automation

Basel, the Big Picture: Tackling Risk Aggregation & Reporting. Part 2

“What [should we] look for in a risk aggregation solution?” asked Renzo Traversini, Director of Europe, the Middle East and Africa & Asia-Pacific, Risk Management Center of Excellence at SAS. He was the second of two speakers at a GARP-sponsored webinar to discuss the recently released Basel paper, Principles for Effective Aggregation and Reporting of Risk Data. Traversini focussed on the “nuts and bolts” of how to aggregate and report risk data. SAS is one of the major suppliers of information technology (IT) solutions in financial risk management. Timeliness is crucial to a good reporting system. Traversini began by showing […]

Credit Workflow Optimization: A Practical Approach

“How can an institution practically approach credit workflow when it might not be streamlined? How can we optimize existing processes?” These questions were posed by Justin Huhn, Credit Assessment & Origination Practice Leader at Moody’s Analytics Enterprise during a webinar arranged by the Global Association of Risk Professionals on September 24, 2013. Huhn noted that, as of Q1 2013, there were over seven thousand insured commercial banks and savings institutions in the US excluding foreign branches. These financial institutions tend to develop silos of expertise.  Workflow optimization is of pressing concern to many. In 2008 the American Bankers Association estimated […]

Risk Data Aggregation & Risk Reporting. Part 2

“Not everything that can be counted counts,” said Mike Donovan, VP, Strategic Risk Analytics & Credit Portfolio Management at Canadian Imperial Bank of Commerce (CIBC). He was the second speaker to address the September 19, 2013 evening meeting of the Toronto chapter of GARP regarding the set of Principles for Effective Risk Data Aggregation & Risk Reporting released by the Basel Committee in January 2013. CIBC, like other Canadian banks, is adapting to the heightened risk management data requirements and building the foundation for future sustainable growth. Donovan used the opening quote by Einstein to remind the audience that big […]

Risk Data Aggregation & Risk Reporting. Part 1

During the throes of the last financial crisis, banks and regulators alike “struggled” to get good quality information. “The infrastructure was not there,” said James Dennison, CFA, Managing Director, Operational Risk Division, Office of the Superintendent of Financial Institutions (OSFI). To enhance banks’ risk management infrastructure, the Basel Committee on Banking Supervision (BCBS) released a set of Principles for Effective Risk Data Aggregation & Risk Reporting in January 2013. Dennison was first to speak on the evening of September 19, 2013 at the Toronto chapter meeting of the Global Association of Risk Professionals (GARP). It was convened at First Canadian Place to allow […]

MATLAB for Excel Users: “Discoverability”

When looking for good data analysis tools, many financial professionals turn first to MS Excel which displays numeric data, contains advanced functions, and can be programmed with Visual Basic. A growing number of professionals are turning to MATLAB which has strengths complementary to ordinary spreadsheets. At a webinar on January 15, 2013, Adam Filion, application engineer at MathWorks, showed approximately three hundred audience members how easily features of MATLAB software adapt themselves to rapid analysis of large datasets. In Excel functions, the input is specified as a cell location and the math is hidden. In MATLAB, the interface has a […]

Automated Trading with MATLAB

Stuart Kozola, product manager for computational finance at MathWorks, demonstrated examples of trading systems using MATLAB during a webinar on August 21, 2012.  In the first half he discussed how to develop an automated trading decision engine.  This meant identifying a successful trading rule, extending the trading rule set, and automating the trading rule selection.  In the second half of the webinar he showed implementation of the automated trading, with a caveat that these would require testing prior to integration and execution in the real-life scenario. The worked problem involved Brent oil futures.  The first challenge was to identify profitable […]