An Interactive 5-Day Training Course
Artificial Intelligence (AI) in Insurance
Transforming Insurance Automation and Innovation
Course Overview
The Artificial Intelligence (AI) in Insurance training course delves into how AI is fundamentally reshaping the insurance landscape, from underwriting and risk assessment to customer engagement and fraud detection. As the insurance sector becomes increasingly data-driven, this training course equips professionals with the strategic foresight and technical understanding required to stay ahead in a digitally transforming environment. Participants will explore the integration of AI technologies into insurance operations, emphasizing data analytics, embedded insurance models, and intelligent automation.
Key themes include the impact of AI on actuarial practices, legal and regulatory compliance, and the broader ESG framework. Participants will gain a comprehensive view of how AI supports sustainability, inclusion, and innovation within the insurance industry. Through in-depth case studies, industry insights, and scenario-based exercises, professionals will examine real-world AI applications such as algorithmic fraud detection, personalized pricing, and ecosystem-based service delivery. This training course is tailored for insurance leaders aiming to leverage AI for strategic growth, operational excellence, and future-ready capabilities.
Key Highlights of the Artificial Intelligence (AI) in Insurance training course:
- Comprehensive insights into AI’s transformative role across the insurance lifecycle
- Enhancing underwriting precision and risk modeling through AI-driven analytics
- Exploring digital distribution channels and embedded insurance offerings
- Utilizing AI to combat fraud and improve claims efficiency
- Addressing regulatory, actuarial, and ESG dimensions of AI integration
- Reviewing practical case studies on ecosystem collaboration and data governance
Training Outline
DAY 1: AI Foundations & Risk Transformation
- Introduction to AI in Insurance
- How digital transformation alters traditional risk models
- Regulatory compliance for AI models, and consumer protection
- Incorporating AI-generated data into pricing models and actuarial projections
- Impact of GDPR and ethical use of customer data in insurance AI models
- AI as a tool for environmental risk modeling and supporting social inclusion
DAY 2: AI in Underwriting & Risk Selection
- Automated Risk Assessment
- Use of lifestyle, wearable, and telematics data in personalizing premiums
- Role of AI in redefining assumptions and claim probabilities
- Legal risks and ethical issues in AI-based decision-making
- Supervisory expectations around algorithmic underwriting
- Embedding ESG metrics in underwriting through AI
DAY 3: AI-Driven Claims Management & Fraud Detection
- Early warning systems and severity prediction using AI
- Fraud Detection Tool, and link analysis for uncovering suspicious claims
- Improved claims forecasting, reserving accuracy, and trend identification
- Challenges in using AI for claims denials or disputes; importance of transparency
- Customer-Centric Claims Automation
- AI in managing climate claims, promoting fairness and identifying ESG-related losses
DAY 4: New Products, Services & Ecosystems
- AI Product Innovation: Parametric and micro insurance, usage-based models
- Embedded Insurance: Integration with retail, travel, fintech, and health platforms
- Smart Services: Maintenance, health coaching, smart home support by AI
- Leveraging real-time data to build continuously priced, adaptive products
- Cross-border data-sharing and licensing concerns for ecosystem players
- ESG-Driven Innovation: energy efficiency, climate resilience, underserved populations
DAY 5: Distribution, Safety & the Future of Insurance
- Next-Gen Distribution: chatbots, robo-advisors, and recommendation engines
- Data-driven tailoring of offers and proactive risk alerts
- AI’s impact on underwriting and claims roles; upskilling for the future.
- Fair marketing practices, informed consent, and AI accountability in digital sales
- Using AI data to refine distribution channel efficiency and customer lifetime value
- Expanding access to underserved markets through AI-enhanced digital channels
Certificates
- On successful completion of this training course, GLOMACS Certificate will be awarded to the delegates
- Continuing Professional Education credits (CPE) : In accordance with the standards of the National Registry of CPE Sponsor, one CPE credit is granted per 50 minutes of attendance
Accreditation
GLOMACS is registered with NASBA as a sponsor of Continuing Professional Education (CPE) on the National Registry of CPE Sponsors. NASBA have final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.learningmarket.org.
All Training Seminars delivered by GLOMACS by default are eligible for CPE Credit.
Providers and Associations
About Saudi Glomacs
At Saudi GLOMACS, we specialize in delivering world-class training courses in Saudi Arabia and across various international locations. Our training courses are tailored to meet the unique demands of Saudi Vision 2030 and the Human Capability Development Program, focusing on empowering Saudi citizens and enhancing workforce skills. We offer diverse courses spanning leadership, management, engineering, and technical disciplines to cultivate expertise and drive professional growth. Our flexible learning options—whether in-person, online, or in-house—ensure accessibility and convenience for individuals and organizations alike.
With over 30+ years of experience through the GLOMACS global network, we are committed to delivering innovative, results-driven training solutions. Our expert instructors combine industry knowledge with dynamic teaching methods, fostering practical skill development and long-term career success. By choosing Saudi GLOMACS, you're investing in personal excellence and contributing to the Kingdom’s sustainable economic growth and vision-driven transformation.
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