Here's how you can prepare for the impact of artificial intelligence as an insurance underwriter.

Als Versicherungsmakler ist es entscheidend, sich auf die Auswirkungen künstlicher Intelligenz (KI) vorzubereiten. KI revolutioniert die Branche durch Automatisierung und verbesserte Kundenerfahrungen. Nutzen Sie KI-basierte Tools, um Kundenbedürfnisse besser zu verstehen und maßgeschneiderte Angebote zu erstellen. Investieren Sie in Schulungen, um Ihre Fähigkeiten im Umgang mit KI zu verbessern. Integrieren Sie Chatbots und virtuelle Assistenten, um Routineaufgaben zu übernehmen und mehr Zeit für persönliche Kundenberatung zu haben. Ich nutze gerne KI, um effizienter zu arbeiten und meinen Kunden besseren Service zu bieten. Bereiten Sie sich auf diese Veränderungen vor, um erfolgreich zu sein.

AI is not going to replace your work, rather it is going to assist you + make you 10x more efficient. Insurance has traditionally been a boring, slow industry with brain-drain. Embrace AI, be the innovator in your firm and think of ways AI can help bring more operational efficiency

Preparing for the impact of intelligence on insurance underwriting should involve more than acquiring technical skills; it also entails dedication to ongoing education. With AI, tasks can be made simpler while enhancing risk assessment precision and data analysis may provide insights that revolutionize the underwriting process. However, human judgment and expertise is still priceless. Thus, apart from using the AI tools, underwriters should concentrate on sharpening their skills and thinking critically. This can be achieved through use of technology in order to gain specialized knowledge, among other measures like improving communication capabilities.

Embracing AI in the insurance sector is crucial. Besides handling routine tasks, AI can significantly improve underwriting by providing more accurate risk assessments and predictive analytics. This allows underwriters to make better-informed decisions, identify potential issues earlier, and tailor policies more precisely to clients' needs, ultimately enhancing the overall underwriting process and thereby reducing the time taken to underwrite large and complex policies.

Two important steps underwriters can take include: - Familiarity with AI Tools and Technologies This involves understanding machine learning models like decision trees, neural networks, and Natural Language Processing (NLP), and using platforms such as SAS, IBM SPSS Modeler, RapidMiner, and AI tools from firms like AWS and Azure for predictive analytics and data-driven insights. - Develop Soft Skills for AI Collaboration This involves refining communication skills to convey AI insights clearly using tools like Tableau or Power BI, and fostering collaboration with data scientists and IT professionals to optimize underwriting workflows with tools such as UiPath and Microsoft Teams.

Take courses that talk about how your role interacts with AI and other Emerging Technologies so that you can understand it properly and exactly how you should engage with it, this will also aid in your upskilling so that you can grow with your role and not get phased out.

For underwriters, the rise of artificial intelligence presents an opportunity, not a threat. And this is the mindset that we need to embrace. Position AI as a partner that can significantly enhance your capabilities. AI excels in handling vast amounts of data and performing routine tasks quickly and accurately. This can free up our underwriters to apply their expertise where it matters most—complex risk assessments and client interactions. Write a list of all of the repetitive tasks you currently perform. Assess how many could be supported by AI and the time it could free up. Now, create a list of tasks you enjoy or want to do more. This is where AI can enhance the underwriter, not replace them.

I've been working with insurance brokers on automating their workflows. AI is a partner in true sense. It needs to be told what to do, it needs to be monitored and evaluated. I often tell brokers to think of AI as their most productive employee, but 10x faster, works 24/7 and can easily be cloned when demand increases.

What makes AI fascinating is how its applications can be seen across a spectrum of industries, solving a myriad of challenges. In the retail sector, AI helps stores optimize stock levels and personalize shopping experiences. In the finance sector, AI aids in algorithmic trading, where it can analyze large volumes of data to execute trades at the best possible prices. As underwriters, we should reflect on our own challenges. How might AI improve our risk assessments, expedite turnaround times, or better our interactions with customers? #InsurTech #Insurance #AI #RiskManagement #DigitalTransformation

The best way to learn is to get hands-on experience. A lot of software allows you to buy a license for a short period. Create an anonymized dataset and just try to use the tool. You don't have to start with a vast database. You can create a medium-sized database and see the outputs. Anonymization is the critical part of not exposing sensitive data until the proper agreements are in place.

Underwriters should start to think about what data they are collecting and from which sources. Consider how this data is being stored and how this data could be surfaced for use by a model to provide recommended actions. They should think about how a model/agent will write data autonomously based on actions taken and the controls that would need to be in place to facilitate this. The underwriter operating system is about to become a lot more efficient.

I would draw parallels with the fintech world. I've worked in the world of transactional risk and the foundational feature of AI in decision making is - traceability. Is there a deterministic way to understanding a decision has been made? And if yes, is it unbiased? Regulators need to be on top of this and work together with researchers in creating a safe ecosystem.

While it is important to pay attention to trends, this space is moving so fast that no-one can do it effectively and certainly as an individual you should not try. Rather ensure that there are people in your organisation who are and ensure there is a mechanism in place that lets them feedback to the right groups at the right time with the right level of detail. Good luck!!

É realmente relevante se manter atualizado sobre o Mercado de Seguros, independentemente da área que você atua nele. Open Insurance, Inteligência Artificial e outras novas práticas, devem estar no radar de um profissional que quer estar atento, bem informado e buscando atualização contínua. Gosto de seguir o assunto com pesquisas automáticas em fontes relavantes, antes usava RSS e hoje uso Google Alerta com palavras chave. Além de estar em Grupos de debate do Linkedin e seguir instituições importantes que trazem inovações. Abraços!

AI in insurance isn't just about efficiency—it also opens up new opportunities for innovation. For example, AI can analyze vast amounts of data to uncover emerging risks and trends that were previously invisible. This can lead to the development of new insurance products that better meet the evolving needs of customers. AI can help launch a product much faster by providing detailed insights and feedback on the apects like underwriting, rating and easy integrations.