Customer experience has become a key differentiator in today’s Insurance market. Customer experience is the fulcrum around which incumbents are going to take on Insurtech challengers. Unfortunately, the insurance sector has traditionally been more product-focused than customer focused.
Most Agencies are focused on new customer acquisition and managing existing clients is mostly an afterthought. Many agencies believe retention as a natural consequence of good customer service. Economic analysis of acquisition and retention tell a different tale. The cost of acquisition of a new client is 20 times more than the cost spent on retaining a client. This includes the cost of resources needed to identify a prospect, quote them, and write the policy. The customer success rate of selling to a new customer is sub 10%.
Increasing customer retention by 5% can increase profits/policy by at least 20%. Of course, the longer an agency retains a client, the more profitable that the client becomes. That’s why even a marginal shift in overall client retention can have a significant impact on an agency’s bottom line. The number one reason why clients switch is simply because of communication. Lack of personal connect, no callbacks or just the perception of no customer care are the reasons behind unhappy clients.
Insurance company executives are being increasingly pressured by the board, partners, and CSR to more aggressively leveraging new technologies like AI and ML to manage customer experience. Insurers need the more customer-centric process from the ground up and rewire of the existing products & systems. Customer acquisition and retention challenges are huge, as Insurers face the challenge of relating the centuries-old industry to a newer generation of consumers. Insurers struggle with adopting smart technology for closing the gap between the company and customers, and the gap between old and new. Not every insurer is ready for AI or able to take the full advantage of the opportunities the technology offers. There are several ways Insurers can prepare and evolve to a position of strong customer experience.
Agencies can bring in Chatbots that can be used to quickly respond to the customer queries without procrastinating. Automatic notifications, reminders and personalized e-mails can be triggered to Clients using BOTs/ technology. AI supported self-service portals help insurers get closer to their customers, increase their loyalty and improve service quality, all of which may greatly contribute to better customer experience.
Many Insurers prioritize their AI investments completely on customer-facing areas to maximize “the moments of truth” often at the cost of weak backend process. While AI can aid in information analysis in voice or text and then quickly and accurately deliver relevant policy information, the customer experience will be wobbly if the backend policy checking infrastructure is weak. Unfortunately, insurance practices are rooted in traditional manual practices simply are not set up to move at high velocity. Many insurance activities are repetitive and prone to manual errors.
Industry insiders realize renewals happen 365 days and seven days a week and most risk managers and brokers consider 30 or 60 days before renewal, termed crunch time in the industry to be critical. However missing information, poor communication, errors cause delays in renewals or rushed quote that does not provide the best customer experience. While Chat bots can improve the speed of customer service interactions, ultimately the accuracy and speed of policy checking can happen only if the backend processes are standardized, automated and enabled with smart technologies to hasten the activity without rework or waste.
Insurers are aware 70% of the policies, especially motor and housing, are automatically renewed each year. Insures realize customers do not renew if the service is poor or the payment process is cumbersome. However, annual renewal processes involve a high possibility of manual error and long wait times for customers. Slippages and renege are common. Many a time low value, high volume policies are missed or delayed leading to lapsed coverage. Data entry issues, data integrity and non-standard process also contribute to below average customer experience.
Insurers realize companywide benefits will only flow if the AI and ML tools bring all-encompassing impact and must, therefore, involve both frontend and backend processes. Insurers can use AI to bring speed, efficiency, and decreased fraud. For many insurers with completely, people based processes claim settlement and fraud happen to be the juiciest “low hanging fruits”. AI to process vast quantities of paper information on policyholders is a honey pot for AI intervention. Insurtech companies have developed smart AI-based solutions to process hard copies, detect fraud and digitize information.
Renewals bring better margins and sustainability to the insurers. Today customers expect an omni channel hassle-free self-managed renewal process. Automating renewal process using AI will not only remove the human burden and boredom but also drive higher productivity. Automation can also serve as another delivery channel to engage in low-value low-risk policies. This would enable brokers and underwriters to spend more time on higher risk and more profitable business. Automation of renewal process involving both on-demand renewals with no touch or minimum touch reduces costs and results in improved productivity. Controlling TAT has a major influence on administrative cost savings, which is a key driver for transforming the broker business Exdion has developed an Artificial intelligence (AI) led solution to offer seamless automatic renewal policy check out. Exdion Policy on Demand (ePoD) involves Robotic process automation (RPA), analytics and cognitive computing to transform “manual led” renewal process to error-free intelligent process.
Exdion has developed bots which are software programs that automatically match the policy information against configured data and approve once the match is perfect. Bot driven automatic approval enables code-driven continuous delivery of policy renewal eliminating the need for a dedicated FTE to manage the same. ePOD offers insurers the flexibility to customize their automated policy renewal process and issuance to accomplish a complete end to end business-specific policy renewal. ePOD enables insurers to configure custom business process for renewal, including the capability to configure selection criteria for policy for renewal, one-time or multi-year recurring execution with comprehensive auditing and error-free capabilities.
AI adoption for backend operation is critical to realize the benefits of AI deployment on the customer-facing side. Deployment of AI to improve backend operations will bring three major benefits to insurers: lower costs, happy customers and higher growth. Deploying AI and ML tools for backend process such as automatic checking gives you significant cost advantage. It costs much less compared to a Full-time employee (FTE) cost. Secondly, human errors which can range between 5 to 7% get completely eliminated. Moreover, your employee would be able to spend time on high-value non-boring activities. Employee satisfaction increases and employee attritions nosedives. Importantly, customer experience is a manageable and predictable process as both front and backend operations work in tandem to seamlessly delight the customer.
Remember all transformation journeys require a new perspective and approaches. To gain from AI led customer experience improvements, Insurers must have a clear vision of what the future must be. Invest and manage your transformation journey consistent with your goal and absorptive capacity. Do not have to rush to a radical change program. Prioritize areas for improvement, invest wisely, support unlearning and relearning and scale as you go. As you prioritize the AI initiatives, do not ignore data, operations, and people fronts. It is important to know AI solutions alone will never be a viable strategy. AI is an enabler of a strategy.
Without clearly defined goals, a flexible operating model capable of experimentation and without leadership or champions, AI tools alone are unlikely to fulfill the growth promise and drive service excellence.