In this episode of Insurance Unplugged, host Lisa Wardlaw speaks with Casey Kempton, President of Nationwide PNC Personal Lines, about the future of the insurance industry. They discuss the importance of revolutionizing personal lines through a focus on 'predict and prevent' strategies, enhancing consumer experience, and leveraging technology to create a seamless insurance journey. Casey shares insights from her background in anthropology and her passion for transforming the insurance experience into one that provides genuine peace of mind for consumers. In this conversation, Casey Kempton and Lisa Wardlaw explore the evolving landscape of the insurance industry, emphasizing the importance of understanding consumer perspectives, user-centered design, and the integration of predictive technologies. They discuss the need for insurance to transition from a necessity to a desired service, highlighting the role of curiosity and continuous improvement in driving innovation and enhancing customer experience.

Takeaways

Casey Kempton is the President of Nationwide PNC Personal Lines.

The insurance industry needs to focus on 'predict and prevent' strategies.

Consumers often feel disappointed with their insurance experience.

Insurance should provide peace of mind, not just be a financial contract.

Technology can enhance the consumer experience in insurance.

Preventing claims is more beneficial than just processing them.

Consumers want fewer interruptions in their lives, not fewer claims.

A singular operating system for technology in insurance is needed.

Understanding customer experiences is crucial for innovation.

The insurance industry has a responsibility to make homes and roads safer. We can imagine what everyone is experiencing, but we must check in on that.

User-centered design is critical in building effective insurance solutions.

Understanding the job customers are trying to get done is essential.

Simplicity in design helps in user adoption and satisfaction.

Insurance must adapt to changing consumer needs and preferences.

Predictive technologies can enhance customer experience and retention.

The insurance industry must focus on value beyond just pricing.

Curiosity about technology can lead to innovative solutions.

The future of insurance lies in understanding consumer wants, not just needs.

Continuous improvement is necessary to keep pace with change.

Chapters

00:00 Introduction to Casey Kempton and Nationwide

02:22 Revolutionizing Personal Lines: Predict and Prevent

07:15 Understanding Consumer Experience in Insurance

12:33 The Role of Technology in Prevention

17:03 Navigating Complexity in Insurance Technology

19:33 Understanding Consumer Perspectives

22:11 User-Centered Design in Insurance

24:03 Balancing Cost and Value in Insurance

26:50 Adapting to Changing Consumer Needs

30:26 The Role of Predictive Technologies

35:04 Curiosity and Continuous Improvement in Insurance

Summary

In this episode, Lisa Wardlaw and Dror Katzav discuss the transformative role of AI in the insurance industry, particularly in understanding policyholder behavior and enhancing agent engagement. They explore the challenges faced by agents, the importance of data in operationalizing AI, and the need for a customer-centric approach in insurance messaging. The conversation highlights the demographic shifts in the agent workforce and the potential for AI to empower both agents and policyholders in navigating the complexities of life insurance.

Takeaways

AI is revolutionizing the insurance industry by enhancing understanding of policyholder behavior.

Agents face challenges in upselling and cross-selling due to commission structures.

AI can identify which policyholders are likely to lapse or need engagement.

Demographic shifts in the agent workforce pose challenges for the industry.

Operationalizing AI can start with basic data points and lead to quick wins for agencies.

Data management is crucial for effective AI implementation in insurance.

AI can help agents craft personalized messages for their clients.

Carriers need to support agents with valuable tools, not just compliance materials.

Economic sensitivities impact policyholder behavior and insurance sales.

A customer-centric approach is essential for effective insurance messaging.

Chapters

00:00 Introduction to AI in Insurance

02:52 Understanding Policyholder Behavior

06:03 The Role of Agents in Upselling and Cross-Selling

09:06 AI's Impact on Agent Engagement

12:08 Demographics and the Future of Insurance Agents

15:00 Operationalizing AI in Agencies

17:50 Quick Wins for Agencies

21:08 The Importance of Data in AI Models

24:06 Empowering Agents with AI

26:57 Carriers and Distribution Dynamics

29:53 Navigating Economic Sensitivities in Life Insurance

33:05 Behavioral Psychology in Insurance Messaging

35:52 Call to Action for the Insurance Industry

Summary:

In this episode of Insurance Unplugged, host Lisa Wardlaw engages with Christian Toph Nielsen, SVP of Predictive Modeling and AI Strategy at Ascot Group, to explore the transformative role of AI in the insurance industry.

They discuss foundational tenets of AI, the importance of democratizing access to AI tools, and the challenges of managing unstructured data.

