Genai took the world by storm. You cannot attend an industry meeting, participate in an industry meeting, or plan your future without Genai taking part in the discussion. As an industry, we are almost constantly debating disruptions, evolving market factors (often consumer expectations, capital market impacts, ongoing M&A impacts, etc.), and are the most optimal way to solve them. This includes using modern assets/tools/abilities with promises such as more growth, increased margins, increased efficiency, and increased employee satisfaction. However, the success of these solutions has achieved success in generating massive changes in revenue generating revenue in the industry.
The technology was primarily developed to promote efficiency and, if properly adopted, had a pocket of achievement. However, individuals who need to use technology or enter data that enhances insights to drive efficiency often benefit little or none from the solution. At its core, Genai could be the first technology widely adopted by its revenue-generating role, as it can increase insights accessibility and provide actionable insights into organic growth opportunities with clients and careers. Without a doubt, the first of that kind gives them insight to act rather than more data, into the revenue-generating role within the value chain of insurance, “What’s in it for me?”
There are five important use cases that appear to explain the promises of the broker and agent genai.
- Viable “clients like you” analysis: Securities companies that have grown primarily through the fusion of acquisitions often find it difficult to identify similar client portfolios that can provide cross-sell and upsell opportunities to acquired institutions. Genai allows you to compare the business books of acquisition institutions, such as geography, acquisitions, and more. Identify clients who have similar profiles but have different insurance solutions, open up important insights for producers to revisit clients’ insurance programs, and open up greater opportunities for organic growth that drive insights about where they will act.
- Submission Preparation and Client Portfolio QA: For brokers and agents who do not have national practice groups or specialized industry teams, insurance within industries outside of the core strike zone often presents the challenge in terms of understanding exposure and asking appropriate questions to respond to. The effort required to identify appropriate coverage and prepare submissions can be dramatically reduced by genai. Specifically, the technology helps to encourage brokers/agents about the types of questions to ask based on what is available in the 3 compared to the risk profiles of the insured, the industry operated by the insured, and the company of the insured.rd Party data source. Additionally, genai can act as a “spot check” to identify overlooked upsell or cross-sell opportunities and support E&O mitigation. Historically, the quality of portfolio coverage and subsequent submissions will be at the discretion of the producers and account teams processing the account. With Genai, you can ask years of knowledge and experience with the right questions at the fingertips of brokers and agents that act as QA and cross-selling and upselling tools.
- Intelligent placement: The decision of risk placement for each client is driven primarily by account managers and producers based on the level of their relationship with the carrier/underwriter, with known or perceived appetites of carriers for a client’s specific risk portfolio. Despite extensive knowledge gained over years of experience, almost constant changes in client risk profiles make it difficult to optimally place an agency or broker due to changes in career risk appetite. With Genai’s support, agents and brokers can generate submission summary, including the carrier’s stated appetite, client risk and policy recommendations, and financial contractual details of the agent or broker. This will provide placement recommendations that will benefit clients and agents or brokers, while reducing the time spent on marketing in terms of finding the best market and avoiding markets where risk is unacceptable.
- Revenue loss avoidance: When a client chooses an advisory fee over a fee, fees that are not specific to the holder, but arising from certain risk management measures offered by the agent or broker are often charged “under.” Genai as a competence can in theory establish a summary that can be provided with tools like ingesting client contracts, assessing internal fee-based service contracts, and internal knowledge exchange for employees who serve their accounts. This knowledge management solution can provide specific guidance to employees at the time required for fees to be charged under contractual obligations, providing revenue growth opportunities for institutions and brokers with unknown, uncollected, collected payments.
- Speed client-specific marketing materials: Historically, if an agent or broker wants to expand its non-core capabilities (e.g. digital marketing), they will hire or rent the appropriate expertise and the ability to benefit from the right efforts. While this was working, it led to an expansion of SG&A that was not firmly linked to growth. Genai Type Solutions solves this in that it allows agents or brokers to provide scalable access to non-core features (such as digital marketing) for just a few investments and costs, and potentially superior results. For example, Genai output can be customized at a rapid pace to enable agents and brokers to generate industry-specific material for mid-market clients (for example, covering X% and Z% of peers).
The use cases we derive from are in the prototyping phase, but it depicts what the near future looks like, like humans and machines meet for revenue-generating activities. There are three important actions that encourage all broker/agent clients to do next when evaluating their use of this technology in their own workflow:
- Focus on a subset of data. To leverage Genai, some data needs to be extremely reliable to generate usable insights. A common misconception is that in order to use Genai, it must be data from all agents or brokers, but the reality is small and it is implemented and unfolded. Identify the data elements that are most important to the insights you need, establish data governance and cleanup strategies, and improve that dataset before expanding. In doing so, datasets that work with private computing models to deliver value to the enterprise before expanding data hygiene efforts.
- Prioritize pilot use cases: Like many new technologies, the values provided through use cases are being tested. Brokers and agents assess what potential high-value use cases are, create pilots, test the value of these areas with a feedback loop between the development team and the revenue-generating team, and make the necessary adjustments and changes.
- We evaluate governance and recruitment methods: As we discussed, insurance as an industry is slow to adopt new technology, and therefore brokers and agents should be prepared to invest in the change management and recruitment strategies needed to show that this technology is the first of its kind to have a significant impact on revenue and organic growth in a positive way for the revenue generating team.
While this blog post is intended to be an exhaustive view of how Genai affects distribution, there are more ideas and ideas on this issue, including the impact of underwriting and claims for both carriers and MGAs. Please reach out Heather Sullivan or Bob Besio If you want to discuss more.
Get the latest insurance industry insights, news and research straight to your inbox.
