Recorded Future Partners with FraudWatch

I see that Recorded Future, who we worked with early on,  is partnering with a company doing 'Brand Protection'.  Which is the place we had originally tested a concept.  In our case both the security of brands due to competitive activity, but also the risk of change in their context.  Also beyond this the inclusion of specific 'Take down' services.  This makes what they do more direct, rather than just future visual forecasting of changes.  Also links to things in the news, like the manipulative use of bots or detection of fraudulent brand online presence.   Overall a good idea.

Recorded Future Introduces Takedown Services to Complete Comprehensive Brand Protection Offering

Go From Brand Monitoring to Active Response With Recorded Future Through FraudWatch Partnership

BOSTON – August 1, 2018 – Recorded Future, the leading threat intelligence provider, has announced it will now provide takedown services as a part of the company’s brand monitoring offering through a new partnership with FraudWatch International, Inc. This feature enhances the company’s brand protection services, which include defenses against social media brand abuse and typosquatting, the detection of fraudulent websites, and more. This announcement comes following the publishing of The Forrester Wave™: Digital Risk Protection, Q3 2018,1 in which Recorded Future was named a Leader.

Fake accounts, apps, and websites are often designed to profit from maliciously redirected or accidental traffic, but they can also result in major damage to an organization’s brand reputation. These accounts can host inappropriate content and target customers with phishing scams. Additionally, these fake domains can host malware or trick users into giving away their credentials, representing a serious security risk to consumers.

“Comprehensive threat intelligence must include brand protection that addresses both reputational concerns for organizations and online abuse risks for customers of those organizations. Threat intelligence starts with detection and drives to security actions. Partnerships with companies like FraudWatch are critical to delivering risk reduction for our customers.” — Matt Kodama, Vice President of Product at Recorded Future     .... "

Computer Vision Assessing Cardiovascular Risk

From Google Research, an interesting application.  With considerable detail about the experimental approach.   Instructive.   Note its about risk rather than diagnosis.   Examples of retinal images.  Would like to see more medical /statistical commentary on the results.

Assessing Cardiovascular Risk Factors with Computer Vision
Posted by Lily Peng MD PhD, Product Manager, Google Brain Team 

Heart attacks, strokes and other cardiovascular (CV) diseases continue to be among the top public health issues. Assessing this risk is critical first step toward reducing the likelihood that a patient suffers a CV event in the future. To do this assessment, doctors take into account a variety of risk factors — some genetic (like age and sex), some with lifestyle components (like smoking and blood pressure). While most of these factors can be obtained by simply asking the patient, others factors, like cholesterol, require a blood draw. Doctors also take into account whether or not a patient has another disease, such as diabetes, which is associated with significantly increased risk of CV events. 

Recently, we’ve seen many examples [1–4] of how deep learning techniques can help to increase the accuracy of diagnoses for medical imaging, especially for diabetic eye disease. In “Prediction of Cardiovascular Risk Factors from Retinal Fundus Photographs via Deep Learning,” published in Nature Biomedical Engineering, we show that in addition to detecting eye disease, images of the eye can very accurately predict other indicators of CV health. This discovery is particularly exciting because it suggests we might discover even more ways to diagnose health issues from retinal images.  .... " 

Risk Detection is Important

Not often covered well enough, worth thinking about.  Detecting the Risk, working with business partners to understand its implications, is important.  In my observation, not often done well. 

The neglected art of risk detection by  Piotr Kaminski and Jeff Schonert in McKinsey

At the core of risk management is risk detection, an art that can be skillfully improved if banks and regulators accept new analytical methods.

The modern risk-management framework generally relies on the “three lines of defense” scheme, with the businesses, control functions, and audit as the first, second, and third line, respectively. The concept borrows from the language of military strategy, in which intelligence plays a key role. For risk management, intelligence means effective detection: to prevent the bank’s reputation, liquidity, and capital position from being harmed, the lines of defense must detect risks early.

Detection is fundamental in risk management, embedded in its activities and processes. Credit scoring, for example, is a tool for detecting potential borrower-default risk at the application stage, while customer due diligence is designed to identify high-risk customers during the onboarding process, as part of the bank’s know-your-customer (KYC) program. Risk managers are practicing the art of detection when they identify instances of fraud, spot a drifting investment strategy in an asset-management business, monitor their network’s end points to locate cyberintrusions and data theft, or identify potential rogue traders.

Most executives and risk professionals will quickly acknowledge the basic importance of detection. Yet the efficacy of detection—and the levels of “detection risk”—vary widely among risk disciplines and from bank to bank. With poor detection, threats can rise to existential proportions, as some of the world’s largest institutions have learned in recent years. Weak detection capabilities can be costly. Manual controls, for example, are not especially effective and yet they always cost more than automated controls. Poor detection can result in high levels of false positives and the needless diversion of valuable risk resources. .... "