The conversation also delves into strategic decisions around building versus buying AI solutions, the significance of data governance, and the need for event-driven architectures. Christian emphasizes the growing AI literacy within the industry and calls for a shift in mindset regarding AI implementation.

Takeaways:

AI is not just for data scientists; it's for everyone.

Establishing a strong foundation is crucial for becoming an AI-driven company.

Data quality is essential; without data, AI cannot function.

AI literacy is increasing in the insurance industry.

Organizations must stop viewing AI as just software.

Capturing data upfront can unlock new insights.

The insurance industry is still in the early stages of AI adoption.

AI will fundamentally change pricing and risk management.

Building internal AI capabilities is necessary for effective implementation.

A collaborative approach to data governance is vital for success.

Sound Bites:

"AI isn't just for data scientists, it's for everyone."

"No data, no AI."

"You have to have your own AI muscle."

"Think of it like weaving a fine tapestry."

"Capture everything upfront if you can."

"Stop thinking about AI as a software."

"AI literacy is way up compared to when I started."

"We're still in the infancy of AI in our industry."

Keywords:

AI, insurance, data governance, unstructured data, democratization, predictive modeling, event-driven architecture, build vs buy, business strategy, AI literacy

Summary:

In this episode of Insurance Unplugged, host Lisa Wardlaw welcomes Mike Wise, founder of Rainmaker and IoT Sandbox. They discuss Mike's extensive background in technology and insurance, his journey into blockchain and IoT, and the importance of decentralized foundations in the insurance industry.

The conversation delves into the concept of post-quantum resilience, exploring how blockchain, AI, and quantum computing are converging to create a secure future for technology. They emphasize the need for innovative solutions in the face of evolving cybersecurity threats and the role of AI in enhancing data security and integrity. In this conversation, Lisa Wardlaw and Mike Wise explore the transformative impact of quantum technology, AI, and blockchain on the insurance industry.

They discuss the challenges posed by legacy systems, the innovative potential of parametric insurance, and the importance of adapting to a rapidly changing technological landscape. The dialogue emphasizes the need for continuous learning and curiosity in navigating these shifts, as well as the critical role of insurance in society's functioning.

Takeaways:

Mike Wise has a rich background in technology and insurance.

Blockchain can facilitate secure operational AI.

Decentralized foundations may be more appealing than the term blockchain.

Post-quantum resilience is crucial for future cybersecurity.

Quantum computing will revolutionize current computing standards.

Blockchain technology is evolving to become quantum resistant.

AI is becoming more accessible and integrated into everyday use.

Data architecture is essential for secure AI applications.

The convergence of AI and blockchain is a significant trend.

MIT is a hub for innovative thinking and technology development. Quantum technology is essential for future decision-making.

Legacy systems in insurance create significant challenges.

AI can accelerate coding and development processes.

Parametric insurance offers innovative solutions to traditional claims.

The herd mentality in insurance can lead to failure.

Continuous learning is crucial in adapting to new technologies.

The insurance industry must embrace change to remain relevant.

IoT devices will significantly impact the insurance landscape.

Education on new technologies is vital for executives.

Collaboration and open-mindedness are key to innovation.

Sound Bites:

"The best use of blockchain is for AI."

"I'm getting there first."

"Blockchain is a hammer looking for a nail."

"It's just architecture. Data architecture."

"We have more comfort level with AI."

"You should store them. You should secure them."

"You can't blockchain enable a Web2 process."

"AI can now do your coding a lot faster."

"The herd mentality will get you fired."

Keywords:

Insurance, Blockchain, IoT, AI, Quantum Computing, Cybersecurity, Decentralization, InsureTech, Technology, Innovation, quantum technology, insurance, parametric insurance, AI, blockchain, IoT, legacy systems, risk management, technology trends, insurance industry

Summary:

In this episode of Insurance Unplugged, host Lisa Wardlaw and guest Scott Shapiro discuss the transformative impact of AI on accounting and financial operations. They explore how AI is not merely a technological advancement but a fundamental shift in business strategy, emphasizing the importance of embedding AI into workflows to enhance productivity and achieve ROI.

The conversation also delves into the challenges of operational efficiency, the need for process transformation, and the future of process mining in the context of AI integration. In this conversation, Scott and Lisa explore the evolving landscape of AI tools, emphasizing the importance of understanding their limitations and potential. They discuss the necessity of auditing and trust in AI governance, the future of auditing with AI, and the balance between human oversight and machine efficiency.

