ADD ON COURSE

Certified Personal Financial Specialist^®,CPFS^®

The Certified Personal Finance Specialist (CPFS^®) Certificate Program is designed to equip students with the basic skills required by a management professional to execute critical functions related to Financial Planning, Goal Planning & Investment Planning and to assist their clients to shift from investment planning to comprehensive financial planning. The program provides financial goal planning skills to students aspiring for a career in the financial services industry.

ADD ON COURSE

POWER BI Training

This fifteen day workshop is to coach the students to use Power BI , which is a self service tool, to transform, relate, analyze, and visualize business data from wide variety of sources. This will help students gain insights from business data through some impactful, interactive, and compelling visuals which otherwise is an overload of information. Students will get a hands-on experience on how companies use Power BI.

ADD ON COURSE

Systems, Applications & Products in Data Processing (SAP)

The SAP training program will equip students with SAP Business Suite (R3) knowledge. This will help them in their career in over 25 industry verticals which are run by SAP. The students will receive global certification in SAP which would enable them to have an edge over non-certified candidates to seek jobs in Information Technology field.

ADD ON COURSE

 International Financial Reporting Standards (IFRS)

International Financial Reporting Standards (IFRS), are accounting standards issued by the IFRS Foundation and the International Accounting Standards Board (IASB). This 30 hours course is designed to help students develop knowledge and understanding of the concepts and principles of the Conceptual Framework for Financial Reporting. Additionally, it also helps them to identify and apply disclosure requirements in financial reports.

ADD ON COURSE

Business Analytics Workshop

The current demand for qualified data professionals and the number of job postings related to analytics in portals are increasing substantially. The course helps the participant to understand and apply analytics in the business context. The course is specially designed for management students who are interested in data analytics techniques which would help them derive insights from data using data exploration and modelling techniques.

ADD ON COURSE

MS Excel

The department offers a five-day Microsoft Certified Instructor Led Training (MCILT) programs to provide application-oriented classes on MS Excel. The objective of the programme is to offer classroom training with intensive hands-on instructional workshops. The course helps the students to design and manage spreadsheets; apply best practices; analyze large amounts of data with pivot tables and pivot charts; generate and customize charts. The sessions are conducted in the computer labs at the college. The course is offered to all the students irrespective of their specializations.

ADD ON COURSE

Data Analytics Using IBM SPSS

The department offers a five-day training programme on IBM SPSS to provide an application-oriented introduction to the statistical component of IBM SPSS Statistics. The objective of this training is to review several statistical techniques and discuss situations in which the students would use each technique, how to set up the analysis, as well as how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. At the end of the training, students should gain an understanding of when and why to use these various techniques as well as how to apply them with confidence, interpret their output, and graphically display the results.

ADD ON COURSE 

INTRODUCTION TO HR ANALYTICS 

Modern organizations are ramping up on data science, recruiting talents by making huge  investments for their work engagement. These firms are accelerating their digital transformation to  deploy smart technologies around AI and big data to improve their talent management systems. In a  world of work that is increasingly virtual (and perhaps even only virtual), the volume of data  available to understand and predict employees’ behaviours will continue to grow exponentially,  enabling more opportunities for managing through HR Analytics. As such, people analytics is a  deliberate and systematic attempt to make organizations more evidence-based, talent-centric, and  meritocratic, which, one would hope, should make them more effective. 

Course Objective: 

∙ Understand how HR and analytics have evolved and are transforming people management  

around the world. 

∙ Understand the role of HR Analytics and build skills to conduct a HR Analysis through  

measuring staffing utility. 

Course Outcomes: 

At the end of the course, the student will be able to 

CO1: Describe the role of descriptive and prescriptive analytics in HR analytics. 

CO2: Explain the recent developments in decision based framework for staffing measurement. 

CO3: Analyse the different utility models for taking staffing decisions. 

