Topic: Recommender Systems for Mass Customization of Financial Advice
18:30 Welcome and introduction into the subject
18:45 - 19:30 Presentation:
- Introduction and business context (10 min by Anna Nowakowska)
- Retail Banking use case (15 min by Milica Petrovic)
- Private Banking use case (15 min by Aleksandra Chirkina)
19:30 - 20:30 Apéro & Networking
Recommender systems suggest new items to users based on their characteristics and previous behavior. Despite the support that they can bring to financial decision making, their application to banking data is an underexplored field. We build recommenders for private and retail banking use cases. The vision is to enhance the quality of financial advice and make it accessible to a wider client base. In the retail banking use case, where clients typically hold few products, we obtained the most promising results with Demographic Recommender Systems using client features. In the private banking use case, where clients typically invest in multiple securities, we found the Collaborative Filtering approach, based on user-product interactions, to be particularly suitable.
Anna Nowakowska --- Anna leads the Data Science team at InCube, focusing on delivering data consulting services within the Swiss financial sector. She holds a MEng degree in Electronics and Electrical Engineering from the University of Edinburgh and the Chartered Financial Analyst® designation from the CFA Institute. She has over 8 years of professional experience in applying data analytics in the telecom, retail and financial industries.
Aleksandra Chirkina --- Aleksandra is a Data Scientist at InCube working on designing and implementing machine learning solutions in the financial industry. She holds an MS degree in Computational Science from UvA (University of Amsterdam) and an MS degree in Statistics from the ETH. She has 2 years of experience in applying data analytics and numerical optimization in industry.
Milica Petrovic --- Milica is a Data Scientist at InCube, working on data analytics and AI projects from design to implementation. She holds an MS degree in Statistics from the ETH. She has one year of professional experience applying data modeling and AI in the financial industry.