![]() ![]() Establish a governance framework: An RPA risks and controls program depends on an appropriate governance model inclusive of an overall automation strategy. ![]() Artificial intelligence can also be applied to dynamically alter insurance pricing based on customer behavior.1. Applying predictive modeling using machine learning algorithms, risk scoring can be refined. Accuracy and speed of risk profiling can be improved significantly by using automated tools to collect medical and social media data. In case of life insurance, factors affecting risk include medical history, family details, and personal activities. They may also check with other insurers on the vehicle’s previous insurance claims. For instance, underwriters at auto insurance companies need to check for each applicant’s criminal history and motor vehicle-related accidents. RPA software can be used to collate data from disparate sources into a common place allowing underwriters to make a decision on the applicant’s policy eligibility. Automating the process reduces onboarding delays and improves the customer experience while ensuring compliance with rules. Verification of the KYC (know your customer) documents is a cumbersome process when done manually as the daily numbers at a single branch can be in hundreds.Īn RPA tool with optical character recognition (OCR) engine can be used to extract data from KYC documents and verify it against prescribed regulations. Customer due diligence (CDD) is a critical onboarding process that helps banks assess the risk of new customers. In the financial services sector, regulatory compliance requires banks and other organizations to collect different types of official documents from customers for various services.
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