The dialogue also touches on the challenges of real-time accounting and the psychological aspects of change management in organizations. Ultimately, they encourage industry professionals to adopt an AI-first mindset and embrace the opportunities presented by these technologies.

Takeaways:

AI is a business reckoning, not just a tech play.

The era of AI is enhancing productivity in finance.

Embedding AI into workflows is crucial for adoption.

ROI from AI is not just about cost savings.

Operational efficiency should not be the sole investment strategy.

Automating bad processes is counterproductive.

AI is integrated into new platforms and processes.

Transformation requires a coordinated approach of technology, process, and talent.

Process mining can reveal inefficiencies in workflows.

Dynamic AI interactions need to be considered in process mining. AI tools are primarily backward looking but need to evolve.

Understanding the strengths and weaknesses of AI tools is crucial.

Trust and governance are essential in AI implementation.

Real-time accounting can transform financial practices.

Change management is more about mindset than technology.

Human oversight remains critical in decision-making processes.

The future of auditing will leverage AI for efficiency.

Organizations must focus on behavioral change for successful adoption.

AI can enhance productivity but requires a shift in thinking.

Industry professionals should embrace an AI-first mindset.

Sound Bites:

"AI is in the new platforms."

"It's a backward looking tool."

"We live in this hybrid world."

"Trust is essential."

"It's hard work, Lisa."

"That's a new world."

"Lean into it, have fun with it."

"Stay curious, stay informed."

"Thank you, Lisa."

Keywords:

AI, accounting, financial operations, productivity, ROI, operational efficiency, process mining, insurance, technology transformation, business strategy, AI tools, auditing, trust, governance, real-time accounting, change management, insurance, technology, productivity, innovation

Summary

In this episode of Insurance Unplugged, host Lisa Wardlaw engages with Rohit Puranik from Tech Mahindra to explore the transformative impact of generative AI in the insurance industry. They discuss the definition and significance of generative AI, its current applications in underwriting, claims processing, and customer experience, as well as the challenges and risks associated with its implementation. The conversation emphasizes the need for insurance leaders to act quickly and strategically to leverage AI while addressing compliance and governance issues. Rohit shares insights on the future of AI in insurance, advocating for a shift from pilot projects to robust platforms that can handle the evolving demands of the industry.

Takeaways

Generative AI can create human-like text and assist in decision-making.

Insurance companies are using AI for personalized policy recommendations.

AI can significantly reduce claims processing time.

Bias in AI can lead to discriminatory practices in underwriting.

Regulatory compliance is crucial for AI adoption in insurance.

Generative AI enhances customer experience through virtual assistants.

Insurance leaders must act quickly to leverage AI technologies.

The future of insurance requires a digital-first approach.

AI can optimize underwriting and risk assessment processes.

Investment in governance and tech talent is essential for success.

Chapters

00:00 Introduction to Generative AI in Insurance

03:25 Understanding Generative AI and Its Importance

06:21 Current Applications of Generative AI in Insurance

10:04 Challenges and Risks of Implementing Generative AI

16:10 Balancing Innovation with Compliance and Governance

22:29 The Future of AI in Insurance: Infrastructure Needs

29:12 Call to Action for Insurance Leaders

Summary:

In this episode of Insurance Unplugged, host Lisa Wardlaw speaks with Heather Wilson, CEO of Clara Analytics, about the intersection of AI and the bad faith epidemic in the insurance industry. They discuss how AI can help manage claims and prevent bad faith situations, the challenges faced by adjusters in a rapidly changing landscape, and the importance of operational intelligence in claims management.

Heather shares insights on the current state of litigation, the role of AI in augmenting adjuster capabilities, and the need for carriers to adapt to the evolving environment. In this conversation, Heather Wilson and Lisa Wardlaw discuss the integration of AI into core systems, addressing the workforce crisis, and the importance of designing for defensibility and trust in claims management.

They emphasize the need for real-time data and the role of AI in enhancing decision-making processes, while also exploring future visions for AI in the insurance industry.

Takeaways:

AI can serve as a strategic tool in preventing bad faith claims.

The insurance industry is facing an epidemic of nuclear verdicts.

Adjusters are overwhelmed by the complexity of litigated claims.

Operational intelligence is essential for effective claims management.

Plaintiff law firms are leveraging AI to gain an advantage.

Insurance carriers must adapt to the changing landscape of litigation.

AI can help identify patterns in claims and litigation strategies.

The competition between AI tools is intensifying in the legal space.

