HEAD
Big data
For the Big Data analytics we have created 3 Use Cases.
Find more about each of them bellow! For each use case you can:
Check the main details here
  • go into details by reading the support peer-reviewed research paper
  • download the code and run it again with your own data

  •       get in contact with the creator of the use case
Use case 1 

Use Case 1 Big Data Analytics – Network based scoring models to improve credit risk management in peer to peer (P2P) lending platforms (Authors: Paolo Giudici, Branka Hadji-Misheva, Alessandro Spelta)

Use case 2 

Use Case 2 Big Data Analytics - Factorial network models to Improve peer to peer (P2P) Credit risk management (Authors: Daniel Felix Ahelegbey, Paolo Giudici, Branka Hadji-Misheva)

Use case 3 

Use Case 3 Big Data Analytics – Spatial regression models to improve peer to peer (P2P) credit risk management (Authors: Arianna Agosto, Paolo Giudici, Tom Leach) 

The 3 used cases were presented all across Europe in mode than 30 events.
Big data analytics research events more
Big data analytics regtech events more
Big data analytics suptech events more
For enriching the field, we have also produced significant research and the main 11 research
papers produced on the topic are:
Check out the feedback we have collected during our events!
Check out more details about the use cases here!
Network Based Scoring Models to Improve Credit Risk Management in Peer to Peer Lending Platforms

Authors: Paolo Giudici, Branka Hadji-Misheva, Alessandro Spelta

Key words: network based scoring models, credit risk management, peer to peer lending

Spatial Regression Models to Improve P2P Credit Risk Management

Authors: Arianna Agosto, Paolo Giudici, Tom Leach

Key words: spatial regression models, peer to peer, credit risk management

Fintech Risk Management: A Research Challenge for Artificial Intelligence in Finance

Authors: Paolo Giudici

Key words: fintech risk management, artificial intelligence, finance

Will they repay their debt? Identification of borrowers likely to be charged off

Authors: Caplescu, RD., Panaite, AM., Pele, DT, Strat, VA.

Key words: peer-to-peer lending, creditworthiness, Logistic Regression, KNN, LightGBM

Fin vs. tech: are trust and knowledge creation key ingredients in fintech start-up emergence and financing?

Authors: Theodor Florian Cojoianu, Gordon L. Clark, Andreas G. F. Hoepner, Vladimir Pažitka, Dariusz Wójcik

Key words: trust and knowledge, fintech, start-up

Peer-to-peer loan acceptance and default prediction with artificial intelligence

Authors: J. D. Turiel, T. Aste

Key words: peer-to-peer, loan acceptance, default prediction, artificial intelligence

On the Improvement of Default Forecast Through Textual Analysis

Authors: Paola Cerchiello, Roberta Scaramozzino

Key words: default forecast, textual analysis, credit worthiness

Latent factor models for credit scoring in P2P systems

Authors: Daniel Felix Ahelegbey, Paolo Giudici, Branka Hadji-Misheva

Key words: credit risk, factor models, financial technology, peer-to-peer, scoring models, spatial clustering

Default count-based network models for credit contagion

Authors: Arianna Agosto, Daniel Felix Ahelegbey

Key words: financial networks, inter-sector contagion, poisson autoregressive models, vector autoregressive models, conditional Granger causality


Comparing Performance of Machine Learning Algorithms for Default Risk Prediction in Peer to Peer Lending

Authors: Yanka Aleksandrova

Key words: machine learning, peer to peer lending, credit scoring, ensemble classifiers, XGBoos

 

Risk-return modelling in the p2p lending market: Trends, gaps, recommendations and future directions

Authors: Miller-Janny Ariza-Garzón, María-Del-Mar Camacho-Miñano, María-Jesús Segovia-Vargas, Javier Arroyo

Key words: risk management modeling, credit risk modeling, profit and investment modeling, P2P lending, machine learning