Identifies policies that are likely to lapse, and how to approach the insured about maintaining the policy. Calculate the probability to lapse
Given similar customers, discovers where individual insureds may have too much, or too little, insurance. Then, proactively help them get the right insurance for their current situation.
Once a car has been towed to a body shop, use computer vision to help the assessor identify issues which need to be fixed. This helps accuracy, speeds an assessment, and keeps the customer informed with any repairs. Car damage detection
Given images of a property, identifies structures on the property and any condition issues. Insurers can proactively help customers schedule repairs by identifying issues in their roofs, or suggest other coverage when new structures, like a swimming pool, are installed.
Identifies claims which are potentially fraudulent. Rare events problem. Class imbalance is a huge challenge here
Improves the customer experience by offering relevant information about the coverage the insured may need based on life events, such as the birth of a child, purchase of a home or car.
Claims processing includes multiple tasks, including review, investigation, adjustment, remittance, or denial. While performing these tasks, numerous issues might occur:
- Manual/inconsistent processing: Many claims processing tasks require human interaction that is prone to errors.
- Varying data formats: Customers send data in different formats to make claims.
- Changing regulation: Businesses need to accord in changing regulations promptly. Thus, constant staff training and process update are required for these companies.
As customers make claims when they are in an uncomfortable position, customer experience and speed are critical in these processes. Thanks to document capture technologies, businesses can rapidly handle large volumes of documents required for claims processing tasks, detect fraudulent claims, and check if claims fit regulations.
Application processing requires extracting information from a high volume of documents. While performing this task manually can take too long and prone to errors, document capture technologies enable insurance companies to automatically extract relevant data from application documents and accelerate insurance application processes with fewer errors and improved customer satisfaction.
AI can assess customers’ risk profiles based on lab testing, biometric data, claims data, patient-generated health data, and identify the optimal prices to quote with the right insurance plan. This would decrease the workflow in business operations and reduce costs while improving customer satisfaction.
Insurance companies need to generate high volumes of documents, including specific information about the insurer. While creating these documents manually consume time and prone to errors, using AI and automation technologies can generate policy statements without mistakes.
Conversational AI technologies can support insurance companies for faster replies to customer queries. For example, a South African insurance company, Hollard, has achieved 98% automation and reduced cost per transaction by 91%, according to its solution providers, LarcAI and UiPath.