Minimize Risk, Build Customer Excellence & Enhance Regulatory Compliance through AI-based Solutions.
The insurance industry is facing a challenging time with increased risk complexity due to global climatic changes, pandemic, and cybercrime. Also, disruptive Innovations like smart homes and autonomous vehicles have created new industry dynamics and unprecedented scenarios while designing policies.
Artificial intelligence is helping Insurance companies to adapt to these challenges by providing highly reliable and robust solutions for underwriting, valuation, and claim management. AI based solutions help Insurers to protect themselves from incurring losses and provide efficient services to their customers.
Reduce turnaround times & improve customer experience through the automated underwriting process. Machine learning algorithms calculate risk by analyzing customer data, such as age, health vitals, location, creditworthiness, financial information, etc. Provide price suggestions for different customers based on the risk factors. Save manpower efforts and time by letting underwriters focus on complex risks while automatically managing the low-risk cases.
Automate processing of service requests such as address change or updation of bank mandate using machine learning. Extraction of changes from voice transcripts, emails, faxes, or other sources and updation of the documents and internal systems with the required changes. Automate document-intensive operations, including the processing of loss run reports, analysis of the statement of value reports, communicating explanations of evidence of insurability to customers, and other processes.
Automate and streamline the entire claim management process right from data capture, settlement and approval to payment tracking, salvage and communication management. Bots enabled claim review, policy verification, fraud checks and payments processing to make the claim process faster and highly efficient.
Boost insurer persistence through predictive analytics based customer retention strategy. Risk assessment based on churn score derived from analysis of different parameters like customer demographics, financial product details, transaction history, financial product performance and customer engagement on different channels.