Harnessing AI, IDP, and Process Intelligence for Financial Transformation

Join this roundtable to explore:

  • What Intelligent Document Processing is and the role of AI, data privacy, Large Language Models (LLMs), and Intellectual Property (IP) considerations, and discover use cases for automation, handling unstructured documents, and preventing fraud through signature verification.
  • How Process Intelligence capabilities can serve the needs of the Financial Services Industry.
  • ABBYY’s approach to AI – Purpose built AI and why Process Intelligence is a pivotal role in your AI strategy.

Private Dinner Hosted by ABBYY

Accelerating Financial Services Transformation through AI-First Platform Adoption

This session will address challenges in financial services, such as regulatory pressure, customer expectations, and competition, and highlight trends like Explainable AI (XAI) and responsible AI. It will demonstrate how EdgeVerve’s AI First Platform is designed to tackle these challenges, empowering financial institutions to achieve their transformation goals through

  • AI-powered operational efficiency and automation.
  • Enhancing customer experience and fraud detection.
  • Data-driven risk and innovation decisions
  • Customer success stories showcasing the platform’s impact.

Join to understand how the platform’s role as a strategic partner for financial institutions in an AI-driven future.

Panel discussion: Evaluating real-world practices of emissions and ethics of AI

• Overviewing ethical concerns of implementing LLMs, GenAI, models, transparency, and responsibility
• To what extent is AI considered unethical?
• Exploring the significance of AI safety and tackling risks of hallucinations in ethical audits
• Who has the answer to efficiently showcase emissions, ethics and ESGs reports supported by AI?
• Discussing potential techniques to enhance ethical data analysis and reporting using AI

 

Accurate, Trustworthy & Reliable Generative AI solutions with Graph-Powered RAG

In a landscape where the expectations for Generative AI are rapidly evolving, this session will delve into the critical role Graph technology plays in advancing Retrieval-Augmented Generation (RAG). As recognized by Gartner and other leading analysts, Graphs are now pivotal in enhancing the accuracy and reliability of Generative AI.
Attendees will learn how the integration of Graph technology with RAG not only addresses the inherent limitations of traditional models but also establishes a solid foundation for developing enterprise-grade Generative AI solutions that are precise, trustworthy, and capable of meeting the demands of today’s data-driven world in highly regulated industries.

Fireside chat: AI Governance and Risk Management in Finance

  • Uncovering how the government’s approach to AI assurance and risk management impacts business decision and operations
  • Aligning government responsible AI initiatives and streamlining AI frameworks to enhance performance
  • Examining implementations of new risk management principles in Finance
  • Ensuring AI governance aligns with regulatory commitments

Bring AI to Your Data: An Ecosystem Approach to AI Adoption

To maximise the benefits of AI, business leaders must ensure investments are well-placed to drive value and competitive differentiation. Given its budgetary, security, and ethical implications, AI has rapidly become a board-level priority. It’s essential to reposition AI from being solely an IT responsibility to a collaborative effort across the entire organisation.

This session will explore the successful business outcomes that a unified strategy around AI adoption can deliver for organisations, particularly how to accelerate their AI journeys from proof of concept to production while also reducing risk.

Revolutionising Risk Analytics with Generative AI & Synthetic Data

• Join SAS and Nationwide Building Society in exploring transformative potential of Generative Adversarial Networks (GANs) and synthetic data in revolutionising risk analytics.
• Collaborating uses GANs to enhance personal loan model accuracy by augmenting default cases with synthetic data.
• How do these technologies boost model performance through a case study comparing outcomes with and without synthetic data; highlighting realistic improvements in risk analytics; and helping to discover the future of risk with generative AI.