CO-PO Mapping 

Course Delivery Methods

Eligibility 

Student should score 50% (30 Marks) & 80% attendance to be eligible for the certification Syllabus: (Total Hours Required – 30) 

Module 1: HR Analytics: Analytics-Nature-Evolution of Human Capital Metrics-Steps in Analytics Role of Descriptive analytics & Prescriptive analytics in HR analytics – HR Analytics Frameworks:  LAMP framework, HCM: 21 Framework& Talent ship Framework, Environmental scanning: The Big  Picture-The value of statistical analysis-The importance of risk assessment, Predictive management  

Module 2: Staffing Utility : Concept and Measures A Decision-Based Framework for Staffing  Measurement, Overview: The Logic of Utility Analysis, Utility Models and Staffing Decisions, The  Taylor-Russell Model, The Naylor-Shine Model, The Brogden- Cronbach- Gleser Model 

Module 3: Absenteeism and Separation: Cost of Absenteeism – Direct Costs and the Incidence,  Causes, Consequences, Categories of Costs, Analytics and Measures for Employee Absenteeism,  Strategies to reduce absence, positive Incentives, Paid Time Off (PTO) 

Module 4: Employee Turnover: Separations, Acquisitions, Cost, and Inventory, Voluntary Versus  Involuntary Turnover, Functional Versus Dysfunctional Turnover, Pivotal Talent Pools with High Rates  of Voluntary Turnover, Involuntary Turnover due to Dismissals and Layoffs, computing Turnover 15  rates, training cost, performance difference between separating employees and replacements, cost  of lost productivity and lost business ,Promotion and succession planning analytics, Compliance  analytics 

Module 5: Employee Health Wellness and Welfare: Logic of Workplace Health Programs (WHP),  Analytics for Decisions about WHP Programs, Measures: Cost Effectiveness, Cost-Benefit, and  Return-on-Investment Analysis, Cost-Effectiveness Analysis, Cost Benefit and Return-on Investment Analysis, Employee Assistance Programs (EAPs) Future of Lifestyle Modification, WHP,  and EAPs 

References 

1. Wayne F. Cascio, John W. Boudreau, Investing in people: Financial Impact of Human Resource  Initiatives, Pearson Education, New Jersey, US  
2. Tracey Smith, HR Analytics, The what, Why and How, 1e Create Space Independent Publishing  Platform  
3. Laurie Bassie, Rob Carpenter: HR Analytics Handbook, Mc Bassi & Company; 1st paperback  edition, Brooklyn ,US  
4. Jac Fitz-Enz, The New HR Analytics: Predicting Economic Value of Your Company’s Human Capital  Investments. New York, NY: AMACOM.

ADD ON COURSE 

Introduction to Fintech

Resource Persons:

Dr Dhanya Alex* (dhanyaalex@fisat.ac.in)

Ms.Sangeeta G** (sangeetasg9@gmail.com)

Ms. Rohini S***(rohinisoman@gmail.com)

Introduction: 

The emerging technologies, paired with massive changes in regulations, have driven an  unprecedented transformation of finance around the world. This course is designed to explore FinTech  fundamentals and help make sense of this wave of change as it happens. 

Course Objectives: 

• Understand how finance and technology have evolved and are transforming finance around  the world 
• Discuss major technological trends, including cryptocurrencies, Blockchain, AI and Big Data Course Outcomes: 

At the end of the course, the student will be able to  

CO 1: Describe how Artificial Intelligence, Big Data, Crypto currencies and Block chain is changing the  Financial World. 

CO 2: Explain the recent developments in digital financial services. 

Co 3: Analyse the progress of FinTech Regulations. 

CO – PO Mapping: 

Course Delivery Methods:

Assessment Tools: 

Quiz (5 numbers – 50 marks) Assignment (1 number – 10 marks) Total 60 marks Eligibility: 

Student should score 50% (30 marks) & 80% attendance to be eligible for the certification. Syllabus: (Total Hours Required – 30) 

Module 1: FinTech: Introduction– FinTech Evolution: Infrastructure, Collaboration between Financial  Institutions and Start-ups –FinTech Typology – Emerging Economics: Opportunities and Challenges – Introduction to Regulation Industry (6 Hours) 

Module II: Payments, Crypto currencies and Blockchain – Introduction – Individual Payments –Digital  Financial Services – Mobile Money – Regulation of Mobile Money – SFMS – RTGS – NEFT –NDS Systems  – Crypto currencies – Legal and Regulatory Implications of Crypto currencies –Blockchain – The  Benefits from New Payment Stacks (6 Hours) 

