Maya is the perfect Insurance agent.
She has the highest satisfaction ratings from customers, instinctively senses their moods and offers relevant conversations, helps them buy or cancel or upgrade policies and empowers her colleagues to settle most of the claims in three seconds.
Maya is an AI driven chatbot.
AI has come a long way from a system of records (eg: multiple spreadsheets) to today's advanced intelligence on demand (AlphaGo, Siri, Cortana, David). AI systems take in unstructured big data and analytical inferences. It then trains hard through intelligent algorithms on master data that is composed of historical data, current trends and future possibilities. The main goals are to...
1. Identify forward-looking patterns.
2. Optimize operations.
3. Automate business processes.
It is this mixture of sophistication and simplicity that makes AI systems omnipresent in every sphere, ranging from smartphones to driver-less cars.
AI empowers agents to move from risk response to risk prevention.
AI is made for Insurance. It acts as a complement to the humanistic approach in insurance pricing, claim handling and fraud detection. This is because AI systems, by themselves, cannot solve problems. It's capabilities need to be leveraged to act as a powerful booster to agent productivity and customer engagement. To achieve this, optimize, transform and create new insurance products, services, business models and business ecosystems.
AI guides insurance agents to use new information sources, explosion of computing power, easy availability of Machine Learning tools and advanced algorithms.
Start with handling claims
Digital AI technology in Insurance CRM can automate claim handling processes through robotic process automation. The result being significant uptake in claim processing speed and bringing in machine learning to find patterns for faster and reliable fraud detection.
There are limitations to human perception. AI, with its deep learning algorithms is faster and better at processing images in detail. AI in imaging, sensors and document management systems (DMS) can help assess the severity of damages and predict repair costs or probable fraud, if any.
Joe wanted to claim insurance against his damaged car. He uploaded a snap of the damaged car, entered the relevant details on the his insurance mobile app and was instantly gave a preliminary approval. Joe was elated. But his joy was short lived. AI infused sensors in image scanner compared the uploaded snaps and found out it matched similar claims in other states. You see, Joe had a history of making fraudulent claims in different states. Thanks to AI powered by machine learning, the insurer was able to find out the patterns and flag down the application.
Automated Underwriting
CRM in insurance can help automate underwriting. Insurance agents can harness the power AI, to find and curb risks beforehand. This is possible with mountains of personal data generated through social media. It is safe to assume that if a customer's virtual presence is an embodiment of healthy lifestyle, the same is inferred for his personal life as well. Additionally, AI lends agents the power of predictions by taking into account economic bubbles, historical sales, natural disasters etc. Automated underwriting offers three main advantages.
1. Insurers can cut in-per property inspections.
2. Agents can focus on exceptions.
3. Insurers can mine insights hidden in paper records.
Jason wanted to buy a medical insurance from a top insurance company. John, an insurance agent used AI inside CRM to combine the data from Jason's demographics, public social media information, weather, telematics and wearable data to conjure up a complete user profile that spoke about Jason's probable health risks. This empowered John to offer a discounted premium plan and delight Jason.
Virtual Assistants - The gatekeepers
Insurance is a product that cannot be experienced in person. And customers are as it is uncertain about intangible products. Uncertainty inhibits buying decisions.
AI enables agents to intervene when needed with chat, video or co-browsing at the point of abandonment in a customer journey, and deploy win back strategies. They can use predictive models and machine learning to target customers based on buying propensity, demographics, and psychographics.
AI uses the power of Natural Language Processing (NLP) and facial recognition to deliver conversation based solutions. Employing virtual assistants, in the form of smart chatbot, powered by natural learning processing and sentiment analysis, can help categorize concerns and instantly gratify wishes. They allow agents, guided by CRM in insurance, to analyse customer intentions and offer tailored products or services.
Leading insurance companies are now using chatbot powered by AI to convert leads. It's conversational interface analyzes customer requests and responses to connect the right opportunity with the right agent. It is also integrated with another chatbot that uses deep learning to answer basic health and medical questions and if needed, connect with expert consultation.
AI in Insurance goes beyond operational improvements like paperless applications and cuts cost for both providers, insured and increase customer engagement.