Insurance started as a safety net for unforeseen events.

Carriers need to collaborate and share knowledge to combat litigation challenges. Clients want integrated solutions that combine document intelligence and workflows.

AI must be embedded in daily operations for effective use.

Real-time data is crucial for managing claims effectively.

The insurance industry has lagged in adopting real-time processes.

APIs alone are insufficient for modern challenges in claims management.

The core systems must evolve to incorporate AI capabilities.

There is a significant talent crisis in the insurance industry.

AI can help manage cognitive load for adjusters.

Explainability in AI is essential for building trust.

The future may see AI agents taking on roles traditionally held by humans.

Sound Bites:

"The competition of the bots is real."

"You have to level up in the era of AI."

"They want all of it together."

"It can't be this side process."

"The intelligence has to be served up."

"It's triaging a human as a patient."

"Real time or near real time on the cases."

"APIs are killing me."

"You have to have all that instrumentation."

Keywords:

AI, bad faith claims, insurance, operational intelligence, litigation, Clara Analytics, Heather Wilson, claims management, data analytics, insurance technology, AI integration, workforce crisis, document intelligence, claims management, insurance technology, real-time data, agentic AI, litigation strategy, explainability, trust in AI

Summary:

In this episode of Insurance Unplugged, host Lisa Wardlaw and guest Kyle Geoghan discuss the transformative potential of agentic AI in the insurance industry. They explore the differences between shallow and deep agentic AI, the challenges posed by current workflows, and the future of customer experience with AI.

The conversation emphasizes the need for a shift in thinking from traditional processes to innovative solutions that leverage AI technology effectively. In this conversation, Kyle Geoghan and Lisa Wardlaw discuss the complexities of insurance coverage, the transformative role of AI in enhancing access to insurance products, and the challenges faced in adopting new technologies. They emphasize the importance of generative AI in improving customer experience and the need for a strategic approach to integrating AI into insurance workflows.

The discussion also touches on the future of the insurance industry, highlighting the necessity for agility and innovation in response to evolving market demands.

Takeaways:

Generative AI is set to revolutionize the insurance industry.

Shallow AI can execute workflows, while deep agentic AI autonomously achieves goals.

Current insurance processes often hinder the effective use of AI.

Specific goals for AI agents increase their chances of success.

The insurance industry must rethink workflows to integrate AI effectively.

APIs are often inadequate for creating seamless customer experiences.

Dynamic forms can streamline the data collection process.

AI agents can help reduce repetitive tasks in insurance workflows.

The industry has lacked the technology to create a great customer experience until now.

Collaboration between carriers and agents is essential for leveraging AI solutions. Even medium-sized businesses should have multiple lines of coverage.

Normalization is essential for a good customer experience in insurance.

Access to information and products is crucial for insurance customers.

AI can enhance quote generation and customer interaction.

Dynamic forms and generative AI can streamline insurance processes.

Human involvement is still necessary for complex insurance queries.

Retrieval augmented generation (RAG) improves AI accuracy.

AI agents can help reduce the burden on human brokers.

Insurance companies must adapt to the rapid evolution of technology.

The future of insurance will be defined by agility and innovation.

Sound Bites:

"Shallow AI vs. Deep Agentic AI."

"We need to think from first principles."

"Provide access to insurance."

"AI agent embedded inside broker portal."

"Don't throw contracts into ChatGPT."

"Generative AI is a revolution."

"Humans are not always easy to regulate."

"Create a feedback loop for AI training."

"Be prepared for a revolution."

Keywords:

Agentic AI, Insurance, Generative AI, Digital Transformation, Customer Experience, APIs, Workflows, Technology, Innovation, Insurance Industry, insurance, AI, generative AI, technology, underwriting, customer experience, insurance agents, digital transformation, access to information, insurance industry

Summary:

In this conversation, Lisa Wardlaw and Oscar Martinez delve into the complexities of Robotic Process Automation (RPA) and its evolution into smart RPA. They discuss the limitations of traditional RPA, particularly in the insurance industry, and explore the potential of cognitive automation to enhance decision-making processes.

The dialogue emphasizes the importance of knowledge sharing and the challenges of maintaining trust in automated systems, especially as they integrate with AI. The conversation also touches on the need for robust verification methods, such as zero knowledge proofs, to ensure process integrity in an increasingly automated world.

In this conversation, Oscar Martinez and Lisa Wardlaw explore the complexities of automation, particularly in the context of AI and human judgment. They discuss the challenges of verifying AI decision-making systems, the importance of human insight in automation processes, and the future of automation as a blend of AI and human capabilities.

