Paul Carroll
We all hear agents and brokers complain about having to deal with compliance issues, but we also know how important compliance is. To start us off, how would you describe the main pain points for agents and brokers?
Jenn Knight
Compliance is essential, but complying can be quite difficult – largely because many processes remain manual, navigating regulatory nuances state-by-state is challenging, and engaging with carriers post-application can be a slow, black-box process. As a result, agents and brokers are often waiting weeks, or months, to get access to the products that best serve their client base – which hurts their clients and their book of business.
When the compliance workflow is streamlined, agents and brokers can focus on what they do best - supporting their clients in getting new policies, working through claims, or adjusting their coverage to better suit their needs. When it’s not, agents and brokers lose time with their clients to focus on the paper chase.
As you noted, compliance is critically important for the industry, and the ultimate question comes down to how to most efficiently manage that workload relative to client-supporting work.
Paul Carroll
How do recent developments in generative AI help address those pain points?
Jenn Knight
In my view, it remains to be seen exactly where generative AI will assist in compliance pain points specifically. Insurance regulation is complex, and specialized training will be needed for any models introduced in this space.
Overall, we do see an opportunity for generative AI to assist in areas that currently take a large lift in data review and analysis, particularly around many data elements that go into the regulatory profile for a producer.
Generative AI was made to take complex, disparate pieces of data and use pattern recognition to develop better, more efficient ways to sort and manage it, as well as surface insights and learnings to help inform decision-making. We believe leveraging generative AI as a part of the onboarding review process can lead to efficiencies for the administrative teams ultimately responsible for compliance checks.
The administrator will still play the decision-making role, but when fed high-quality data, the AI can create great efficiencies for that individual. This will ultimately result in data-driven decisions happening more quickly, which results in faster onboarding and response times for the agents and brokers.
Paul Carroll
Are there other technological improvements that are also helping?
Jenn Knight
There are many building blocks that are required before the introduction of generative AI, primarily focused on high-quality capture of operational data. For any company evaluating the best tools to implement, they need to start by looking at the intersection of internal knowledge and contextualized data in the organization. In addition, any solution used for compliance, onboarding, or other distribution management will require some degree of maintenance as rules and regulations are constantly changing.
To unlock future efficiencies, it’s important to have a technology stack that creates a virtuous cycle of quality-data-in and quality-data-out. This can start with more basic features such as ensuring data is validated at capture and stored in a centralized database for further analysis. More complex features involve codifying business rules in a machine-readable format to move compliance knowledge from an individual into an accessible system. Investing in technology solutions with these building blocks allows for immediate efficiencies in today’s workflows and creates the baseline for future workflows supported by generative AI.
Paul Carroll
We hear a lot about AI’s “hallucinations,” which could be a disaster in a compliance setting. How do you prevent them?
Jenn Knight
Ultimately this comes down to AI best practices - training models on a controlled and validated set of compliance data and conducting rigorous quality assurance with compliance experts to flag inaccuracies.
With data, it’s “garbage in, garbage out,” and this can be amplified with AI models. The data needs to be accurate, updated, and well-organized for AI to deliver on its promise. If that is not the case, and the data isn’t high-quality, hallucinations and biases can result, alongside other inaccuracies. It’s one of the reasons we are so focused on getting the best data, especially in the area of compliance, ensuring it can be captured across the value chain so all stakeholders are able to reap the benefits of AI technology.
Paul Carroll
If you project out two, three, or five years, what is your vision for how compliance will be handled in an agency or brokerage?
Jenn Knight
As I look ahead to the coming years, I am excited about a future where compliance workflows at an agency or brokerage transform from a manual, siloed process to a data-driven, integrated workflow that can drive additional value to the agency and agent beyond the baseline of meeting the obligation to sell products. Compliance data is rich and informative, but it is currently locked in spreadsheets, PDFs, and people’s minds. Moving that data into structured forms will allow us to unlock insights for the agency and agent on where to best spend their time and can move us away from the paper chase and to a model where the more an agent participates, the more value they receive from the process.
Paul Carroll
Any concluding thoughts?
Jenn Knight
When we started AgentSync almost six years ago, it was with a simple premise — the industry needed better infrastructure to align all the disparate points of the value chain to more effectively and accurately share information. After all, insights are only as good as the data going in. This is especially true when it comes to compliance.
We keep data up to date with a two-way daily synchronization to the industry source of truth and can integrate that data through the system – surfacing licensing and appointment data in commission payment systems, background checks, agent management, and other areas. There is increased visibility with smart automation integrations that can stop compliance violations before they happen – which also makes for better distribution relationships.
As technology advances, we believe it will represent meaningful opportunities for progress. I’m reminded of a customer who told us, “We were self-reporting licenses to all 50 states, which took six weeks to do manually through the NIPR website, one agent at a time…. That same thing would have taken less than a week to do with AgentSync.”
Many of the challenges still stem from poor infrastructure, which is what we’re solving — capturing data effectively and using it to build efficiencies that improve workflows.
Paul Carroll
Thanks, Jenn.
Turbocharging the Modern Insurance Agency
About Jenn Knight
 | Jenn Knight is Chief Technology Officer and co-founder of AgentSync, where she leads the product and engineering teams as they develop a frictionless, modern solution to some of the biggest pain points associated with producer management – broker onboarding, contracting, and compliance management. Jenn and her co-founder and husband, Niji Sabharwal, believe that using technology to solve back-office bottlenecks will empower scaled innovation across the massive, fragmented insurance industry. As one of the industry’s leading Salesforce developers, Jenn has helped solve back-office problems for leading technology companies including LinkedIn, Stripe, and Dropbox. |
