Montréal: Convergent Quantitative Cyber Risk Assessment to Optimize Mining Enterprise Reliability

June 21, 2018 all-day
McGill University
Room 105
FDA Building, 3450 University Street, Montréal
H3A 0E8

En français


McGill COSMO, CIM Montréal, in collaboration with CIM MES Montréal, are pleased to present:

Dr. Franco Oboni

Lead Management Consultant, Riskope


who will deliver a presentation on:

Convergent Quantitative Cyber Risk Assessment to Optimize Mining Enterprise Reliability


Cyber risks in mining companies are a reality like those generated by storms, quakes and equipment failures. The deployment of an adequate siloes-busting convergent risk analysis methodology eliminates capex squandering and increases overall enterprise reliability. Mitigative benefits are maximized within sustainable and reasonable investments.



Franco co-authored “Improving Sustainability through Reasonable Risk and Crisis Management” (2007) and serves Global 1000 companies, mining, insurances, and railroads. His studies support arduous decisions shading light and conveying pertinent information to decision-makers. He teaches MBA risk management modules.


Thursday, June 21, 2018
12:15pm – 1:45pm

Refreshments will be served



Registration: 12h15PM
Presentation: 12h30PM
Closing Remarks: 1h40PM


McGill University

Room 105, FDA Building, 3450 University Street, Montréal


Adams Building, 3450 University Street (third building on the left as you head North on University Street, between Milton and Sherbrooke), Room 105, Montréal, Québec H3A 0E8


The seminar is complimentary and seats are limited. Register by Monday, June 18, at 12noon to secure your place. Please RSVP to Lise Chartrand, Secretary, CIM Montreal Branch at or Tel. (514) 425-5553 if you are interested in attending. This is an excellent networking opportunity and there is no charge to attend. So we can best service all who are interested and able to join us at this upcoming event please register for it if you are confident that you are indeed able to attend it. Thank you for your interest and understanding.



Thank you to our sponsor, McGill University’s COSMO (Stochastic Mine Planning Laboratory), for providing the space!


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