The dialogue emphasizes the need for businesses to rethink their approaches to automation, ensuring that they are not merely shifting burdens but genuinely enhancing efficiency and effectiveness. The conversation concludes with a cautionary note for businesses to be aware of the realities of automation solutions and to understand their own capabilities and needs.

Takeaways:

RPA has often been a temporary solution for deeper process issues.

Smart RPA needs to be defined clearly to understand its value.

Insurance has been slow to adapt due to legacy systems.

Cognitive automation could revolutionize decision-making processes.

Knowledge sharing is crucial for successful automation.

Maintaining trust in automated processes is a significant challenge.

Zero knowledge proofs can enhance process integrity.

The atomic units of processes need to be clearly defined.

Automation should evolve beyond simple task execution.

The future of automation lies in dynamic decision-making capabilities. Verifying AI systems is crucial for trust and reliability.

Human judgment remains essential in automation processes.

Automation should not shift burdens but enhance efficiency.

The future of automation lies in integrating AI with human insight.

Businesses must scrutinize their assumptions about automation.

RPA may not be the ultimate solution for all processes.

Companies should focus on automating complex, judgment-based tasks.

Transparency from vendors is vital in automation solutions.

Understanding the true value of automation is essential for businesses.

Know thyself: businesses must be honest about their capabilities.

Sound Bites:

"RPA is glue for legacy systems."

"The future is cognitive automation."

"How do you verify those decisions?"

"We need notarized proofs of processing."

"What are the atomic units of your process?"

"When does it get committed?"

"It's hard for me if I have an AI system."

"Buyer beware, right?"

"Know thyself, right?"

Keywords:

RPA, Smart RPA, Cognitive Automation, Insurance, Decision Logic, Automation Challenges, Trust in Automation, Zero Knowledge Proofs, Process Integrity, AI in Insurance, AI, automation, decision-making, human judgment, RPA, technology, business processes, verification, auditing, intelligent automation

Summary:

In this episode, Lisa Wardlaw interviews Christian Lau, co-founder and chief product officer of Dynamo AI, discussing the intersection of AI, security, and governance in the insurance industry.

They explore the challenges enterprises face in deploying generative AI, the importance of security measures, and the evolving landscape of centralized versus decentralized AI architectures. The conversation highlights the need for tailored governance frameworks and the identification of blind spots in AI security as organizations adapt to rapid technological advancements.

In this conversation, Lisa Wardlaw and Christian Lau delve into the evolving landscape of AI, focusing on decentralized computing, the implications of Agenic AI, and the pressing need for robust security governance in AI systems. They discuss the challenges organizations face in implementing AI securely and the importance of establishing clear roles and responsibilities for stakeholders involved in AI governance. The conversation culminates in actionable insights for CISOs and security leaders on how to navigate the complexities of AI security and compliance.

Takeaways:

Enterprises need to demonstrate robust technical controls for AI.

Generative AI poses unique security risks that must be managed.

CISOs face challenges in monitoring multiple AI use cases.

Centralized governance may not be feasible for all AI applications.

Decentralized approaches can empower teams to define their own rules.

Shadow AI presents risks that organizations must address.

The landscape of AI security is rapidly evolving.

Embedded AI is becoming integral to enterprise systems.

Organizations must identify and catalog all AI processes.

Future AI architectures will require hybrid models for efficiency. Decentralized AI is becoming essential for real-time processing.

Localized AI compute nodes are emerging as a solution.

Agenic AI introduces new security risks that need to be managed.

Organizations must establish clear governance structures for AI.

CISOs should engage with AI initiatives early on.

Security and compliance in AI come with significant costs.

Prompt engineering is crucial for secure AI implementations.

AI systems require continuous monitoring and governance.

The role of the CISO is evolving with AI advancements.

Dynamic security measures are necessary to keep pace with AI developments.

Sound Bites:

"What excites you the most about AI security?"

"Embedded AI is changing the landscape."

"Shadow AI is a challenge."

"Each team should define their own rules."

"Decentralization is not built for the era of AI."

"The utilization is going to go up so high."

"It's infeasible to manage everything centrally."

"How can people not see this?"

"Just do it."

Keywords:

AI, insurance, security, governance, generative AI, compliance, decentralized architecture, enterprise risk, technology, data privacy, Decentralized AI, Agenic AI, AI Security, Governance, AI Implementation, AI Risks, AI Compliance, AI Management, AI Technology, AI Future