Arming Adjusters with Cutting Edge Artificial Intelligence and Machine Learning Tools

As artificial intelligence and machine learning (AI/ML) continues to mature in some parts of the financial services industry, (algorithmic and machine learning investing models began over two decades ago), the deployment of AI/ML into the insurance company claims ecosystem is still in the early adopter stage.

Forward thinking carrier and third party administrator claims organizations that are moving aggressively to fully embrace the benefit of AI/ML are beginning to outperform their competitors in a variety of ways. These progressive organizations:

  • Leverage the skills of senior adjusters through intelligent claims assignment (the right claim to the right adjuster at the right time)
  • Improve efficacy of adjusters by providing intelligent guidance from FNOL forward.  
  • Provide severity scoring at FNOL and update throughout the claim life cycle with each new data input improving accuracy
  • Remove clerical tasks with smart workflow tools to allow skilled adjusters to maximize meaningful client and claimant interaction for improved claim resolution.
  • Provide “explanations” of the machine guidance to quickly gain adjuster confidence and acceptance

The desire of the insurance industry to catch up with other parts of the financial services industry has fueled the evolution of data science based insurtech firms. And while some major carriers that began their AI/ML journey a decade ago were far ahead of the industry, this gap is closing. The increased velocity of carrier interest in AI/ML based solutions is also being driven by the rating authorities, who have made “innovation” a criteria of evaluation.

Innovation in claims organizations has mostly focused on work flow, data analytics, and compliance over the last two decades with varying degrees of success. All of these efforts have been aimed at making the claims organization more efficient. Standard workflow solutions and modern claims management systems have been primary areas of investment and the foundation of the digital transformation taking place within insurance carriers. Today, cutting edge artificial intelligence and machine learning solutions from a wide array of insurtech companies aim to better leverage this data to drive profitability, starting in the largest cost center – the claims organization. 

Maximizing adjuster performance must now evolve to provide real-time, intelligent claim guidance, informed by the historical structured and unstructured data contained in legacy claims systems and adjuster notes.  Utilizing cutting edge artificial intelligence and machine learning techniques will allow modern claims organizations to extract and digest millions of data points to predict claim trajectory from first notice of loss to settlement. The earlier the potential severity of a claim is identified, the quicker it can be assigned to the adjuster that has a specific skill set to mitigate the cost of a claim. The ability to leverage the institutional knowledge of the carrier to augment individual decision making will lead to more consistent, optimal outcomes.

However, in order to achieve these types of results, one must invest in the behavioral change management to drive the most ROI from the models itself. Two major considerations when claims organizations are evaluating potential solutions from the insurtech world (or developed internally) are “how does this fit into my current workflows?” and “how do I ensure my team is using the data to make decisions?”. First, rather than piecemeal solutions, carriers are best off looking for expertise in data science that is complemented by productized solutions and easy to use dashboards or applications. The second critical consideration in an Artificial Intelligence enabled world will be the concept of explainability. In order to gain rapid and broad adoption from adjusters and managers, data science solutions must provide an explanation of why it is giving this particular guidance to the adjuster and manager. Asking skilled adjusters and managers to blindly follow a machine’s guidance without satisfactory data based explanations, will fail quickly. And the AI/ML must deliver the guidance and explanations in plain language. 

Artificial Intelligence and Machine Learning solutions applied in the property/casualty, health, and benefits insurance industry will be essential to every organizations’ overall underwriting and claims management success both in the short and long term. Early adoption of solutions which provide data driven guidance to claims adjusters will allow for quicker and more accurate decision making, a reduction in litigation, an early warning system for severe claims from FNOL and throughout the life cycle of a claim, and ultimately a sustainable reduction loss ratio across all lines of business.

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