The volume of claims processed every day and the amount of data attributed to those claims is growing. But what we’re doing with data within the claims management space is constantly changing. And while risk factors must be considered, we’ve only begun to tap into opportunities for the future. Data, combined with artificial intelligence, can be used to reduce claims costs and processing times, and to facilitate adjusters, clinicians, and customers with a more intelligent way of making claims handling decisions.
My role as chief data officer has given me unique insight into the possibilities for data in our industry. I came into this role in 2021 and in just the 1.5 years since I joined Sedgwick, so many things have changed for our data science team. We’ve strategically invested in expanding this team, as well as breaking down silos for analysts to more effectively collaborate across our organization in support of decision optimization for our business units. We are focused on training, educating, and upskilling the data analyst population. And to make it all possible, we’ve integrated new AI-focused platforms and tools to allow both highly technical users as well as business users who hold valuable contextual knowledge to collaborate in new ways.
But why such an investment and focus? It comes down to two things in my mind: efficiency, sure, but also opportunity. At Sedgwick, we like to say that taking care of people is at the heart of everything we do, and that’s true even when we think about why we take on new initiatives in technology.
Efficiency is essential to evolving the claims process – and the way we care for people
Claims management has always been a data-driven endeavor to some extent. The future is about helping our large population of examiners/adjusters/clinicians save more time on the highly repetative tasks so they can spend even more time thinking about and strategizing on the more complex aspects of claims adjudication such as reserving/settlement actions. Simplifying the claims process helps us care for clients and the people they support – from employees to policyholders to customers. It’s critical for user experience, quality of outcomes, and speed of resolution. The goal is to improve outcomes by reducing claim costs or processing times, and we take on projects that we believe will be the most impactful.
How data science and AI are making a difference:
- Easy access: By linking our team and our data through a new platform that is both robust and user-friendly for a large portion of our population, analysts and data scientists can easily access data elements that were very hard to get to before. Generalized data for the popular elements needed to analyze and model claim outcomes now easily flows into the system, and models that are found to be useful can be replicated easily to benefit additional clients almost instantly.
- Let’s connect: With new supporting tools and more robust reporting capabilities, we’re now better able to work together across our IT organization and better collaborate with the business. Our decision optimization team and analysts and stakeholders within our business units are, together, finding opportunities where they can capitalize on areas of efficiency within current systems or extract valuable insights from data to improve the process.
- Sharing is the standard: By linking people, technology and data in new ways, our data science team can now rapidly develop, share and deploy scorecards, benchmarking tools and models to capitalize on benefits and value across clients. With the tools for progress all in their hands, replication of projects is now easy. If we build a customer model that’s successful for one of our clients, we can simply copy the model, change the client, and then fine tune it to the client’s unique use case and historic data. We have achieved a new level of global collaboration which goes above and beyond the technology.
Industry-wide impact and opportunities for transformation
We have the responsibility to reduce risk and to prepare and protect our clients using data science. A common challenge for corporations and carriers is finding an attorney or firm they can trust to improve claim outcomes. They’re also seeking to protect themselves against financial and reputational risks, specific challenges such as fraud and nuclear verdicts. We believe comparable performance metrics should be used to address these concerns. In the same way that provider benchmarking relies on data to predict which providers will bring the best outcomes to a claim, we believe an attorney scorecard based on the history of claims and court case outcomes can provide a similar benefit.
When it comes to systemizing the use of data and AI, and giving more roles and profiles a seat at the table, there is indeed an opportunity for new and existing models to be woven into the entire claims handling process. Everyone involved such as claims examiners, client service directors, and managers would use the data and insights provided to augment their decision-making capabilities.
One opportunity would be to apply a global score to all claims. This way, those working at the claim level might be able to use these scores to prioritize and compare claims universally, offering a rating system to the industry as a benchmarking standard. Today, this only exists in the form of time ranges for things like return to work guidelines or severity indices. Having scores or models applied to multiple areas of the claim can certainly help to streamline the workflows, but it’s not until AI or machine learning itself is performing those examiner tasks that the team will have achieved AI at scale.
For us, success when it comes to data and AI is having a process that delivers a usable product from start to finish and is fully integrated into Sedgwick’s systems while requiring minimal maintenance or manual intervention. Thanks to the caliber of our global data teams, the tools we’re putting in place and the power of our data, our organization is poised to uncover unique opportunities that might not be possible anywhere else. We can leverage our data to not only improve our own claims management process, but also develop new methods or insights that bring value to the entire industry.