مدیریت تبلیغات و فروش

مدیریت تبلیغات و فروش

کمینه‌سازی ریسک اعتبار مشتریان با استفاده از تشخیص میزان ریسک در بانکها

نویسندگان
1 دانشجوی دکتر، گروه مهندسی صنایع، دانشگاه ایوانکی، سمنان، ایران
2 استادیار، دانشکده ی مهندسی صنایع، دانشگاه ایوانکی، سمنان، ایران.
JABM.3.2.15564.358898
چکیده
روش های زیادی برای محاسبه ریسک اعتبار مشتریان یک فرد یا یک موسسه وجود دارد، اما ما در این مقاله به دنبال پیش بینی مقدار ریسک اعتبار مشتریان در بخش های مختلف مانند صنعت، کشاورزی با توجه به شاخصهای اقتصادی مانند نوسانات نرخ ارز هستیم. این محاسبات موجب می شود تا ابتدای هر سال مبلغ های مورد نیاز برای تخصیص به بخش و شهرهای مختلف مشخص گردد تا کمینه میزان ریسک اتفاق افتد. ما در این پژوهش با استفاده از داده های مربوط به بانک های استان سمنان، میزان ریسک اعتبار مشتریان را در بخش های مختلف و در شهرهای مختلف محاسبه کرده ایم بدین صورت که با استفاده از خوشه بندی ابتدا عوامل موثر در عدم بازپرداخت ها را مورد بررسی قرار می دهیم، سپس با استفاده از خوشه بندی نمراتی به هر خوشه داده ایم، در ادامه نمره هر شهر در هر بخش با استفاده از نمره بازگشت تسهیلات و خوشه بندی را محاسبه کرده ایم. با توجه به نتایج عددی نتیجه می گیریم که شاهرود به عنوان قطب کشاورزی در استان سمنان شناخته شده است لذا تخصیص منابع کشاورزی در این شهر بهتر می باشد و در نقطه مقابل آرادان اصلا وضعیت خوبی در کشاورزی ندارد. همچنین سمنان نیز قطب صنعتی می باشد و به همین علت تخصیص وام های بخش صنعت در این شهر از بازدهی بیشتر برخوردار می باشد، در مقابل میامی اصلا یک شهر صنعتی نیست و در این بخش نباید بودجه ای دریافت کند.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Minimizing the credit risk of customers by using the detection of the amount of risk in banks

نویسندگان English

Mehdi Salamati 1
Ahmad Gaeeni 2
1 PhD student, Department of Industrial Engineering, Ivanki University, Semnan, Iran
2 Assistant Professor, Faculty of Industrial Engineering, Ivanki University, Semnan, Iran.
چکیده English

There are many methods to calculate the credit risk of customers of an individual or an institution, but in this article we seek to predict the amount of credit risk of customers in different sectors such as industry, agriculture according to economic indicators such as exchange rate fluctuations. These calculations will determine the amounts required for allocation to different departments and cities at the beginning of each year so that the minimum amount of risk occurs. In this research, using the data related to the banks of Semnan province, we have calculated the amount of credit risk of customers in different departments and in different cities, in such a way that by using clustering, we first examined the factors affecting non-repayments. then we have given scores to each cluster using clustering, then we have calculated the score of each city in each section using the return score of facilities and clustering. According to the numerical results, we conclude that Shahroud is known as an agricultural hub in Semnan province, so the allocation of agricultural resources is better in this city, and on the opposite point, Aradan does not have a good situation in agriculture at all. Also, Semnan is an industrial hub, and for this reason, the allocation of industrial sector loans in this city is more efficient, on the other hand, Miami is not an industrial city at all and should not receive funding in this sector.

کلیدواژه‌ها English

Customer credit risk
customer credit risk management
outstanding receivables
exchange rate fluctuations
Basel Committee
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