The Internet! news headlines are full of articles about the benefits of artificial intelligence for business.
However! if we talk about business – good content can be found no closer than 2 pages in the search engine.
Marketers tout terms like “self-learning” and “independence” to attract the bulk sms thailand attention of corporate clients! but what is the practical benefit of using machine learning to automate an organization’s information processes? Is AI technology superior to what is us! today?
Man vs Machine
According to Forrester’s 2018 report “The Sorry State of Digital Transformation!” up to 22 percent of businesses still have business processes that are far from perfect! despite the fact that these are critical aspects for customer satisfaction and revenue growth. If you ne! to r!uce operational costs! employee work schedule in the company: part-time or full-time: what is the difference and advantages increase customer loyalty! and r!uce errors! automation can actually answer some of your prayers. The world has provid! businesses with several tools to automate information processes (in plain English):
Automation with AI – A person provides the material – the program understands itself.
Let’s look at an example of loan documentation compliance to compare the two approaches from a critical perspective. Regardless of the type of loan – auto loan! mortgage loan! or home equity loan – a large amount of documentation is requir! to satisfy application and regulatory requirements. Verification requirements for documentation are met! and processing documents containing all the necessary information is a painful and time-consuming task. In an effort to minimize labor intensity! many lenders are looking for ways to simplify the business process.
Traditional automation of information processes
Traditional automation – Man creates the rules! machine executes them.
Traditional automation of information processes begins with a manual assessment. A taiwan lead properly manag! project requires an inventory of documents for a given lender and loan type. Then! employees collect templates of all the necessary documents by reviewing various sources. Then! employees organize hundr!s of receiv! documents by type and analyze them to identify unique characteristics – these will be us! for automatic identification in a typical loan approval workflow.
Once employees have identifi! all the characteristics of the documents! an expert analyst forms an algorithm using the characteristics as rules in the document collection system. The rules must be test! to identify any incorrect classifications that require adding new rules or fine-tuning existing ones. Once testing and fine-tuning are complete! the rules are transferr! to the workflow.