Εφαρμογή στατιστικών μεθοδολογιών και αλγορίθμων μηχανικής μάθησης για την βελτίωση του εξωδικαστικού μηχανισμού ρύθμισης ληξιπρόθεσμων οφειλών
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Keywords
Out-of-court mechanism for the settlement of overdue debts ; Statistics ; Machine learning algorithms ; Instalments ; DebtAbstract
This thesis provides an extensive review of the existing out-of-court mechanism for the settlement of overdue debts, highlighting the points of the current framework for calculating instalments and the total amount of the settlement. In the next step, an innovative model for calculating the amount of each instalment, the total amount and the number of instalments is proposed, which takes into
account the financial characteristics of the debtor and proposes a specific amount of discount from the original debt. Finally, a new algorithm based on known machine learning methodologies is introduced which can be used to recalculate the amount of each instalment, the total amount in case of default by the debtor. In this case, in real time and, when it detects signs of weakness to
pay the debt, it automatically recalculates the instalment, the total balance and the duration of the arrangement, thus ensuring the flexibility and viability of the arrangement for the debtor.
Department
Σχολή Οικονομικών, Επιχειρηματικών και Διεθνών Σπουδών. Τμήμα Οργάνωσης και Διοίκησης ΕπιχειρήσεωνNumber of pages
130Language
GreekCollections
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Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα