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Category: RESEARCH PAPERS

China can reshape the global oil market

CMCRC researchers show that China is still on track to reshape the global oil marketTalk of a petroyuan replacing the petrodollar has been called “premature”, but analysis from CMCRC shows that China’s new crude oil futures contract is exceeding expectation when compared to the established US and European exchanges in key areas.In March 2018, The

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Adviser Ratings becomes CMCRC’s 58th industry partner in financial markets

CMCRC’s reputation for delivering commercialisable outcomes for industry partners continues to grow.Adviser Ratings has recently partnered with CMCRC. Launched in October 2014, in the wake of the Future of Financial Advice reforms (FOFA), the Financial System Inquiry (FSI) and financial planning scandals of the time, Adviser Ratings’ vision is to improve the penetration of financial

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SOLVING THE DATA CONUNDRUM: THE FUTURE OF UNIVERSITY RESEARCH IS COLLABORATIVE

David Wright, Group CEO of Capital Markets CRC, explains how universities can benefit from translational research in the data-driven digital economy. The digital economy has arrived and, according to Deloitte, it is undermining “conventional notions about how businesses are structured; how firms interact; and how consumers obtain services, information, and goods.” The ability to harness

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MERGER TO CREATE GLOBAL TRANSLATIONAL RESEARCH POWERHOUSE

Two Australian research centres already responsible for some of the biggest innovations in market quality enhancements in health, capital and other markets have merged – creating a global translational research powerhouse based in Sydney. Capital Markets CRC and SIRCA both have outstanding individual track records of success in bringing global industry together with Australian and

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LEVERAGING BIG DATA ANALYTICS TO REDUCE HEALTHCARE COSTS

The healthcare sector deals with large volumes of electronic data related to patient services. This article describes two novel applications that leverage big data to detect fraud, abuse, waste, and errors in health insurance claims, thus reducing recurrent losses and facilitating enhanced patient care. The results indicate that claim anomalies detected using these applications help

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APPLICATION OF NETWORK ANALYSIS ON HEALTHCARE

Fei Wang, Uma Srinivasan, Shahadat Uddin, and Sanjay Chawla. “Application of network analysis on healthcare”. In Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on IEEE, 2014. The healthcare sector holds large amounts of semantically rich electronic data generated and used by different sections of the health care community. Data analytic

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TIKHONOV OR LASSO REGULARIZATION: WHICH IS BETTER AND WHEN. IN TOOLS WITH ARTIFICIAL INTELLIGENCE

Fei Wang, Sanjay Chawla, and Wei Liu. “Tikhonov or lasso regularization: Which is better and when. In Tools with Artificial Intelligence” (ICTAI), 2013 IEEE 25th International Conference on, pages 795–802. IEEE, 2013. It is well known that supervised learning problems with ℓ1 (Lasso) and ℓ2 (Tikhonov or Ridge) regularizers will result in very different solutions. For example,

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DATA SCIENCE AND THE POLICY COMPLETION PROBLEM

Sanjay Chawla, Federico Girosi, Fei Wang “Data Science and the Policy Completion Problem” The link between policy analysis and data science is more delicate than it may appear. A new policy, by definition, will change the underlying data generating model, rendering classification or supervised learning inapplicable. Perhaps eliciting causal relations from observational data is the

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MULTI-FUND DATA ANALYTICS TARGETS ENHANCED VALUE-FOR-MONEY IN HEALTHCARE SERVICES

Governments as well as health and accident compensation insurers are grappling to improve health outcomes while keeping spiraling costs under control. These seemingly irreconcilable goals require a careful balance of policy to help stem the tide of ever increasing costs in the health industry. Dr Uma Srinivasan CMC Insurance Solutions CMC Lead Scientist   Keywords: Health insurance,

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JOINT APPOSITION EXTRACTION WITH SYNTACTIC AND SEMANTIC CONSTRAINTS

A study by CMCRC researchers presents a fresh look at extracting apposition from large collections of news, web and broadcast text in order to turn unstructured news stories into “computable data”. News is about interactions between entities ‐ people, places and organisations ‐ and understanding stories requires interpreting the entities in them and their attributes.

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