Commercial real estate finance and the lending cap rate

PurposeThe aim of this study is to report on a simple derivation that results in what the authors refer to as the lending cap rate. The lending cap rate is a unique cap rate resulting in a property valuation that perfectly aligns the maximum loan amount for the financing of commercial real estate.Design/methodology/approachThe derivation is the result of simple algebra relating the two most common underwriting ratios: debt service coverage and loan-to-value with the formula for the present value of an annuity. Numerical examples are presented to demonstrate the calculation of the lending cap rate, property valuation and maximum loan amount. The authors also present comparative statics results.FindingsThe main finding of this research is that once a lender knows the debt service coverage ratio, loan-to-value ratio and lending terms for a specific property financing request, a simple calculation reveals the lending cap rate and the property valuation that aligns the maximum loan amount implied by the two underwriting ratios.Practical implicationsOne practical implication of the research is that a simple calculation reveals the lending cap rate which facilitates timely property evaluations for lending purposes. The methods demonstrated also offer real estate finance educators a practical means of connecting the loan underwriting process with property appraisal thereby facilitating conceptual understanding.Originality/valueThe key finding is original, and the importance of the finding is that the determination of the lending cap rate is simple and has the ability to make commercial real estate lending faster and cheaper, especially in lending situations where an evaluation rather than an appraisal is appropriate.

DETERMINATION OF THE UJRAH OF GOLD PAID GOODS AT MANDIRI SHARIA BANK (BSM) BATUSANGKAR

This study analyzes the cost determination for a gold pawn ujrah at the branch of Banque Syariah Mandiri Batusangkar. This type of research is field research with qualitative methods. The analysis technique is based on the Fatwa DSN and the theory advanced by Rozalinda. The research results explain that the implementation of the gold pledge at the branch of Bank Syariah Mandiri Batusangkar in accordance with the Standar Operasional Prosedur (SOP) that have been set by the Bank. The costs of administration, maintenance and storage of the pledged goods are determined according to the amount of the customer's loan, the level of fees also depends on the amount of customer loans. So this is not in line with Fatwa DSN No. 25/DSN-MUI/III/2002 regarding Rahn, in point four, stated that maintenance and storage charges should not be based on loan amount. It is also not in line with the theory advanced by Rozalinda that the administration of administrative costs is based on the weight of the gold, the cost of maintaining and storing or renting the premises according to the content of the gold.

A Study of Various Constraints Regarding Credit Utilization in Jaunpur District of Uttar Pradesh

Background: Credit is the crucial input for the economic development of the farmers as it helps in increased production through use of modern inputs. The study was carried out to examine the various constraints faced by the different groups of farmers in the Jaunpur district in regards to credit utilization. Aims: To study the various constraints regarding credit utilization and credit acquisition by the borrowers Place and Duration of Study: Jaunpur district of Uttar Pradesh, between year 2020 and 2021. Methodology: A total of 120 respondents were selected randomly from the Karanzakala block of Jaunpur district, Uttar Pradesh and a pre-structured questionnaire was used to collect the data from the farmers. Respondents were classified into two categories and 60 respondents from borrowers and 60 from non-borrowers were selected for study purpose Results: It is revealed by the Garrett scores that maximum number of borrowers with 71.61 mean score reported that hectic documentation as main problem faced in acquiring the credit. Conclusion: From the findings of the study, it has been stated that there was a high level of constraints associated with access to credit. Highly responded constraints for bank credit were hectic documentation (71.61 mean score), repayment period not being sufficient (68.25 mean score) and Insufficient loan amount (60.25 mean score) were the major constraints. Due to having these constraints, farmers faced a lot of troubles to get credit which hindered agricultural activities, increased cost of credit, led to selling of agricultural crops at low prices.

Customer Loan Approval Prediction Using Logistic Regression

Banking Sector contains loan where it is a process of lending or borrowing a sum of money by one or more individuals, organizations, etc. from Banks. The Person who lends that money from respective financier incurs a debt, and he is responsible to pay back the money with the Interest decided by Bank within a certain period. Generally what Bank’s look into before applying for a loan is Credit History, Credit loss and Income of Applicant. So basically,loans play a major role regarding Income for Bank. Due to rapid urban development people who are applying for loans got increased rapidly. Therefore, finding the applicant to whom loan can be approved become a complexed process. In this paper, we want to predict the loan eligibility based on details of the customer. Fields that required are Matrimonial Status, Income, Education, Loan Amount, Credit History and other income sources of Applicant dependants. To predict the status, we will use Logistic Regression to spot the eligible applicants so bank will engage with them for granting loans to those people who can payback in a given time.

Financial projects and loans with different, decursive annuities, interest rates and capitalization periods with the use of excel

The authors of the paper have innovated and explored the theory of size relations of a financial project, the duration of its creation, the determination of its price, the duration of use and financing of the price of a project. The duration of use of a financial project has two planned time intervals. The first time interval is planned for repayment of the loan amount of the project price, and the second one is for acquisition of the planned profit. A new model of loan repayment is used – with different; decursive annuities, interest rates and periods of capitalization. The introduced theory was applied to calculations in the form of a financial project model using Excel.

