Why Underwriters Matter in Our AI-Driven World

Dani Katz, Co-founder and Director of Optalitix, explores the evolving role of underwriters as AI innovation transforms legacy processes and roles across the insurance industry

The London insurance market has thrived on three things, since the 1600s, information or in today’s parlance, data, face-to-face meetings, and coffee. We won’t mention alcohol as it does not go down well at Lloyd’s these days, but talking over a cuppa has until recently remained as important as ever.

Pre-pandemic, brokers and insurance underwriters would meet in Lloyd’s and the thriving global insurance market around it to negotiate and thrash out deals on risks as diverse as shipping, airlines, major property and cyber risks.

It all changed in 2020, when Covid put a stop to these in-person meetings. Subsequently, there has been a slow move back to where we were, but in truth it’s not the same, and many brokers, social beasts by nature, complain about not being able to meet in person with underwriters.

This situation has been exacerbated by the rise of algorithmic underwriting, the rise of the power of actuaries in the world of insurance pricing, and complex data-driven pricing models.

Insurance pricing transformation

In the insurance industry, pricing transformation involves the complex task of creating pricing and underwriting processes that are competitive and profitable, yet digitised, scalable, and future-proof. This requires analysing existing underwriting workflows, understanding pricing models, modern pricing techniques, predicting future trends, and complying with regulatory requirements.

In today’s increasingly AI-driven world, insurance underwriters now have a host of new tools at their disposal that can optimise these processes for speed and efficiency – sometimes achieving a three- to fourfold improvement. Whilst at the same time, according to Accenture, 40% of underwriters’ time is spent on non-core and admin tasks, creating between $17-32bn of annual underwriting efficiency losses.

The good news is that, according to PWC, 50% of insurers want to digitise their pricing spreadsheets, however, this requires a strategic approach to technology implementation, which works in tandem with human expertise.

An integrated yet discrete role for AI

In our view, the future of insurance underwriting lies in the seamless integration of technology and human discretion. An ideal scenario involves submissions being ingested by a submission tool, processed through a pricing engine, and presented to the underwriter with all relevant checks and side ratings completed. This allows insurance underwriters to apply their expertise and discretion to assess risks that models may not fully capture.

Nevertheless, transparency and understanding in the modelling process are vital. For underwriters to make informed decisions, they need access to and understanding of the models used in the rating process. Unfortunately, some recent modelling engines have turned into ‘black boxes’, offering no insight into their workings. This lack of transparency can lead to underwriters maintaining their own rating models, which can create governance challenges and negative long-term consequences.

The role of people in decision-making

No matter how intelligent the technology becomes, human expertise remains a crucial part of the insurance underwriting and pricing process. At the core of all written risks is the underwriter; imposing large-scale changes without considering existing workflows can cause significant internal disruptions and even existential crises.

Why is this? Both actuaries and underwriters possess irreplaceable domain knowledge and experience that algorithms simply cannot replicate, and are essential for contextualising data and making informed decisions. For example, people will always be needed for:

• Ethical considerations: Human judgment is necessary to ensure that pricing strategies are fair and ethical, considering factors that may not be captured by data alone.
• Collaboration: Effective pricing transformation requires input from various departments, including risk management, finance, and sales. Collaboration ensures that all perspectives are considered.
• Change management: Implementing new pricing strategies often involves significant organisational change. Leaders must guide their teams through this transition, ensuring buy-in and adoption of new practices.

We recommend a co-pilot approach

This is why we believe the ideal solution is one where technology and people work hand in hand – an approach known as ‘co-pilot decision-making’. In pricing transformation, this involves using advanced tools to augment human decision-making rather than replace it, such as:

• Decision support systems: These systems use data analytics and AI to provide recommendations, which are then evaluated and adjusted by human experts.
• Interactive dashboards: Business intelligence tools offer interactive dashboards that allow users to explore data, test scenarios, and visualise potential outcomes.
• Continuous learning: As professionals use these tools, they provide feedback that can be used to refine algorithms and improve the system’s accuracy over time.

Of course, as part of this it is important to implement systems that underwriting or pricing teams will understand. Remember that people always come first and the pricing programming language should be designed to fit with their methods of operation, such as:

• Integrated pricing platforms: Specialised pricing platforms offer end-to-end solutions for pricing transformation. These platforms integrate data from multiple sources, apply advanced analytics, and provide user-friendly interfaces for business users

• Advanced analytics and AI: Leveraging advanced analytics and artificial intelligence can enhance the accuracy and effectiveness of pricing strategies. Machine learning algorithms can identify patterns, predict market trends, and suggest optimal pricing models.

• Business Intelligence tools: Tools like Tableau and Power BI provide robust data visualisation capabilities, enabling stakeholders to gain insights from data quickly and make informed decisions.

• Collaboration and Workflow Management: Effective pricing transformation requires collaboration across departments. Workflow management tools ensure that all stakeholders are aligned and can contribute to the decision-making process seamlessly.

The path to success

While the AI revolution presents immense opportunities for the insurance industry, the key to success lies in empowering underwriters, maintaining transparency and flexibility, and keeping people at the heart of the decision-making process.

To quote Lloyd’s Chairman, John Neal, from our recent event at the Lloyd’s Library, “The ‘secret sauce’ behind Lloyd’s incredible success, is the importance of doing business face to face.”

Further, as Edward Lloyd would attest, it’s vital to move with the times, but it’s also important to understand the power of human relationships in business. It’s not always about the hard numbers. Sometimes, it’s important to remember the softer factors like long-term client relationships and loyalty to an underwriter when thrashing out a deal. AI is good, but it will be a while until it works that out.

I believe co-pilot decision-making, where technology augments human expertise, is the key to successful pricing transformation. By leveraging the strengths of both technology and human insight, organisations can develop robust and effective pricing strategies that boost the bottom-line.

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