Candor Technology announced that it has created the first-ever automated underwriting engine for Loan Quality Services (LQS), further helping clients transform their business models for the twenty-first century. "Candor is dedicated to finding new and innovative ways to leverage technology to enhance the lending process" Candor is offering lenders its Loan Quality Services for just $75 per loan file, enabling them to adapt to current market conditions while still offering borrowers best-in-class service. Candor's LQS addresses many pressing concerns such as QA's impact to fallout, QC impact to loan profitability, leakage of recurring defects from QA to QC, and originator's quality ranking with investors. Candor's LQS gives client members access to automation of numerous capabilities, including primary source document and data validation; thorough re-underwrite of income and asset; application of guidelines and overlays; defect identification and resolution; and reporting and repurchase defense data. AI News: An Investment Into Artificial Intelligence as Daktela Buys Coworkers.ai

Sepsis is a major medical issue. In the next week, an estimated 5,000 people will die from sepsis in the U.S. alone, and one third of all hospital deaths are related to sepsis (according to U.S. Centers for Disease Control and Prevention figures). These deaths are preventable, but by the time sepsis is detected, it's often already too late. One way to reduce incidences of sepsis is with the application of artificial intelligence. The staff at Sentara Healthcare are using an AI-enabled prescriptive analytic tool developed by Jvion, which identifies who is at risk of sepsis, alerts clinicians and suggests interventions tailored to each patient's needs.

Artificial intelligence is coming to healthcare. In fact, in areas such as radiology and cancer detection, it's already here in places, and is poised to become ever more prevalent in the industry. Which naturally raises a question for nurses and physicians: Is AI coming for my job? At least according to experts we interviewed for our Focus on Artificial Intelligence. That said, both AI and machine learning are in a prime position to alter clinical workflows and physician training.

Healthcare is at a two-tined fork: One strip leads to repeating the same mistakes others have already made while the more enlightened rail learns from those instead. That avenue is not a foregone conclusion. Hospitals' development and implementation of emerging technologies under the artificial intelligence, cognitive computing and machine learning rubric is nascent enough that there's time to choose which tine to take. Taking the well-trodden path will neither be easy nor exactly inexpensive, so why pick it? There's a lot to be gained -- and piles of money to be saved -- by learning from those who have gone before.

The future might not be far away. Editor's Note: This article initially was a presentation at the marvelous 2017 Saberseminar. Advancements in technology allow Buck Showalter to unplug a USB drive from a port behind his left ear and transfer it to an iPad. They don't call them iPads anymore, but there's no need to be bombarded with a bunch of unnecessary jargon right now. If that's what you came here for, sit tight.