Archives: Agenda

• Exploring factors affecting costs and time efficiency
• Re-evaluating strategies and tools supporting automation and GenAI to optimise performance
• Risks vs results: Can taking risks possible help to generate better results?
• How is your business saving time and boosting productivity?

In today’s competitive business environment, delivering exceptional customer experiences (CX) while reducing operational costs is paramount for organizations looking to stay ahead of the curve. This session will explore how companies can achieve this delicate balance by leveraging the power of boost.ai and large language models (LLMs), such as OpenAI’s GPT-4.

Boost.ai UK Lead, Cherie Landman, will be joined by Adam Rathbone from our Technical Pre-Sales team to discuss the transformative potential of the boost.ai conversational AI platform and demo its hybrid integration of LLMs.

• How is the Finance industry navigating AI safety regulations in their daily operations?
• Detecting how companies are managing their data and AI risks in a transforming digital ecosystem
• Unravelling challenges of data privacy and GDPR whilst using AI to leverage services to clients

• How AI is powering the future of financial services?
• Building AI-enabled applications for customer acquisition and retention
• Using AI solutions to create robust fraud detection and prevention systems
• How can the GenAI trust issue be solved?

• Automation of Routine Tasks: Accelerating claim processing and optimizes underwriting using data analysis and machine learning.
•  Improved Customer Service: Virtual assistants and chatbots provide quick responses to customer inquiries.
•  Fraud Prevention: AI detects fraud by analyzing claims data and utilizing image recognition for assessments.
•  Risk Management: AI helps insurers predict risks using data from weather and demographics.
•  Personalization: AI enables tailored insurance solutions by evaluating individual behaviors, such as dynamic premiums based on data from wearables or vehicles.

• Using AI-driven behavioural analytics to detect emerging fraud and scam techniques

• Improving customer trust whilst reducing friction through behavioural intelligence

• Proactively detecting mule accounts before the damage is done