Sökning: "machine learning corporate"

Visar resultat 1 - 5 av 35 uppsatser innehållade orden machine learning corporate.

1. 1. Modeling Credit Default Swap Spreads with Transformers : A Thesis in collaboration with Handelsbanken

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Johan Luhr; [2023]
   Nyckelord :Machine Learning; Transformer; Finance; Credit Default Swap; Credit Valuation Adjustment; Time Series Data; Maskininlärning; Transformer; Finance; Kreditswapp; Kredit Värderings Justering; Tidsserie data;

   Sammanfattning : In the aftermath of the credit crisis in 2007, the importance of Credit Valuation Adjustment (CVA) rose in the Over The Counter (OTC) derivative pricing process. One important part of the pricing process is to determine Probability of Defaults (PDs) of the counterparty in question. LÄS MER

3. 2. The Tale of Two Techniques - The comparative accuracy of machine learning and statistical techniques in predicting corporate bankruptcy for Swedish industrial firms

   D-uppsats, Handelshögskolan i Stockholm/Institutionen för redovisning och finansiering

   Författare :Edvin Lindhout; Hampus Ljunglöf; [2023]
   Nyckelord :Bankruptcy prediction; Machine learning; XGBoost; Probit analysis; Swedish firms;

   Sammanfattning : Bankruptcy prediction has long been an important area of study, yet the evolution of these predictive models in the context of modern machine learning techniques remains underexplored. Our thesis addresses this by comparing the effectiveness of probit analysis - a time-tested statistical approach - with XGBoost - a new-era machine learning technique - in predicting corporate bankruptcy among Swedish firms. LÄS MER

4. 3. Customer Acquisition Process Digitalization: A Case Study on the Use of Machine Learning in The Corporate Insurance Industry

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Klara Larsson; Freja Ling; [2023]
   Nyckelord :Customer Relationship Management CRM ; Customer Classification; Customer Acquisition; Machine Learning; Insurance Industry; Corporate Insurance; B2B; AI-CRM; Kundrelationssystem CRM ; Kunklassificering; Nykundsbearbetning; Maskininlärning; Försäkringsbranchen; Företagsförsäkring; B2B; AI-CRM;

   Sammanfattning : This thesis explores the application of machine learning 8ml9 techniques in customer classification and their intergration into customer relationship management (CRM) systems within the corporate insurance industry. The research aims to address the gap in the use of AI-CRM for the corporate insurance industry. LÄS MER

5. 4. Predicting corporate financial distress- A deep neural network approach

   Master-uppsats, Göteborgs universitet/Graduate School

   Författare :Adam Eklund; Petter Lundgren; [2022-06-29]
   Nyckelord :;

   Sammanfattning : Background. Predicting bankruptcy is of great importance for creditors, investors and other stakeholders. Early warning signs of financial distress allow stakeholders to take action to minimize the negative consequences of a bankruptcy. LÄS MER

7. 5. Federated Learning for Natural Language Processing using Transformers

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Gustav Kjellberg; [2022]
   Nyckelord :Machine Learning; Federated Learning; Distributed Machine Learning; Natural Language Processing; BERT; ALBERT; Transformers; Data Privacy.; Maskininlärning; Federerad inlärning; Distribuerad Maskininlärning; Språkteknologi; BERT; ALBERT; Transformers; Dataintegritet.;

   Sammanfattning : The use of Machine Learning (ML) in business has increased significantly over the past years. Creating high quality and robust models requires a lot of data, which is at times infeasible to obtain. As more people are becoming concerned about their data being misused, data privacy is increasingly strengthened. LÄS MER