“Beyond emerging technology, reshaping the insurance claims landscape demands a blend of "Technology + People". At Crawford, we champion this synergy, driving solutions through innovation and proficiency.”
– Sam Krishnamurthy
Unleash the power of GenAI
Generative AI (GenAI) has unlocked new opportunities to enhance workflows across the insurance value chain. Many of the benefits are already known and even in practice in some use cases. It has the potential to elevate customer experiences, refine performance in certain areas and drive operational efficiencies across the lifecycle of business.
However, companies should be cautious as they begin to integrate these new tools into their technology ecosystem. GenAI represents game-changing opportunities across industries but, like any new technology, there are pitfalls carriers need to keep in mind.
Understanding and implementing trustworthy GenAI is paramount for business optimization, improved outcomes and reputation protection. Beyond mere integration, it's essential to address concerns tied to ethics, culture, human factors and change management. Proper training and comprehensive risk assessment are crucial. To bolster trust and responsible AI deployment in business, it's imperative that technology undergoes thorough security and data privacy vetting, ensuring its ethical use and strategic incorporation for optimal results.
“At Crawford, when evaluating GenAI, we ask: How might it uplift operational, customer, and employee experiences, aligning with ethical, security, data and client consent standards? In the backdrop of varied legal landscapes, are we adhering to regional laws? Moreover, is our GenAI investment calibrated for optimal ROI, resonating with our growth goals? Collectively, these pivotal considerations steer our alignment with overarching innovation and growth strategies.”
– Sam Krishnamurthy, Vice President, Corporate Systems.
Assessing the value of GenAI Tools
Executives across industries are eager to see how GenAI tools can positively impact processes and increase efficiencies across enterprises. However, companies looking to adopt GenAI should assess their current processes first. Identifying the pain points in existing workflows can help businesses understand where technology implementation is needed and what technologies can help enhance, or in some cases remove, a problem.
Companies should consider GenAI as a tool to enhance processes, not replace them. While technology empowers the business, optimizing workflows is crucial. Existing flaws might be amplified by integrating technologies like GenAI.
”At Crawford, we take a thoughtful and strategic approach. First, we aim to understand the overarching business problem, then delve deeper to uncover its root cause. In cases of process inefficiency, our team doesn't merely automate. We collaborate with operational leaders to streamline the end-to-end process and change management is essential. This pivotal step lays the foundation for crafting a principled GenAI strategy and solution right from the start.”
– Sam Krishnamurthy, Vice President, Corporate Systems.
Once the pain points and inefficiencies have been identified, businesses can start taking steps to integrate GenAI technology. As carriers begin to implement GenAI, it will be important for them to know the potential pitfalls.
GenAI, an evolving technology, brings innovation paired with concerns. These vast large language models produce human-like content but face challenges like misinformation, malicious use, and opaque decisions. Unlike deterministic systems that predictably respond to set rules, GenAI operates probabilistically, sometimes generating 'hallucinations' or content disconnected from reality. Their immense scale also presents interpretability, bias, and control issues. Given the evolving nature of data privacy laws and the high stakes surrounding client consent, it's imperative we approach GenAI with utmost caution. A misstep here could result in significant legal and reputational repercussions.
In the realm of insurance claims adjudication, precision and trust are paramount. The introduction of GenAI into this sector brings along a suite of benefits, but not without its challenges. A core concern is AI's potential for delivering results that, while appearing structurally sound, may not always be factually accurate. It's imperative to note that while AI systems can process vast amounts of information swiftly, their outputs require rigorous validation. Companies need to consider implementing a robust AI governance framework and proceeding with utmost caution, so that they can harness AI's potential while ensuring that the trust and reliability clients expect remain uncompromised.
Implementing AI into core business functions demands rigorous testing and validation. Let's take an example of tackling bias in an image detection AI model. When AI is trained on skewed data, it can lead to biased performance, which in turn can distort applications by relying excessively on such biased sources. Companies aiming to mitigate bias in AI image detection models should diversify and balance their training data, adopt continuous monitoring and retraining practices, and actively seek diverse stakeholder input during regular audits. For effective AI integration, it's vital to test consistently, prioritize explainability and maintain robust performance to quickly address potential model or data discrepancies.
At Crawford, the Digital Desk platform manages digital claims with desk adjusters overseeing AI-directed claim triage and channel segmentations. Adjusters review AI decisions using confidence scores: high scores expedite routing claims to the right channels, while low confident triage core might prompt model retraining from adjuster feedback. This not only ensures precise and unbiased claim routing, but also builds trust to drive better outcomes.
In summary, while deterministic AI provides consistent results and probabilistic AI embraces uncertainties, neither can fully capture the complex nuances of human understanding. This highlights the importance of the "human in the loop" approach. By assessing AI's outcomes, humans bring empathy, ethics, and contextual understanding that machines may overlook. This collaboration ensures that AI technology serves as a complementary tool, fostering decisions that are balanced, fair and contextually relevant.
By understanding when and how to use GenAI effectively and responsibly, companies can enhance efficiency and effectiveness. Augmenting current processes with GenAI, carriers can uncover valuable use cases within their adjusters' toolkit. It's crucial to establish governance policies for assessment and strategy, culminating in a responsible AI framework solution.
