POLIMI Graduate School of Management courses

This module deals with fintech & insurtech, digital innovation and new business models in banking and insurance sectors, sypply chain finance, digital payments, “open banking” strategies, digital banking, insurance processes and asset management, and topics such as Data/API, Blockchain and Cloud. Note: This module is held in common between the International Master in Fintech and the International Master in Financial Risk Management.

Innovative business and startup planning represent the core of this module. The course covers models of adoption of new technologies, the business model canvas and the lean startup approach. Finally, the course deals with business model patterns, corporate entrepreneurship and driving innovation.

The module covers the basics of blockchain technology and performs a case analysis of Bitcoin and Ethereum. It introduces the languages for drafting smart contracts, paying particular attention to Solidity. The module further deals with patterns in the development of distributed applications (Dapp), an evaluation of accuracy in smart contracts and references to zero-knowledge proof.

This module explores crowdinvesting: equity crowdfunding, marketplace, social lending and invoice trading. It includes innovations in payment systems and cryptocurrencies, initial coin offerings and the economics of peer-to-peer platforms. Moreover, the module covers subjects as digital asset and tokenization, and the application in finance of token & smart contracts.

The aim of the course is to understand societal, economic, and technological trends in Fintech, digital innovation in the finance industry by looking at applications/experiences provided by traditional intermediaries and fintech startups. This module deals with customers and digital innovation. It includes financial education, behavioural finance in the banking and insurance world, digital marketing, and customer protection and regulation.

This module features machine learning methods, supervised/ unsupervised learning, reinforcement learning and control, natural language process tools. It provides the competencies to manage these methods correctly.

Two main topics related to digital transformation will be covered in this course: usage of API to exploit the potentialities of open data and data scraping and visualization as to render data in order to build enriched web applications. The module examines information retrieval: application programming interfaces, elements of web scraping and web design for financial tools.

The course aims to apply artificial intelligence, big data, machine learning techniques methods to the finance industry evaluating their potentialities and challenges for the business activity. This module covers the use of big data, natural language processing and machine learning methodologies in finance: sentiment analysis, nowcasting, network analysis, systemic risk, algo trading, credit risk, customer behavior, and option pricing.