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How Artificial Intelligence Optimizes the Workload of Your Adjusters to Handle the Most Complex Claims

Moving from spreadsheets to optimizing your adjuster ecosystem across all your options has evolved significantly lately, by combining mobile technologies with Artificial Intelligence and cloud computing. The key is to keep pace with the evolution of enabling technologies.

Before we do that, as a Claims Manager responsible for a team of adjusters, how many of the following challenges are you experiencing?

  • Your veteran staff adjusters are overwhelmed at times
  • They’re handling too many routine claims while their skills and experience are better served handling complex claims
  • You need your junior staff adjusters up to speed faster
  • You use independent adjusting firms only for catastrophe claims
  • Your managing staff and external adjuster assignment via spreadsheets
  • You have a sense that there must be a better way to match the adjuster skillset to the anticipated claim complexity automatically

Does it feel like there should be a way to automate the decision process and balancing the workload of your most scarce resource, the seasoned adjuster? These challenges can be solved by:

  • Incorporating Artificial Intelligence (AI)
  • Smart adjuster assignment
  • Enhancing relationships with trusted partners
  • Continuous learning and improvement

Incorporating Artificial Intelligence (AI)

To reshape an Insurance Company’s adjuster assignment processes, we suggest taking advantage of the insights contained in your historical claim data that Artificial Intelligence tools provide. Adjusters can use these tools to build claim complexity scoring models based on your historical claim data. These claim complexity models predict the level of expertise needed to settle new claims that also incorporate adjuster availability, skill set, location, type of claim, and more.

Smart Adjuster Assignment

A Claims Manager then uses an automatic scheduler that leverages AI to score the claim and assign the highest rated adjuster for the First Notice of Loss that just arrived. The manager will analyze, confirm, or manually refine the results provided by the automatic scheduler. The manager also uses a daily planning console that shows the status of each adjuster out in the field, along with a daily/weekly work plan that tracks the status of each open claim in the field.

Since intra-day changes to the work plan crop up often, the system would also enable real-time and intra-day rescheduling by managing any possible exception or unplanned events that occur throughout the day. If a claim takes longer than expected, the adjuster can alert this system on a mobile device to make intra-day adjustments to the schedule.

Enhancing Relationships with Trusted Partners

Many carriers routinely bring in their trusted independent adjusters for catastrophic claims. But many of your independent adjusting partners can also provide specialized expertise, availability near the claim event with high quality and timely service. They can also reduce the burden on your seasoned staff.

But you need the ability to move beyond spreadsheets and other manual systems while enabling your partners with a real-time collaboration system that provides information around availability, skillsets, locations, and productivity scores. This digital boost of resources creates smarter adjuster assignment across the entire pool of staff and independent adjusters. We refer to this approach as a hybrid adjuster model.

Think about the impact on your customer’s experience, and the reduced time for claim settlement, if you had visibility across the availability and skillsets of you your entire pool of adjusters. What If you could automatically match domain expertise to claim complexity?

  • Might this reduce the travel burden on your senior staff?
  • Could your senior adjusters devote more quality time adjusting complex claims?
  • Would they now be able to spend more time assisting, coaching, and training your junior adjusters?
  • How might this approach be operationalized across internal and external resources?

Continuous Learning and Improvement

Now that the ball is rolling in a new direction, your AI-based system is continuously scoring and re-scoring the claims assignments and outcomes to continually optimize the assignment process to provide the optimal smart adjuster assignments.

How AI Optimizes the Workload of Your Adjusters to Handle the Most Complex Claims

Getting Started

Start Small 

From our experience, companies should begin by selecting a forward-thinking team of internal staff adjusters. Then partner with an independent adjusting firm that has history providing high-quality work at fair prices. Develop a shared transformational vision and obtain some historical claims data upon which claim complexity scores can be computed along with adjuster productivity or efficiency scores. Where adjuster productivity can be a derived unit of measure that considers data points such as reserving accuracy, claim settlement time, experience level, and customer feedback for both staff and independent adjusters.

 

Integrate Smart Scheduling with your Claims FNOL Process

Once the AI model(s) are built, the data from your existing claims system is integrated into your AI-based smart adjuster assignment system. The adjuster receives an alert and the claim details on their mobile device reaches out to the claimant to schedule the first meeting to capture the claim details. The smart scheduling system should have a robust API that integrates easily into your Guidewire, Duck Creek, Majesco, Verisk, or your homegrown claims administration systems.

Pro-active and Reactive Examples

A Catastrophic Event

A hailstorm is tracking to hit specific counties within an Insurance Company’s policyholder base. The Company can run a report of all properties potentially impacted by the weather event and start assigning outbound calls with their pool of hybrid adjusters to ensure all customers receive an initial touch to confirm some damage estimates and provide advice around how best to mitigate any additional damage to the insured property.

The AI-based Smart Scheduling system assigns the right adjuster with the right licensing, skillset, and experience to perform the initial outreach across their hybrid system of junior, senior, and independent adjusters.

Customers are thrilled at the proactive approach taken by their carrier. Their confidence that their carrier has their best interest at heart strengthens. The desire to seek a public adjuster decreases since they see a line of sight to a quick settlement. The claim settles quickly, and customer satisfaction improves.

 

A Complex Claim 

A severe auto accident occurred, and it looks like it will involve physical damage, PIP, and liability coverages. The only local adjuster is junior since the senior adjuster is vacationing with their family. The claim scores as complex, and the AI-based Smart Scheduling system recommends a liability expert from the independent adjusting firm.

The liability expert receives the work order from the automated adjuster assignment system from the carrier and contacts the insured within a few hours of the claim to obtain the particulars. The insured provides the accident details to the adjuster, and the adjuster contacts the injured party to assess the extent of their injuries. The reserve is set, and the claim process is expedited efficiently by assigning the right skillset at the right time to drive the right claim settlement processes forward.

Conclusion

When you combine AI, Automation, Mobile, and Cloud Technology to empower a hybrid staffing model, you reduce the burden on your seasoned adjusters, leverage your trusted partner and bring your junior adjusters up to speed faster. The result is improved customer claim service, reduced time to settlement, reduced litigation rates, and reduced claim leakage. A winning combination for all!

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Neil Doherty
Director of Sales
Neil Doherty is a Sales Director responsible for business development in central US/Canada along with a North American focus on Telecommunications, Healthcare and Insurance. He has been in the mobile Field Service space for the last 20 years, starting his career in software engineering, and eventually moving into technical sales and direct sales.