase of intelligence—one whe re AI systems are no longer just analytical tools but autonomous collabora tors capable of interpreting goals\, reasoning over complex data\, and tak ing context-aware actions. This talk explores the emergence of agentic AI systems in finance—AI architectures designed with intent\, memory\, and decision agency at their core.\n\nWe’ll examine how these systems differ from traditional automation by introducing the concept of goal-driven aut onomy: agents that plan\, execute\, and self-reflect across dynamic financ ial environments. Drawing from real-world applications such as loan underw riting\, portfolio monitoring\, and compliance intelligence\, the session will unpack how planners\, executors\, and reflectors interact within an a gentic loop to make transparent\, auditable decisions.\n\nThe discussion w ill also highlight enabling technologies—large language models as reason ing engines\, retrieval-augmented generation (RAG+) for contextual groundi ng\, and knowledge graphs for structured memory—and how they converge to form adaptive decision frameworks. Finally\, we’ll address the critical dimensions of safety\, alignment\, and regulatory oversight required to o perationalize agentic AI responsibly in financial ecosystems.\n\nParticipa nts will gain a systems-level understanding of how to engineer intent into AI\, design autonomous yet trustworthy financial agents\, and prepare for a future where decision-making is increasingly shared between humans and intelligent systems.\n\n-------------------------------------------------- -------------\n\nBy registering for this event\, you agree that IEEE and t he organizers are not liable to you for any loss\, damage\, injury\, or an y incidental\, indirect\, special\, consequential\, or economic loss or da mage (including loss of opportunity\, exemplary or punitive damages). The event will be recorded and will be made available for public viewing.\n\nS peaker(s): Dhivya Nagasubramanian\n\nVirtual: https://events.vtools.ieee.o rg/m/508173 LOCATION:Virtual: https://events.vtools.ieee.org/m/508173 ORGANIZER:pendyala@ieee.org SEQUENCE:18 SUMMARY:Talk - Systems with Intent: Designing Agentic AI for Financial Deci sioning URL;VALUE=URI:https://events.vtools.ieee.org/m/508173 X-ALT-DESC:Description: <br /><p>Hosted via Google Meet -&nbsp\; <a href="h ttps://meet.google.com/pqw-trcy-xpg">https://meet.google.com/pqw-trcy-xpg< /a></p>\n<p>The financial industry is entering a new phase of intelligence &mdash\;one where AI systems are no longer just analytical tools but auton omous collaborators capable of interpreting goals\, reasoning over complex data\, and taking context-aware actions. This talk explores the emergence of agentic AI systems in finance&mdash\;AI architectures designed with in tent\, memory\, and decision agency at their core.</p>\n<p>We&rsquo\;ll ex amine how these systems differ from traditional automation by introducing the concept of goal-driven autonomy: agents that plan\, execute\, and self -reflect across dynamic financial environments. Drawing from real-world ap plications such as loan underwriting\, portfolio monitoring\, and complian ce intelligence\, the session will unpack how planners\, executors\, and r eflectors interact within an agentic loop to make transparent\, auditable decisions.</p>\n<p>The discussion will also highlight enabling technologie s&mdash\;large language models as reasoning engines\, retrieval-augmented generation (RAG+) for contextual grounding\, and knowledge graphs for stru ctured memory&mdash\;and how they converge to form adaptive decision frame works. Finally\, we&rsquo\;ll address the critical dimensions of safety\, alignment\, and regulatory oversight required to operationalize agentic AI responsibly in financial ecosystems.</p>\n<p>Participants will gain a sys tems-level understanding of how to engineer intent into AI\, design autono mous yet trustworthy financial agents\, and prepare for a future where dec ision-making is increasingly shared between humans and intelligent systems .</p>\n<p>&nbsp\;</p>\n<hr>\n<p class="MsoNormal"><span style="font-size: 10pt\;"><em>By registering for this event\, you agree that IEEE and the or ganizers are not liable to you for any loss\, damage\, injury\, or any inc idental\, indirect\, special\, consequential\, or economic loss or damage (including loss of opportunity\, exemplary or punitive damages). The event will be recorded and will be made available for public viewing.</em></spa n></p> END:VEVENT END:VCALENDAR