Essays about: "Credit risk management"

Showing result 31 - 35 of 105 essays containing the words Credit risk management.

  1. 31. User interface suitable for credit risk management

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Xiao He; [2019]
    Keywords : user interface; user experience; usability; data visualization; GUI; front-end development; credit risk assessment; användargränssnitt; användarupplevelse; användbarhet; datavisualisering; GUI; front-end-utveckling; kreditriskbedömning;

    Abstract : Graphical User Interface, which is known as GUI, is a way for a person to communicate and interact with a system through icons or other visual indicators. A well designed and intuitive user interface is critical to the success of a system since it encourages a natural interaction between a user and a system, thus conveying information more clearly and efficiently to the user. READ MORE

  3. 32. Asset-Backed Securitization of Chinese PPP Projects : Operating Mechanism and Current Difficulties

    University essay from KTH/Fastigheter och byggande

    Author : Xiaokuan Li; [2019]
    Keywords : Asset Securitization; PPP Asset Securitization; Risk Segregation; Credit Enhancement; legal practice; Asset Securitization; PPP Asset Securitization; Risk Segregation; Kreditförbättring; juridisk praxis;

    Abstract : Under the background that China's economy has entered the new normal, de-leveraging, structural adjustment, and resolution of various risks have become an essential part of macro-control. The unique advantages of PPP asset securitization make this tool widely recognized and respected by the government, enterprises, and investors. READ MORE

  4. 33. Comparison of Machine Learning Techniques when Estimating Probability of Impairment : Estimating Probability of Impairment through Identification of Defaulting Customers one year Ahead of Time

    University essay from Umeå universitet/Institutionen för matematik och matematisk statistik

    Author : Alexander Eriksson; Jacob Långström; [2019]
    Keywords : Classification; Imbalanced Data; Machine Learning; Probability of Impairment; Risk Management; Klassificering; Obalanserat Data; Maskininlärning; Probability of Impairment; Riskhantering;

    Abstract : Probability of Impairment, or Probability of Default, is the ratio of how many customers within a segment are expected to not fulfil their debt obligations and instead go into Default. This is a key metric within banking to estimate the level of credit risk, where the current standard is to estimate Probability of Impairment using Linear Regression. READ MORE

  5. 34. Government yield spread determinants in the eurozone and the effect of the European debt crisis

    University essay from KTH/Skolan för industriell teknik och management (ITM)

    Author : Arian Kalantari; [2019]
    Keywords : Government bonds; yield spread; eurozone; European debt crisis; risk; Statsobligationer; räntor; spread; euroområdet; risk; skuldkrisen;

    Abstract : The inception of the economic and monetary union (EMU) in January 1999 created new conditions for government debt. By eliminating currency exchange rate risk between the member states, the hope was to achieve a more sustainable and integrated government debt market in the euro area. READ MORE

  6. 35. The Effects of Corporate Social Performance (CSP) on Credit Ratings - Evidence from the European Market

    University essay from Lunds universitet/Företagsekonomiska institutionen

    Author : Gustav Johannesson; Oscar Zedendahl; [2019]
    Keywords : Corporate Social Responsibility CSR ; Corporate Social Performance CSP ; ESG Factors; Credit Ratings; European Rating Market; Business and Economics;

    Abstract : Purpose: The purpose of this thesis is to fill the existing research gap in Europe by examining the effect of corporate social performance (CSP) on firms’ credit ratings. Methodology: Through a quantitative research strategy, we examine the relationship between CSP and firms’ credit rating using a fixed effects regressions analysis based on a panel data set. READ MORE