AI: Reducing Errors, Delighting Customers

Delivering exceptional customer experience requires near-real-time service when a customer has a new claim. In a market that has the highest customer acquisition costs, it’s paramount for property and casualty insurers to keep the customers they have by making their experience as positive as possible. One key is to reduce human error in claims handling, because a whopping 91% of dissatisfied customers decide to move on instead of making their complaints known. It is also important to remember that, while speed is great, the response has to be right for that type of claim. AI can reduce response times while increasing accuracy. Insurance companies must focus on reducing customer effort as a key performance indicator (KPI). Forrester reports that 71% of consumers say that good service hinges on a company’s aptness to value their time. The good news? Field service management solutions leveraging artificial intelligence (AI) help property and casualty insurers lay the foundation for a positive customer experience from the first interaction. Adjuster Self Optimization vs. AI-Driven Optimization Field claims adjusting is full of in-day surprises that reduce efficiency and lead to service-level agreement (SLA) violations and poor customer experiences. To minimize the number and impact of disruptions, it’s important to have an accurate schedule, with each claim assigned to the appropriate adjuster. Predictive field service, powered by machine learning and data science, is key in making this happen. See also: And the Winner Is…Artificial Intelligence!   Companies are increasingly using machine learning to expose how and where to improve operational efficiency. This automated insight, combined with the wealth of precise data captured throughout the life cycle of every claim, delivers the feedback needed to improve decisions. By leveraging these capabilities, organizations can break out of the limitations forced on them by static systems and institute a culture of continuous improvement. Static, legacy solutions and approaches limit a providers’ ability to reach this level of precision and customer service. Improve Customer Loyalty The personal lines market is becoming increasingly commoditized, and it’s common for customers to choose a provider solely on price. To differentiate from competitors, insurance companies can provide a superior customer experience, especially in the face of a crisis. It’s no surprise that 84% of customers become frustrated when their insurance provider does not have or provide information they deem essential. By using AI, companies can ensure the right field adjuster is at the right place at the right time with the relevant information to address the customer need efficiently. Seventy percent of consumers expect their provider to have a mobile option for providing alerts, status updates and scheduling changes as well as a feedback loop on the quality of service provided. As a result, leading insurers are offering policyholders real-time engagement with Uber-like ETA visibility that eliminates a large percentage of calls into claim centers inquiring when an adjuster will arrive. Adjusters can then be scheduled in the most optimal way, based on actual availability, predicted traffic and other critical factors. Handle Complexity in Job Times and Locations Predictive job duration estimates the time it will take to complete a job based on all relevant task and adjuster properties. It continuously learns and improves from historical data. This means, for example, that, as an adjuster gets more efficient adjusting a certain type of claim, the expected job duration decreases. Let’s consider auto claims. To succeed, insurers must interactively expose appointments for appropriate drive-in or direct repair program (DRP) locations. Full awareness of customer’s location, employee and third-party availability, capabilities, cost and travel times quickly presents precise and appropriate options for a customer to select from. Field service solutions collect reams of detailed data at every stage of engagement and crunch the data through machine learning algorithms to enable improved performance. This increased precision and speed increases operational awareness, while pointing to where better outcomes can be achieved. Effective Use of Resources It’s easy to focus on individual adjuster performance when measuring job duration—but it’s not the sole purpose. It’s also important to go beyond looking at job duration at an individual level and maintain a holistic view into operations. With full visibility into performance across regions, claim types, customers and field resources, you can uncover which areas are strong and which areas need improvement. The visibility allows you to set standards, define goals and objectives and work toward improvements to the claim organization as a whole. This is an irreplaceable benefit of incorporating AI and one of the best ways companies can use historical data, in combination with machine learning, to help optimize field resources for the benefit of your customer’s experience. See also: Strategist’s Guide to Artificial Intelligence Managing appraisals, inspections, claims and catastrophic events to the customer’s satisfaction is table stakes, and must occur while balancing business needs. The inherent complexities of addressing these planned and unplanned activities— whether at the asset location, in a field office or at the site of a claim or catastrophe—require a high level of precision to balance the opposing objectives of providing exceptional service and profitability. The key performance indicator (KPI) improvements are visible through an increase in number of claims handled per adjuster, reduction in travel expense, reduction in calls to the claims center and fewer re-dos and missed claim appointments. By taking advantage of the latest field service management solutions, your organization can satisfy expectations efficiently, increasing your competitive advantage -- and your profits. It’s time to consider making a change for your field claims professionals in an effort to enhance customer retention and increase profitability. For success, we will need to reduce human error by leveraging applications powered by AI that make smart recommendations for your customers and your business.