Today’s businesses increasingly rely on intelligent automation. Many companies are achieving their goals by turning to emerging technologies like artificial intelligence (AI) and machine learning (ML) for help.
While both have received a lot of attention in the past, recent advances in processing technology are helping businesses show their work to customers in new and exciting ways. Here are a few examples:
- Error Determination. Any process has the potential for errors. Businesses have historically had limited options for improving service levels: training, checking every item in a process multiple times, or performing random sampling of items flowing through a process. What if we could check only work that has errors? We can now use AI and ML to create analytical models based on key elements of a process to determine the probability an item has an error, then route it through a quality process without impacting other work. Solutions like Quality Check AI can improve your quality day-one, reducing costs and improving customer satisfaction.
- Saving Costs. Most organizations see straight-through processing as the ultimate goal. The process moves the item along, updates systems, then a human is involved only if there is information presented that requires human decision making. The biggest challenge is often at the beginning of a process. For example, in highly regulated fields where regulation hasn’t caught up to allow end-to-end digital processing, like financial services and healthcare, there is still a significant volume of incoming paper and even faxes. Most intelligent character recognition (ICR) and optical character recognition (OCR) solutions have made slow or negligible progress over the years. Historically, 90% character recognition and 40–60% word recognition were considered to be good enough. With new AI and machine learning models, we can use large amounts of data to “train” these models to recognize words and sentences that even human workers may find difficult to read. SS&C Chorus Document Automation, an AI-driven ICR, has a 98% accuracy rate, even on handwriting, making it more accurate than humans.
- Meeting Service Level Agreements (SLAs). Generally, work is prioritized through some calculation based on business days. During traditional processing, the system distributes work objects to users based on a work selection routine. It could be first-in, first-out (FIFO), based on some set of rules defined by the company or self-selected by an associate. Depending on the type of work selection routine in use, the system scans a list of outstanding work objects and chooses objects for each user according to queue and privileges. None of these are ideal, however, as some work needs to be prioritized. Whether it is an SLA, a “VIP Customer” request, or regulatory, companies need the flexibility to prioritize some work over others. Add digital workers (robotic process automation) into the scope and the situation can get messy to maintain. By launching a solution like Work Prioritization AI, an intelligent way to identify what works needs to be prioritized, there is no need to depend on static rules or to miss an SLA as the AI can learn from your current prioritization patterns and prioritize the work dynamically.
Read our "The Digital Mailroom: Reimagined with AI-Driven Document Automation at 98% Accuracy" case study to learn how SS&C Chorus used artificial intelligence and machine learning for a large insurance company to achieve straight-through indexing with 98% accuracy in its mailroom.
Built on SS&C’s reputation as an end-to-end solutions provider, SS&C Chorus delivers a unified suite of intelligent automation technologies, including Chorus Document Automation, the AI-driven document automation technology, Chorus BPM, an award-winning digital workflow solution, and consulting, implementation and managed services to accelerate straight-through processing in complex, highly regulated environments such as insurance, banking, financial services, and health. SS&C Chorus is available via SS&C’s secure private cloud, on-premise and public cloud offerings.
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