Sökning: "Expected credit loss"

Visar resultat 1 - 5 av 32 uppsatser innehållade orden Expected credit loss.

1. 1. Svenska Bankers Prognosutveckling för Kreditförluster under Införandet av IFRS 9 : En kvantitativ studie av redovisningsstandardens inverkan på svenska banker

   Kandidat-uppsats, Södertörns högskola

   Författare :Nour Al-Fakhoury; Nour-Eddin Shaker; [2023]
   Nyckelord :IFRS 9; Förväntade kreditförluster; konstaterade kreditförluster; svenska banker; medelstora banker; små banker;

   Sammanfattning : This study examines the impact of the transition from IAS 39 to IFRS 9 on the credit loss forecasting ability of banks, and its implications for value relevance. The implementation of IFRS 9 brought about a shift from the Incurred Credit Loss (ICL) model to the Expected Credit Loss (ECL) model, emphasizing forward-looking information. LÄS MER

3. 2. Unraveling earnings management: A comprehensive analysis of loan loss provisions under IFRS 9 and the influence of executive remuneration

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

   Författare :August Forsell; Daan van Elk; [2023]
   Nyckelord :Loan loss provisions; Banks; IFRS 9; Earnings management; Executive remuneration;

   Sammanfattning : This study examines what impact the change from the Incurred Loss (IL) model under IAS 39 to the Expected Credit Loss (ECL) model under IFRS 9 had on earnings management through loan loss provisions (LLP). By studying a sample of listed European banks, our findings suggest that CEOs manage earnings through LLP but with different loss recognition practices under the two accounting regimes, recognizing fewer LLP under IAS 39 and more under IFRS 9. LÄS MER

4. 3. Portfolio Risk Modelling in Venture Debt

   Master-uppsats, KTH/Matematisk statistik

   Författare :John Eriksson; Jacob Holmberg; [2023]
   Nyckelord :Startup Default Probability; Venture Debt; Gaussian Copula; Value-at-Risk; Expected Shortfall; Exposure at Default; Loss Given Default; Forecast; Linear Dynamic System; ARIMA Time Series; Monte Carlo Simulation; Linear Regression; Central Limit Theorem;

   Sammanfattning : This thesis project is an experimental study on how to approach quantitative portfolio credit risk modelling in Venture Debt portfolios. Facing a lack of applicable default data from ArK and publicly available sets, as well as seeking to capture companies that fail to service debt obligations before defaulting per se, we present an approach to risk modeling based on trends in revenue. LÄS MER

5. 4. Loan Loss Provisions and Lending Activity in Banks : A quantitative study comparing the effects of loan loss provisions on lending activity in banks applying IFRS 9 and ASC 326

   Master-uppsats, Umeå universitet/Företagsekonomi

   Författare :Rikard Fredmer; Alicia Julienne Zanic; [2023]
   Nyckelord :Agency Theory; ASC 326; Basel III; Earnings Management; Expected Credit Loss es ; Expected Credit Loss Model; FASB; IASB; IFRS; IFRS 9; Lending Activity; Loan Loss Allowance s ; Loan Loss Provision s ; New Loans Originated; Procyclicality; Signaling Theory; Stewardship Theory; US GAAP;

   Sammanfattning : As a response to the financial crisis of 2008 the IASB and the FASB developed IFRS 9 and ASC 326, respectively. These accounting regulations are supposed to increase reporting transparency and promote financial stability by determining the calculation and recognition of loan loss provisions. LÄS MER

7. 5. Peeking Through the Leaves : Improving Default Estimation with Machine Learning : A transparent approach using tree-based models

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Elias Hadad; Angus Wigton; [2023]
   Nyckelord :Machine learning; Expected credit loss; Probability of default; ECL; PD; Risk Management; Credit Risk Management; Default Estimation; AI; Artificial intelligence; Fintech; Supervised learning; Decision tree; Random forest; XG boost; Transparency; Machine learning transparency;

   Sammanfattning : In recent years the development and implementation of AI and machine learning models has increased dramatically. The availability of quality data paving the way for sophisticated AI models. Financial institutions uses many models in their daily operations. LÄS MER