Module III: Digital Finance and Alternative Finance -Introduction – Brief History of Financial Innovation  – Digitization of Financial Services – FinTech & Funds- Crowd funding– Regards, Charity and Equity – P2P and Marketplace Lending – New Models and New Products – ICO (6 Hours) 

Module IV: FinTech Regulation and RegTech -Introduction – FinTech Regulations Evolution of RegTech  – RegTech Ecosystem: Financial Institutions – RegTech Ecosystem Ensuring Compliance from the Start:  Suitability and Funds – RegTech Startups: Challenges –RegTech Ecosystem: Regulators Industry –Use  Redesigning Better Financial Infrastructure (6 Hours) 

Module V: Data & Tech – Introduction– Data in Financial Services –Application of Data Analytics in  Finance – Methods of Data Protection – How AI is Transforming the Future of FinTech –Digital Identity  – Change in mindset: Regulation 1.0 to 2.0 (KYC to KYD) – AI & Governance – New Challenges of AI and  Machine Learning – Challenges of Data Regulation (6 Hours) 

References: 

• Susanne Chishti and Janos Barberis, “The FINTECH Book: The Financial Technology Handbook  for Investors, Entrepreneurs and Visionaries”, John Wiley, 1st Edition, 2016 
• Theo Lynn, John G. Mooney, Pierangelo Rosati, Mark Cummins, “Disrupting Finance: FinTech  and Strategy in the 21st Century”, Palgrave, 1st edition, 2018 
• Abdul Rafay, “FinTech as a Disruptive Technology for Financial Institutions”, IGI Global,  January, 2019 

* Dr. Dhanya Alex, Associate Professor, FISAT Business School 

** Sangeeta G, US Tax Associate, KPMG Global Services 

*** Rohini S, US Tax Associate 2, Big Four

ADD ON COURSE (2021-22) 

 Customer Analytics 

Course Facilitator: Dr. Jose Varghese 

(josevarghese@fisat.ac.in) 

Introduction: 

Customer analytics is a process by which data from customer behavior is used to help make  key business decisions via market segmentation and predictive analytics. This information is  used by businesses for direct marketing, site selection, and customer relationship management. 

Course Objectives: 

• Create a single, accurate view of a customer to make decisions about how best to

acquire and retain customers. 

• Gather deeper understandings of customers’ buying habits and lifestyle preferences

Course Outcomes: 

At the end of the course, the student will be able to:- 

CO 1: Acquire knowledge related to the various terminologies and techniques associated  with customer analytics 

 CO 2: understand the segmentation process 

 CO 3: Analyze how the markets prices are determined 

CO – PO Mapping: 

Course Delivery Methods:

Eligibility: 

Student should score 50% (30 marks) & 80% attendance to be eligible for the certification. 

Syllabus: (Total Hours Required – 30) 

Module 1- Marketing Management Process and Customer Analytics 

The Marketing Management Process and its link to Customer Analytics and Customer Insights – Correlation – Simple linear regression – Trend – seasonality- Exponential smoothing 

Module 2 – Pricing 

Non-linear pricing strategies for profit maximization – price skimming and sales – optimal pricing – price bundling – demand curve and the willingness to pay 

Module – 3 – Customer Insights 

Conjoint analysis – product attributes and levels – full profile conjoint analysis – choice based conjoint  analysis – random utility theory 

Module 4 – Customer value 

Lifetime customer value, – relation between spending, customer acquisition and customer retention – Market basket analysis – RFM analysis 

Module 5 – Market Segmentation 

Cluster analysis – collaborative filtering – classification trees for segmentation – Application of  Customer Analytics in Advertising, Retailing and Internet & Social Marketing 

References: 

1. Winston, Wayne L. (2014), Marketing Analytics: Data-Driven Techniques with Microsoft Excel, 1st  ed. Wiley. 
2. Winston, Wayne L. (2014), Marketing Analytics: Data-Driven Techniques with Microsoft Excel, 1st  ed. Wiley. 
3. Malhotra, Naresh (2015), Marketing Research – An Applied Orientation, 7th ed., Pearson  EducationVandana Ahuja. Digital Marketing. Oxford University Press India, 2015 
4. Damian Ryan. Understanding Digital Marketing: Marketing Strategies for Engaging the Digital  Generation (3rd Edition). Kogan Page Publishers, 2014.