**Antecedents of SME Loan Defaults : An Exploration of Business Failure Factors as Measures of Cr...

1. Micropolitics: This topic is universal common features for many SMEs and financial institute and it will not restrict to any particular institute rather it will be a combination of different SMEs and Financial Institutes. Multi stake holders from both internal and external will be a part of this thesis hence there are very minimal chance of debate.

2. Risk and security: Risk of sharing trade secrets and designing new risk framework for SMEs itself a risky proposition however potential sustainable and profitable model compensate the risk also.

3. Resources: Need to involve multiple SMEs and officials from financial institutes which is time consuming and sometime expensive.

4. IT skills: This thesis will get another level of dimension if we can implement AI and machine learning to identify mistake trend and potential risks for SMEs and credit model. These implications require high IT skills and resources.

5. Interest and relevance: Master's Degree Programme in International Business Management at Tampere University of Applied Sciences gives me encourage and hope to work for financial institute to support Small-Medium Enterprises. By learning from other SME’s mistakes, I will be able to design SME business analysis framework for myself and any financial institutes. To me learning from other’s failures is the key to develop sustainable SMEs.

6. Durability: Identification of key factors for SME failures and bad credit history we will able to design business model for SMEs and as well as credit framework for financial institute. By implementing AI in Small Business, we can generate early alert for both SMEs and financial institutes. Usually SMEs are not aware of their future mistakes and not keen for its sustainability. Moreover, due to lack of consistency in innovation; financial institutes may not continue this learning and development of credit risk modeling. Instead of these uncertainties this thesis topic itself a requirement for both SMEs and Financial Institutions.

7. The breadth of research questions: This topic directly and indirectly supporting SMEs and Financial Institutions to identifying mistakes of SMEs and existing Credit Models. This thesis is having a broad aspect for modeling credit risk and making SME sustainable. Through this thesis I want to implement Ai and machine learning for identification of Business Failure Factors; also wants to design a SME credit inducive model for both financial institute and SMEs to ensure sustainable business model.

8. Topic adequacy: This topic will be able to establish itself as a necessary topic to explore more for ensuring sustainable SME and SME friendly credit risk model for financial institute. These relevancies of the topic will help this thesis to go through assessment.

9. Access: Interviewing SMEs and credit officials of financial institute can enlighten us to understand reasons behind SME credit failures. SME and financial institutes both have interest to make SMEs sustainable and to imply a innovative SME friendly credit models.