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This often result in inefficiencies, delays, and increased risk of errors and non-compliance. Historically, the extraction of relevant data from these documents has relied heavily on optical character recognition (OCR), manual dataentry, or basic forms from the LOS or DMS with the dealership salesperson standing as the go between.
Accuracy at Scale – Building a Foundation for Informed Decisions Human error is an inevitable part of manual processes and dataentry. IDP eliminates this risk factor by extracting data with exceptional accuracy using advanced algorithms and AI. In essence, IDP doesn’t replace credit analysts; it empowers them.
The digitization of the financial services sector has generated vast amounts of unstructureddata in the form of documents, either PDF or images, and volumes of data that can hold valuable insights for businesses, and help make better decisions. However, extracting meaningful information from this data has been a challenge.
Especially, when manual entry requires, for compliance reasons, the dreaded “stare & compare.” Think dataentry, form filling, and basic calculations—tasks that follow a clear set of instructions. Reduced Errors : Minimizes human error by eliminating manual dataentry.
Regulatory Compliance Banks and financial institutions must comply with a wide range of regulations governing lending practices such as anti-money laundering (AML), Know Your Customer (KYC) requirements, and others specific to lending. They can answer frequently asked questions (FAQs) about loan applications and recovery processes.
It uses AI capabilities like NLP and machine learning to analyze, categorize, and interpret vast amounts of text-based healthcare data. With SurveySensum you can automate data collection from multiple sources, ensuring that patient feedback, complaints, and reviews are consolidated in one place for a unified view. Why is it Important?
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