Artificial Intelligence is Ready to Make Data Automation More Efficient

Eighty percent of enterprises are investing in artificial intelligence. Is your business one of them? When Forbes summarized the highlights of Vanson Bourne’s “State of Artificial Intelligence for Enterprises” study, it was merely recounting old news. Intelligent automation has reached an inflection point: It has moved beyond science fiction stories to IBM/DOE’s Summit supercomputer and now Captricity’s new READ engine.

The READ engine is an enterprise-level AI solution extracts and enhances data from any customer channel—even handwritten documents—with powerful throughput, speed, and accuracy that surpasses humans. Trained using the world’s largest handwriting training dataset, the READ engine is a deep neural network that accurately extracts data that financial services, insurance, healthcare, and government organizations need for enrollments and operational workflows. Cognitive solutions like the new READ engine are now being implemented to deliver a value to a range of enterprise-level organizations, like helping to predict heart attacks in patients and innovating their paper-to-digital processes.

 

AI slashes costs, boosts workflows, enables analytics

Implementing AI helps financial services and insurance companies gain a significant advantage in the marketplace. These businesses are already moving toward investments in digital solutions, with an expected investment of over $5 billion by 2020.

Cost reductions can be realized from solutions like the new READ engine because AI is significantly less expensive to implement than employing in-house manual data entry teams and making seasonal adjustments. Using an engine like READ is also much more cost-effective than engaging in business process outsourcing (BPO), which can encompass not only the labor costs, but also the increased concerns around data security. Operational efficiencies are a key outcome of the utilization of Captricity’s new AI READ engine. Since the AI boasts greater than human accuracy, significantly fewer errors need to be managed, resulting in reduced cycle times and rework on difficult or not-in-good-order (NIGO) data. This ability to consistently achieve high accuracy with reading handwritten data, coupled with speed – a single READ engine can outperform 80 FTEs – many businesses are at last realizing the power of digital adoption. This improved efficiency and reduced reliance on manual data entry frees in-house employees to perform more high-level, critical tasks.

This boost in operational efficiency has a direct impact on the customer experience. Customers largely experience the impact of the rapid, more accurate AI via faster, more efficient enrollment processes. Since there are fewer errors to address, customers will experience lower levels of frustration and improved interactions with the business. In addition, this improvement in the customer experience extends to allowing customers to work with paper while enjoying the benefits of digital. For example, there are some customer populations that may not be able to effectively use online applications or forms, such as the disabled or elderly. Rather than forcing these customers to go digital, these individuals can use a paper form, which may be more comfortable and convenient. Even large enterprises in government or financial services are burdened by regulations so the prospect of going “fully digital” is difficult and costly.

Cognitive data automation also enables businesses to extract data from historical documents. Locked away in many Iron Mountain warehouses are key customer insights that enable businesses to target new demographic markets or build new analytical models to support their existing business. Moreover, the ability to add multiple document types—even difficult-to-read forms results in the creation of larger datasets. Larger data sets increase a firm’s ability to better identify patterns and even reveal possible areas of growth.


AI solves real-world problems

What does an AI in action actually look like? Most people would likely think of IBM’s Watson sinking Ken Jennings and Brad Rutter during a Jeopardy! match, but in the world of AI, this event is ancient history. Instead, the focus should be on the more advanced, useful technologies like Google’s new virtual assistant called Duplex. (Duplex is so advanced that individuals interacting with it could not tell that it was an AI.) Not every business will require a natural speaking AI scheduler, but every business can use AI in ways that help them reach their goals and aspire to new ones. Captricity has partnered with numerous organizations to help innovate their paper-to-digital processes with the power of AI.

Insurance automation is key to realizing greater productivity and cost savings. A simple test case can highlight how Captricity’s new READ engine can make a difference in operational efficiency and cost reductions. For example, a large insurer needs to manage sensitive information from forms, so accuracy is critical. However, its legacy system is chipping away at revenue and efficiency. The system itself has already cost the company $850 million in initial fees and is siphoning off another $7 million in additional costs. By using Captricity’s cognitive document automation solution for 10M forms, this business could slash an estimated 75 percent of its FTE costs. Overall, it could reduce its annual overall costs from $7 million to a bit over $4 million, allowing the company to more effectively allocate human workers for higher-value tasks or explore other strategic priorities.

At MetLife, Captricity helped reduce the amount of time spent on managing data exceptions. By implementing the new Captricity READ engine and leveraging an easy-to-use interface for managing data exceptions, MetLife was able to streamline the automation process and reduce the amount of time spent handling exceptions. Overall, the processing time per form was reduced by more than half, with the amount of time spent on managing exceptions reduced by 70 percent.

More recently, Captricity has helped Flint, Michigan’s endeavor to replace all of its lead pipes. Clean water is essential to life, and when the people in Flint, Michigan, were suffering from lead-laced water, AI was able to help realize a workable solution. READ was able to extract information successfully from about 140,000 handwritten service line records and plumbing invoices. By aggregating multiple third-party data sets, the AI was able to deliver key insights into when and where work crews could begin replacing the dangerous pipes.

 

Become future-ready with AI

Integrating AI into business processes can seem daunting but that emphasizes the need with which enterprises need a partner in intelligent automation that is experienced, highly skilled, and capable of guiding the entire process from beginning to end. Today, Captricity’s READ engine is used by eight of the top 10 U.S. life insurers and other large businesses.

The experts at Captricity possess deep knowledge in automation processes and have helped many businesses, including MetLife and New York life, capitalize on the speed and efficiency gained from implementing AI to innovate paper-to-digital processes. If you’d like to learn more about how you can start using intelligent automation to enable analytics, reduce costs or increase efficiency, read our newest white paper. Gain insight into how the new Captricity READ engine is helping businesses thrive in a technology-driven marketplace.

Stephen Dawson

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