Sökning: "credit loan"

Visar resultat 1 - 5 av 189 uppsatser innehållade orden credit loan.

  1. 1. Explainable Artificial Intelligence and its Applications in Behavioural Credit Scoring

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Robert Iain Salter; [2023]
    Nyckelord :Behavioural Credit Scoring; Deep Learning; Machine Learning; Long Short-Term Memory; Default Prediction;

    Sammanfattning : Credit scoring is critical for banks to evaluate new loan applications and monitor existing customers. Machine learning has been extensively researched for this case; however, the adoption of machine learning methods is minimal in financial risk management. 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. Finansiering av kommunala bostadsbolag : Hur finansierar kommunala bostadsbolag sin verksamhet och hur har bolagen påverkats av det senaste årets räntehöjningar?

    Kandidat-uppsats, KTH/Fastighetsföretagande och finansiella system

    Författare :Alexander Edelsvärd; Ludvig Elg; [2023]
    Nyckelord :Municipal Real Estate Companies; Financing Sources; Interest Rate Increase; Kommunala bostadsbolag; finansieringskällor; räntehöjning;

    Sammanfattning : I denna uppsats undersöks genom en kvalitativ metod vilka finansieringssätt somkommunala bostadsbolag använder sig av samt hur räntehöjningarna i Sverige det senasteåret har påverkat de kommunala bostadsbolagens verksamhet och agerande. För attbesvara frågeställningen har intervjuer genomförts med sju olika kommunala bostadsbolagoch med den kommunala långivaren Kommuninvest. LÄS MER

  5. 4. Are concessional state loans available to every SME? - Challenges and opportunities in the provision of concessional state loans for micro and small businesses engaged in tourism in the regions of Azerbaijan

    Master-uppsats, Lunds universitet/Institutionen för kulturgeografi och ekonomisk geografi; Lunds universitet/LUMID International Master programme in applied International Development and Management

    Författare :Elmar Hajiyev; [2023]
    Nyckelord :Tourism and development; Micro and small businesses; Access to finance; Concessional state loans; Environmental factors; Supply-side factors; Demand-side factors; Social Sciences;

    Sammanfattning : Tourism is considered one of the main driving forces of economic growth. At the same time, micro and small businesses play a vital role in the development of the tourism sector as a supply side. Also, the development of entrepreneurial activity directly depends on internal and external financial resources. LÄS MER

  7. 5. From Data to Decision: : Using Logistic Regression to Determine Creditworthiness

    Kandidat-uppsats, KTH/Matematisk statistik

    Författare :Joel Norling; Sami Abdu; [2023]
    Nyckelord :Bachelor Thesis; Scorecard modeling; Mathematical Statistics; Logistic Regression; Consumer Credits; Binning; Kandidatuppsats; Scorecard-modellering; Matematisk statistik; Logistisk regression; Konsumentkrediter; Binning;

    Sammanfattning : The development of scorecards for customer credit rating is a well-established field in the financial sector. The aim of this project, conducted in collaboration with a Swedish credit institute, was to develop a statistical model for predicting customer performance. LÄS MER