AI Applications in Marketing and Finance

University of Pennsylvania via Coursera

Coursera based on 390 ratings

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Overview

In this course, you will learn about AI-powered applications that can enhance the customer journey and extend the customer lifecycle. You will learn how this AI-powered data can enable you to analyze consumer habits and maximize their potential to target your marketing to the right people. You will also learn about fraud, credit risks, and how AI applications can also you combat the ever-challenging landscape of protecting consumer data. You will also learn methods to utilize supervised and unsupervised machine...

Syllabus

Module 1 AI and the Customer Journey

In this module, you will delve into the impact of AI in marketing, and how it affects how your customers interact with your organization and its offerings. You will learn about how AI is disrupting retail and transforming the way that we conduct business in the digital age. You will next discover the risks and challenges that you might encounter when trying to implement AI, such as privacy issues, and how to make the journey from interest to purchase a much shorter one. By the end of this module, you will have a firm understanding of how AI influences and also impact customer behavior, and how you can take advantage of the myriad of ways AI can be applied to support your business and align with your customers.

Module 2 Personalization

In this module, you will discover different ways that AI can be applied to enhance the consumer experience. You will take a deep dive into the realm of personalization algorithms, and how they are utilized in companies such as Pandora, Netflix, and Amazon. Next, you will learn about the challenges that you can face when trying to implement these algorithms or recommendation systems. You will also hear from Barkha Saxena, Chief Data Office for Poshmark, and how she takes data provided by their over 80 million users to create a curated experience, but still allow their customers to discover new products and engage with buyers. By the end of this module, you would have gained valuable insight into how AI can enable personalization and in turn drive customer engagement and retention.

Module 3 Finance

In this module, you will learn how to mitigate fraud using AI systems. By examining various machine learning methods, you will discover different ways to analyze risk assessment using KPIs and the scientific method. You will then learn about corporate credit and the relationship between money borrowed, the price and availability of credit, as well corporate credit ratings and why and how that rating translates to risk. Lastly, you will learn about using models versus real-world data, and how you can use AI to conduct error analysis to prevent costly miscalculations. By the end of this module, you will have a firm knowledge of different risk assessment methods, how data can be used to analyze and predict credit ratings, as well as the benefits and limitations of different applications used in the industry.

Module 4 Additional AI Applications in Finance

In this module, you will hear from executives Carleigh Jaques, In this module, you will hear from executives Carleigh Jaques, SVP of CyberSource at Visa, and Apoorv Saxena, formerly the head of Googles AI Verticals Team and was until recently the Global Head of AI at JPMorgan Chase. These interviews will allow you to get valuable insight into how major global brands utilize AI to create a secure shopping environment for their customers and clients, and how AI is instrumental in the data-driven world of finance. By the end of this module, you will have heard from top industry experts in their field and gained firsthand accounts of risk management and assessment and how AI is playing a more integral role in combating digital fraud.