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Pilots and gradual expansions from pilots may prove the potential of smart processing, but they do not create value on an enterprise-wide scale.
If the potential of smart processing is realized, it will do much more than make a few processes better and overcome legacy system challenges.
If machine learning (ML) is incorporated, the automated agents keep getting smarter and more efficient, and the savings go up.
Automation based on ML also has the potential to improve customer experience—creating the kind of intuitive digital service that until now has mainly been the province of fintech firms.
These AI elements dramatically lessen the time required for such an exchange, help focus the bank’s expert staff on cases that are more difficult or of higher value, and frequently reduce the overall number of employees needed. Today, applying for a mortgage is a frustrating, paper-heavy process that takes several months to complete and can involve dozens of often-repetitive requests for information by the bank’s lending department—a suboptimal customer experience that decreases the chance of a successful outcome.The mash-up of technologies that such vendors are creating gives banks an opportunity to radically improve their traditional services.We believe that several core areas of banking are ripe for smart-processing-led transformation, including deposits and payments processing, loan operations, trade finance, fraud prevention, and mortgage processing.Behind the Art Gallery of South Australia, art conservators have been hard at work preparing tailor-made mannequins for a much-anticipated exhibition of fashion couture.
Paolo Sebastian: X has opened at the gallery, profiling works from the label launched by Adelaide designer Paul Vasileff.
The second category of smart processing involves judgment-based approaches enabled by various types of AI software.