Developing an effective London market data strategy

The imperative of data quality to improve London market underwriting

• Overcoming the data quality & accuracy challenges in the London market
• Breaking down silos so data is used consistently across the organisation – and showing its value
• Ingesting real-time data to enable effective portfolio management and automated digital transactions
• Tackling legacy technology and architecture challenges

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Data readiness for Generative AI

Overcoming the operational and cultural challenges to leverage and exploit GenAI

• Ensuring data quality, relevance and accessibility when dealing with large volumes of data
• Seamlessly integrating disparate sources of data ready for data analysis
• Devising and implementing a data governance strategy with clear roles, responsibilities and metrics
• Enriching the dataset with additional data points or features to improve model performance

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Rethinking the customer experience

Leveraging AI to enable better interactions with customers

Successfully meeting changing customer expectations, improving communications and enabling self-service

• Understanding your current customer journeys to identify friction points and frustrations
• Using AI to personalise journeys and deliver a seamless experience across different channels
• Overcoming the operational challenges to integrate AI tools with existing IT infrastructure
• Enabling an organisational culture that embraces continuous change

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CDO Hub Event

CDO simulation: Navigating leadership challenges

In this energetic, vendor-free conversation, you’ll be presented with common leadership scenarios and challenges that Chief Data Officers in insurance face and tasked with navigating them successfully. 

 In this, we'll explore delivering value, executing your data & AI strategy, stakeholder engagement and dealing with curveballs. There's not necessarily one definitive answer or approach so it's a chance to, in small groups, get the cogs whirring, crowdsource how you'd approach the problem statement and build some new ideas for your back pocket. 

This is a collaborative session, based on conversation, sharing experiences to learn from each other and meet new senior data peers. It's hosted by the founders of the CDO Hub, a community of over 300+ senior data leaders globally. The session is open to senior data leaders who own and implement the data strategy in their organisation. Strictly no vendors or consultants.

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Practical Data Mesh

Implementing federated data management in the insurance industry

Successfully meeting changing customer expectations, improving communications and enabling self-service

• What is a data mesh architecture and is it right for you?
• What are the benefits and drawbacks?
• Concrete practical advice on getting the best out of the approach?
• Advice and examples of using Microsoft Fabric to implement data mesh
• Organisational change and governance structures required for success

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Integrating and enriching 3^rd party data across the organisation   

Achieving data accuracy, quality and scalability

Overcoming the practical challenges to leverage real-time data to improve the customer experience

• Leveraging third party data to enhance personalisation, innovate insurance products, and tailor services to individual customer needs and preferences
• Ensuring continuous data quality through accuracy monitoring
• Achieving more detailed and accurate risk assessments to improve business performance
• Leveraging real-time data to enable more precise underwriting and pricing models

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Transforming operations

Delivering operational efficiencies & improving customer service through data, automation and AI

Grasping the opportunities to streamlining operations through data analytics  

• Assessing where the friction occurs in your current operating model
• Using data to optimize resource allocation, ensuring that investments in technology and processes deliver ROI
• Successfully implementing tools to understand customer behaviour and preferences to enable more personalised service
• Tackling the legacy technology challenges to enable more data driven decision making

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Enabling a data driven, London Market operating model

Embedding data and analytics at the core of all processes

• Ensuring relevant data from underwriters, brokers, and actuaries is easily accessible to all stakeholders to facilitate informed decision-making
• Promoting data literacy across the organisation to drive efficiency and improve client outcomes
• Transforming the tools and technologies to enable innovations and insights from data

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Workshop

Be the future of insurance

Uncover high-value AI use cases for your business

Guided by our expert team at Cynozure, this hands-on workshop will give you a framework to uncover and articulate your leading use cases for AI and GenAI and prioritise them based on the potential value to your specific organisation.

Walk away from the session with ideas for your next prototypes or proof of concept and strategies to secure buy-in and investment from your leadership.

Whether you’re already executing your AI strategy or just at the start of your journey, this session will give you confidence in your approach and help maximise the value AI delivers to your organisation.

The team will bring the session to life with their experience, real-world examples and use cases they expect to see insurers embracing soon.  

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Data standards & governance

Leveraging commercial value whilst achieving regulatory compliance

Devising and implementing a robust data governance strategy and culture

• Successfully establishing effective policies and standards for data management and usage with clear accountability
• Bringing disparate data from across the organisation into a holistic data governance framework
• Defining key metrics and reporting systems to mitigate AI risks
• Implementing 'awareness programs' to promote a culture of data governance

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Ensuring AI success and mitigating bias

Uncover best practice to successfully deliver change

CASE STUDY: Overcoming the operational and cultural barriers for successful AI and automation deployment

• Securing senior stakeholder buy in and effectively communicating initiatives across the organisation
• Ensuring data accuracy and consistency to provide a comprehensive and unified data set for AI models
• Overcoming legacy system and process challenges to integrate AI tools
• Tackling resistance to change and developing a culture of continuous improvement

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Enabling digital underwriting

Leveraging data and analytics in real-time to improve underwriting performance

Improving risk selection and delivering efficiencies through advanced analytics

• Understanding where the opportunities are to automate processes and enable quicker decision making
• Leveraging real-time data and machine learning models to assess risk more accurately
• Ensuring vulnerable customer are considered when implementing digital solutions
• Developing transparent and explainable AI models to build trust with customers, regulators and avoid bias

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Optimising portfolio management in the London market

Building digital competencies to enable advanced analytics tools and a data first culture

Harnessing the power of data and analytics to support more effective portfolio management in a complex and changing risk environment

• Collecting, recording and modelling data at a consistent level of detail
• Using real-time data to rapidly respond to issues in the portfolio
• Leveraging analytics to identify changes in risks and trends to take advantage of opportunities and avoid costly mistakes

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