Sistem Pendukung Keputusan Pemberian Jumlah Pinjaman Kepada Calon Nasabah Bumdes Menggunakan Metode Topsis (Studi Kasus Bumdes Gergas Mandiri Kecamatan Wampu)

The development of the savings and loan business is currently growing rapidly as a financial institution in alleviating poverty . BumDes is a business owned by a village or sub-district that is engaged in lending or channeling funds to people who need to develop their business. The BUMDes conducts deliberation meetings in determining loan granting. There is often disagreement between the parties that will borrow. This resulted in unequal distribution of loans to BUMDes members. Although the determination of the granting of the loan amount is fully determined by the BUMDes However, this Decision Support System will display the highest to lowest priorities of the prospective customer , so that it will facilitate and assist the BUMDes in making decisions. TOPSIS uses the principle that the chosen alternative must have the closest distance from the positive ideal solution and the longest distance (farthest) from the negative ideal solution to determine the relative proximity of an alternative to the optimal solution.

Service mantra of the Grameen banks of India in the post-merger era

Purpose This paper aims to find out the performance of the Grameen Banks of West Bengal after their merger. Design/methodology/approach The objective of the paper is to measure the performance of Paschim Banga Gramin Bank (PBGB) and Bangiya Gramin Vikash Bank (BGVB) after their amalgamation, to compare the performance of PBGB and BGVB, using the key performance indicators and to analyze the future scope of these two banks. The factors that are considered for this study are number of branches (if these banks could reach maximum of the rural mass), number of staffs (if these banks generated employment after the merger), investments, deposits, composition of total funds (owned funds and borrowed funds), lending services, productivity per branch and per staff, etc. The study uses statistical tools to analyze the data. Findings It has been observed that there exists a significant difference in the “Branch Network” of PBGB and BGVB. A significant difference has been observed in the “Number of Staffs” of PBGB and BGVB. It has been found that there is a significant difference in the “three type of funds” of PBGB and BGVB. It has been found that there is a significant difference in the “Investments” of PBGB and BGVB. A significant difference has been observed in the “Deposits” of PBGB and BGVB. It has been found that there is a significant difference in the “Outstanding Loan” amount of PBGB and BGVB. It has been observed that there is a significant difference in the “Loan Issued” amount of PBGB and BGVB. It has been found that there is no significant difference in the Productivity “Per Branch” and “Per Employee” of PBGB and BGVB. Research limitations/implications The study is based on the published/secondary data and is restricted to two Regional Rural Banks of West Bengal, the PBGB and the BGVB, for nine years, 2012–2020. Social implications The paper will help the future researchers, to know the performance of the Grameen Banks for the study period; this will help them to carry on with the study in the future. Originality/value The work is original and never sent to anywhere else for publication.

Loan Amount Prediction Using Machine Learning

Loan amount prediction is helpful for banks or organization who want their work easier. All Banks give Loan to customer and customer first apply for loan after any bank or organization validate customer information. It must be providing some advantages for banks or company or any organization who wants to give loan. There are various methods to improve the accuracy classification algorithm. The accuracy of random forest classification algorithm can be improved using Ensemble methods. Optimization techniques and Feature selection methods available. In this research work novel hybrid feature selection algorithm using wrapper model and fisher introduced. The main objective of this paper is to prove that new hybrid model produces better accuracy than the traditional random forest algorithm.

PERBANDINGAN ALGORITMA K-NEAREST NEIGHBOR, DECISION TREE, DAN NAIVE BAYES UNTUK MENENTUKAN KELAYAKAN PEMBERIAN KREDIT

The banking world in terms of providing credit to customers is a regular activity that has a large effect. In its application, non-performing loans or bad loans are often created due to poor credit analysis in the credit granting process, or from bad customers. The purpose of this study is to compare the results of algorithm accuracy between K-Nearest Neighbor (K-NN), Decision Tree, and Naive Bayes which results in the best accuracy will be implemented to determine creditworthiness. The attributes used in this study consisted of 11 attributes, namely marital status, number of dependents, age, last education, occupation, monthly income, home ownership, collateral, loan amount, length of loan and information as result attributes. The methods used in this research are K-Nearest Neighbor, Decision Tree, and Naive Bayes. From the results of evaluation and validation using k-5 fold that has been carried out using RapidMiner tools, the highest accuracy results from a comparison of 3 algorithms is using a decision tree (C4.5) of 98% in the 3rd test.

Mobile Credit and Performance: Experience and Lessons from Micro and Small Enterprises in Kenya

Micro and small enterprises sector is considered as very important in growing the economies of many countries, especially the developing nations. In Kenya, the Micro and small enterprises sector is an important contributor to the growth of the economy through facilitation of trade and creation of employment. While various interventions have been made to grow this sector, the enterprises have continued to perform poorly, struggle to survive and a large number die off. This study sought to investigate the effect of mobile credit on performance of micro and small enterprises. The study was to determine the effect of accessibility, the effect of the cost, the effect of mobile credit loan amount and the effect of regulation on performance of micro and small enterprises. The study was anchored on various theories of Resource based view, Dynamic capabilities, Diffusion of technology, Credit rationing, and the asymmetry of information. The study found out that the accessibility of mobile credit, the Loan amount and the regulation have significant positive effect on performance, while the cost of mobile credit has a significate negative effect on the performance of micro and small enterprises. The study concluded that mobile credit is an essential source of credit to micro and small enterprises. Keywords: Mobile credit, Micro and small enterprises, Performance, Resource based view, Dynamic capabilities theory.