Like all other sectors, insurance too is going digital. Consumers increasingly seek digital self-service tools, whether they want to buy a policy or submit a claim. Digitalization also has a role to play when it comes to facilitating better customer understanding, which is an important business imperative for the insurance sector. At the same time, insurance providers are seeking ways to build greater operational efficiency, trim costs, reduce fraudulent claims, and build greater resilience, especially in the context of the COVID-19 pandemic.
Insurance claims typically involve laborious processes from both a customer and provider point-of-view. Filing a claim, the investigation and review process, approval, and processing call for several man hours that can otherwise be devoted to cost or digital analysis for constructive decision making and business improvement.
Technologies such as RPA can help address all of these challenges by allowing for seamless customer journeys as well as handling and processing day to day business activities such as marketing, administration or even data analytics. Automation brings in efficiency, better distribution, reduced overhead and lower latency. Therefore, routine tasks around claims processing, servicing, mail centre management, present enormous opportunities for automation.
From a business point-of-view, the insurance sector stands to benefit greatly by integrating legacy software with third-party systems to streamline its internal workflows. For example, automation projects aimed at enhancing employee productivity and improving customer and agent experiences have accrued benefits such as a gain in man-hours per week, increase in incoming claims, and reduction in Average call Handle Time (AHT). There are several minor processes that have been automated across businesses with 100% accuracy.
Automation Opportunities in Insurance
In insurance, just like in other industries, time is of the essence. With automated systems at the helm, activities such as checking validity of customer data, evaluation of default risk, screening fraudulent activities, and processing of claims can be transformed into a seamless process. While business processes must be continuously monitored for opportunities, some of the components of an insurance processing cycle that can be automated for visible benefit include:
Claims process: Multi-channel claims submission (email, web, AI chat, etc.), case investigation, third party invoice and payment processing, and recoveries can be automated to achieve reduction in operations cost, reduced revenue leakage and an increase in NPS. For example, an insurance carrier was using attended robots to help monitor email, process the claims forms, create first notice of loss and based on specific set of parameters, identify and triage the COVID-19 related claims to the specialist processors. The carrier not only drastically reduced the claims triage time, but it also resulted in better efficiency and claimant servicing.
Servicing and billing: Automating multi-channel service request management, Policy servicing and surrender, collection management and renewal processes have displayed reduction in operations cost and an increase in renewal rate. A personal accident carrier used a human-in-the-loop App to review all relevant data and take decisions, after which the downstream processes continued by the unattended robot.
Contact centre and mail centre: Single interface for agents to handle ‘one-and-done’ transactions (e.g.: claims status or premium change management), customer issues and tickets, interaction analysis and feedback management have shown reduction in operational cost and reduction in call-in volume. For example, requests through online or Chat interfaces as well as contact centers are handled by agents assisted by a bot.
Sales, distribution, and underwriting: Agent onboarding and offboarding, case status, etc. can be automated to see a visible reduction in operational cost, a higher conversion rate and a massive reduction in turnaround time to quote.
F&A, reporting, and audit: Reconciling premium received, validating payments and bank statements, closing ledgers, standardising reporting formats, meeting regulatory compliances, etc. have been automated to show 100% accuracy and compliance in the process with reduction in operational cost. For instance, a robot can scrape multiple data sources online and create customized content based on where you’re located. The bot then compiles the data into a daily report and brings the latest updates, and helps guide on getting tested, and other fact-based helpful resources. Another example is KYC, which is being automated by many of our customers.
AI enabled platforms can enable automation of ‘high impact journeys’ that belong to a process cycle. The first step is to scientifically identify automation opportunities. Insurance companies can use process mining and task mining tools to discover automation opportunities powered by AI.
These solutions also support the regulatory requirement to have all key processes documented. They can extract data from structured/unstructured claim documents to build on the Intelligent Automation required. They then manage, deploy, and optimize automation at an enterprise scale. Lastly, tools such as chatbots can bring customers and employees into the AI loop, and drive a seamless collaboration of man and machine.
With all the technologies available today, an insurer can predict claim fraud with the help of a machine learning model on AI Fabric. A combination of integrated sources and ML models running on AI Fabric can help predict fraudulent cases, eliminating the exhausting manual labour involved earlier.
In short, automation in Insurance will evolve to facilitate improved bottom lines with continuously improving ML models.
Source: The Economic Times