Data mining methodology and application in debt collection industries
Authors
Date
2017Access restrictions
This material has a restricted access due to copyright reasons. It can be read at the workstation at Jyväskylä University Library reserved for the use of archival materials: https://kirjasto.jyu.fi/en/workspaces/facilities.
Collecting debt bills from different types of organizations and people is always a
challenging task. And for that as a debt collector company you need to have a very smart way
to collect money. There has been not been too many research done on analysis of debtor
behavior to get some generalized information in Finland. As a result, most organizations have
to have their own analytics team to set proper business strategy for any debt. We get lots of
classified data from different sources regarding debtor’s basic information, detail debt
information, payment information and many other information. From thousands of variables,
we find out the important variables and build a model. Later data is analyzed with these
models and each case is given a rating value, by which business decisions can be made. And
time to time the cash flow and other business factor is monitored to evaluate the performance
of that model. To conclude, proper and accurate analysis is important before taking any
business decision.
...
Keywords
Metadata
Show full item recordCollections
- Pro gradu -tutkielmat [29561]
Related items
Showing items with similar title or keywords.
-
Unstable feature relevance in classification tasks
Skrypnyk, Iryna (University of Jyväskylä, 2011) -
Bankruptcies and bankruptcies of an estate in the town of Vaasa, 1817 - 1900.
Turunen, Riina (2022)Aineisto sisältää tietoa Vaasan raastuvanoikeudessa käsitellyistä konkursseista ja perinnönluovutuksista vuosina 1817 - 1900. Sisältyvät tiedot: Nimi, ammatti, sukupuoli, konkurssin aloittaja, omaisuudenluovutuksen ... -
Database: Bankruptcies and surrenders of an estate to creditors in Finnish cities 1810 - 1900 in every 10 years
Turunen, Riina (2022)The data contains information on bankruptcies and the surrenders of an estate to creditors in Finnish cities from 1810 to 1900. The data includes information on ten-year cross sections (1810, 1820, 1830, 1840, 1850, 1860, ... -
Potential of predictive modeling methods for individual response : applications and guidelines for sports sciences
Jauhiainen, Susanne (Jyväskylän yliopisto, 2023)The amount of data and consequently machine learning (ML) approaches are increasing at a fast pace in sports sciences, opening many new possibilities but on the other hand, also challenges. Generally limited data together ... -
Complementary methods assessing short and long-term prey of a marine top predator : Application to the grey seal-fishery conflict in the Baltic Sea
Tverin, Malin; Esparza-Salas, Rodrigo; Strömberg, Annika; Tang, Patrik; Kokkonen, Iiris; Herrero, Annika; Kauhala, Kaarina; Karlsson, Olle; Tiilikainen, Raisa; Vetemaa, Markus; Sinisalo, Tuula; Käkelä, Reijo; Lundström, Karl (Public Library of Science, 2019)The growing grey seal (Halichoerus grypus) population in the Baltic Sea has created conflicts with local fisheries, comparable to similar emerging problems worldwide. Adequate information on the foraging habits is a ...