Advanced/AI-supported Rating Models for P2P systems
Beschreibung
Our innovative idea is to provide a Proof of Concept concerning a superior and adaptive rating system applicable to both SME and personal lending, able to cope with low-quality, sparse data that is commonplace in the context of P2P lenders. If successful, we will have both a new methodology (how to deal with low-quality, sparse data in the context of credit risk) as well as a new product that will complement our existing business.We further intend to use our unique and comprehensive loan data to provide transparency for other market participants and the financial regulators. We will achieve this by providing insights on default and migration probabilities similar to what rating agencies (Standard&Poors, Moodys) do for traditional credit markets. An enhanced methodology will lead to a sophisticated rating system on the level of the loan originator as well as on the level of the borrower.
Eckdaten
Projektleitung
Dr. Branka Hadji Misheva
Co-Projektleitung
Prof. Dr. Jörg Osterrieder, Prof. Dr. Jan-Alexander Posth, Prof. Dr. Christoph Schmidhuber
Projektteam
, Florian Bozhdaraj
Projektpartner
i2 operations GmbH
Projektstatus
abgeschlossen, 07/2020 - 06/2021
Institut/Zentrum
Institut für Datenanalyse und Prozessdesign (IDP); Institut für Wealth and Asset Management (IWA)
Drittmittelgeber
Innovationsscheck / Projekt Nr. 44596.1 INNO-SBM