‘Putting AI into Practice with Taylor Cyr, Practice Lead, Public Sector/Higher Education at Quantiphi!’

Featured Speaker: Taylor Cyr, Practice Lead, Public Sector/Higher Education at Quantiphi!

Claims processing is a time-consuming process. The submitted claim documents have to be manually reviewed and verified for authenticity, while simultaneously digitizing the data and making outbound calls to request applicants for missing information. This makes the entire process inefficient, cumbersome and difficult to align with business priorities.

To stay relevant amidst the changing landscape and meet shifting customer expectations, it is important to:

• Transform business processes to make them more effective and efficient

• Provide engaging and value-added interactions

• Proactively support customers and manage risks

Quantiphi’s Automated Claims Processing solution accelerates the decision making process by identifying supporting documents and extracting relevant entities, leveraging AI driven recommendations to make more informed decisions and initiating automated outbound calls for missing and invalid information.

Quantiphi is an award-winning applied AI and data science software and services company driven by the desire to solve transformational problems at the heart of business. Quantiphi solves the toughest and complex business problems by combining deep industry experience, disciplined cloud and data-engineering practices, and cutting-edge artificial intelligence research to achieve quantifiable business impact at unprecedented speed.

Agenda:

• 12:00-12:30pm: Featured Presentation

• 12:30-13:00pm: Audience Q&A and interaction

About AI in Government:

AI in Government is where those working in and with the government get together to network, discuss, and interact on topics relating to AI, machine learning, and cognitive technologies. Join us at this monthly event for high-quality content with compelling & informative speakers and opportunities to network and connect with fellow like-minded individuals. ​