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IS453

Financial Analytics

1 CreditsBoth

Description

Financial analytics helps to identify insights from vast amounts of data that financial institutions have to help them to answer specific business questions and to forecast possible future scenarios. Financial firms are investing significant sums in data analytics to facilitate market trading activities and to improve business processes that range from customer acquisition to fraud detection. With large amounts of data available and great potential value for providing competitive edge to businesses, the demand for analytics professionals is also increasing. Analytics professionals in the banks require a broad array of skills such as data management, analysis, statistics, and an understanding of the financial services domain.The module helps students understand how analytics techniques are applied in financial institutions. Through hands-on application of analytics techniques in financial services contexts, together with class discussion and labs, students will learn how business objectives and constraints can be supported by data analytics.

Requisites

Prerequisites: IS111/SMT111/CS105/COR-IS1704 - Pre-req

Co-requisites: None

Anti-requisites: None

Attributes

Department: SCIS

Course Level: Undergraduate

Tracks: IS/T4BS: Business Analytics Track IS/T4BS: Financial Technology Track

Areas: Accounting Data and Analytics Electives Accounting Electives Accounting Options Advanced Business Technology Major Business Options Business-Oriented Electives Econ Major Rel/Econ Options Finance Electives Financial Forensics Electives Grad Req - Dig Tech/Data Ana (Intake 2024 onwards) IS Depth Electives Social Sciences/PLE Major-related Business Core-Dig Skls in Biz(Intake 2025 onwards) IT Solution Development Electives

Learning Outcomes

1. Learn about the business contexts in financial services 2. Develop a basic understanding of statistical techniques and commonly used for analysis of financial markets, instruments, and risk management 3. Develop skills with Python to analyze financial services data 4. Build skills using common industry tools for data exploration and validation of ideas

Graduate Learning Outcomes

Disciplinary Knowledge, Innovation and enterprising skills, Collaboration and leadership, Communication

Competencies

Data Analytics, Business Innovation, Business Risk Management, Computational Modelling, Data Visualisation