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Como afirma el dicho: renovarse o morir. La industria de seguros necesita transformar su cultura, operación y atención al cliente. SAS México realizó un foro de líderes del sector en el que, durante un panel conformado por representantes de MAPFRE, GNP y AXA, se debatió dicho tema y se concluyó
In a recent Computerworld feature, Deanna Wise, Executive Vice President and CIO of Dignity Health, encouraged forward-thinking CIOs to develop partnerships within their organizations to drive better customer experiences that translate into revenue. Wise has a strong record of doing just that, collaborating with SAS to implement advanced analytics throughout
A nivel global, la mayoría de las personas tiene conocimiento sobre el tema por las constantes primicias que vemos cada año acerca de muertes de celebridades ocasionadas por sobredosis de medicamentos recetados, pero esto solo es la punta del iceberg de un problema mucho mayor. De acuerdo con información de
As part of the 2017 College Series, I have invited a few individuals to write guest blogs. Today’s blog comes from Christopher Campau, the Collegiate Recovery Program Coordinator for the state of North Carolina. If you have a student who has struggled with substance use in high school and you
IFRS17 hat weitreichende Auswirkungen und bedarf umfassender Änderungen und Anpassungen im Finanz-Reporting von Versicherungen. Bezogen auf die IT-Landschaft sind insbesondere die beteiligten Accounting-Prozesse und -Systeme betroffen. Dazu gehören aber nicht nur das Hauptbuch und die Reporting-Anwendungen, sondern auch Quellsysteme und aktuarielle Systeme. Einführung neuer IFRS17-spezifischer Funktionen Die Prozesse und die
In last week's article about the Flint water crisis, I computed the 90th percentile of a small data set. Although I didn't mention it, the value that I reported is different from the the 90th percentile that is reported in Significance magazine. That is not unusual. The data only had
My colleague Gerhard Svolba (Solutions Architect at SAS Austria) has authored his third book, Applying Data Science: Business Case Studies Using SAS®." While the book covers a broad range of data science topics, forecasters will be particularly interested in two lengthy case studies on "Explaining Forecast Errors and Deviations" and
오탐(False Positive), 자금세탁방지(AML)의 새로운 도전 과제 2016년 2월, 미국 재무부 산하의 금융범죄단속반 ‘FinCEN(Financial Crime Enforcement Network)’은 플로리다 주 지브롤터 프라이빗 뱅크(Gibraltar Private Bank)와 트러스트 컴퍼니(Trust Company)에 자금세탁방지(AML: Anti-Money Laundering) 프로그램의 ‘상당한’ 결함을 이유로 4백만 달러의 벌금을 부과했습니다. 글로벌 금융 업계의 이목은 당시 보고된 여러 결함 중 ‘오탐(false positives)’으로 쏠렸습니다. *오탐(False Positive): 잘못
In recent years, solar panels have become much more economical, and therefore more popular. But because of the curvature of the Earth, the angle at which you need to install the panels varies, depending on where you live. In this example, I demonstrate how to visualize this kind of data
Technical Support regularly receives incoming calls from customers who have encountered the following transcoding warning: WARNING: Some character data was lost during transcoding in the data set xxx.xxx. Either the data contains characters that are not representable in the new encoding or truncation occurred during transcoding People are not always
David Loshin explores considerations for organizations gradually making the transition to Hadoop.
Conversations around equity in education are at a fever pitch. Decades of research show that students of color and low-income students are disproportionately taught by less effective or more inexperienced teachers. Civil rights leaders encouraged the Obama administration to require states to develop Equity Plans to ensure that every student
Ensemble methods are commonly used to boost predictive accuracy by combining the predictions of multiple machine learning models. The traditional wisdom has been to combine so-called “weak” learners. However, a more modern approach is to create an ensemble of a well-chosen collection of strong yet diverse models. Building powerful ensemble models
Are you caught up in the machine learning forecasting frenzy? Is it reality or more hype? There's been a lot of hype about using machine learning for forecasting. And rightfully so, given the advancements in data collection, storage, and processing along with technology improvements, such as super computers and more powerful
A common barrier to quantitative research, especially in health and financial areas, is the inability to share sensitive data due to confidentiality and privacy. It can be difficult and time consuming to get permission to share the data, which means useful research is delayed or not even attempted. However, collaborators seeking