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Data analytics emerges as a tool of paramount importance for anticipating and mitigating risks. By integrating emerging technologies and a proactive approach to risk management, Data Analytics in Risk Management (DARM) course ensures readiness for future challenges and opportunities in the dynamic business environment.
No pre-requisite. Suitable for everyone with and without prior technology experience.
Who Should Attend
Risk Management Professionals, Data Analysts, Data Scientists, Finance and Compliance Officers, Business and Strategy Leaders, Insurance and Actuarial Professionals, IT Professionals, Cyber Security Professionals, Auditors, Internal Control Specialists, Students, Graduates, and Anyone interested in Data Analytics in Risk Management.
Acquire essential knowledge of risk management in finance. Dive deep into identifying, assessing, and managing various financial risks, laying a solid foundation for advanced study in risk analytics.
Deep dive into Python programming, gain comprehensive knowledge of its syntax, data structures, and functions. Engage in in hands-on activities to solidify their understanding, empowering them to leverage Python for automation, data analysis, and more
In this module, Learners will have the opportunity to dive deep into Exploratory Data Analysis (EDA) and Visualization techniques tailored for finance. Gain comprehensive understanding on how to extract insights from financial data through visualization tools, enabling informed decision-making and risk assessment in the dynamic financial landscape.
Learn the advanced techniques for quantifying and assessing financial risks, utilizing mathematical models and statistical methods to forecast potential outcomes. Start making data-driven decisions and effectively manage risks in financial contexts.
Acquire first-hand experiences through extensive hands-on exercises and case studies on how to employ statistical models and analytics tools to assess creditworthiness and mitigate potential losses, enhancing their proficiency in credit risk management.
Address the critical aspect of maintaining sufficient liquidity in financial institutions. In this module, learners will learn to assess liquidity risk, develop strategies for managing liquidity positions, and navigate regulatory requirements effectively.
A comprehensive exploration of Machine Learning techniques tailored for Risk Management. Leverage Machine Learning for proactive risk mitigation and strategic decision-making in diverse industries.
This course involves extensive practical/hands-on exercises, rigorous usage of real-time case studies, role-playing and group discussion
Upon completion of the course, participants are required to attempt an examination. This exam tests a candidate’s knowledge and skills related to Digital Transformation, based on the syllabus covered.
Participants are expected to score a minimum of 70% to pass the examination
Add Value to your prolific portfolio a Certificate of Competency from CASUGOL.
All certificates issued by CASUGOL are to individuals who have successfully completed CASUGOL Certification Programs / Executive Workshops and have fulfilled all requirements by demonstrating proficiency in applying the knowledge and skills acquired.
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