Bad Customers Research Articles

Penyelesaian Kredit Macet dengan Jaminan Hak Tanggungan pada PT Bank Perekonomian Rakyat Pulau Punjung

Providing credit does not always run smoothly, there are some loans that are bad because debtors do not carry out their obligations properly. If bad credit is not handled properly, it will have a bad impact on PT BPR Pulau Punjung because it will disrupt cash flow in and out. This research aims to find out: (1) What is the process of resolving bad credit with mortgage guarantees carried out by BPR Pulau Punjung? (2) What are the obstacles and constraints faced by BPR Pulau Punjung in resolving bad credit with collateral? (3) What efforts have been made by BPR Pulau Punjung to resolve the problems or obstacles that occur in bad credit with mortgage guarantees? This research method is empirical and includes descriptive research. The data source was obtained from interviews. The data collection techniques were literature study and field study. The results of this research are (1) The resolution of bad credit at PT BPR Pulau Punjung was carried out very well by making various efforts to save credit and in accordance with banking procedures. (2) constraints and obstacles faced by PT. Punjung Island BPR in resolving bad credit with mortgage guarantees is difficult to meet customers, bad customer character, economic factors, the credit given is not fully used for business, the debtor is not open to creditors, the debtor is negligent in the agreement, the condition of the debtor's family is not conducive. . (3) Efforts made by PT. Punjung Island BPR in resolving the problems and obstacles that occur in bad credit with collateral rights is applying the 5C 7P and 3R principles, and BPR proposes various efforts for bad credit which can still be saved by finding out the factors causing the bad credit by re-surveying and considering returned a request to save the bad credit. In conclusion, before executing the PT guarantee. BPR has made various efforts to save bad credit so that the debtor's credibility does not decline.

ROLE OF INDIAN CONSTITUTION IN WOMEN EMPOWERMENT

The Indian Constitution is a beautiful blend of both federal and unitary systems. The Indian Constitution is called a federal constitution on the basis that it is a written constitution. It provides for a supreme and independent judiciary. The preamble of the Indian Constitution declares the goal of making India a democratic republic. Its head of state will be elected democratically. Being a republic means that any common person of India, whether a man or a woman, can reach the highest position in the country on the basis of his qualifications. India is a union of states. It is an independent sovereign socialist democratic republic with a parliamentary system of government. This republic is governed according to the Constitution of India which was adopted by the Constituent Assembly on 26 November 1949 and which came into force on 26 January 1950. The Constitution of India is the supreme legal authority that links together the legislative, executive and judicial organs of the government. The Constitution provides fundamental rights to all citizens and gives the independent judiciary the right to declare invalid the laws or government actions that violate the Constitution. In the Vedic period, women had a very respectable position in India. But later in the medieval period, the status of women deteriorated a lot due to the arrival of foreigners. Due to illiteracy, bad customs and conservatism in the society, the status of women was greatly affected. But gradually in the first half of the nineteenth century, some social workers of India like Raja Ram Mahen Rai, Swami Dayanand Saraswati, Ishwarchand Vidyasagar and Keshavchand Sen raised their voice against the oppressive social system. They raised their voice before the then British rulers for gender equality, women education, ban on Sati Pratha and ban on polygamy, as a result of which Sati Pratha Prohibition Act, 1829 and Hindu Widow Remarriage Act in 1856, Age of Constancy Bill in 1891 and Vative Marriage Act to stop polygamy were passed. By the twenty-first century, the condition of women started improving and the Indian Constitution implemented provisions to promote women's upliftment and empowerment and to improve their economic, social, educational and political status and to include them in the mainstream of development by running many welfare schemes and developmental works.

Risk Mitigation of Murabahah Financing for Teacher Certification at BPRS Metro Madani KCWest Garlic Bones

Murabahah financing for teacher certification is a form of financing based on sharia principles in order to help teachers to obtain certification as part of increasing their professional competence. This research journal aims to find out how risk management is implemented in murabahah financing for teacher certification (Sergu) and how banks try to deal with bad customer financing. The object of this research is PT. BPR Syariah Metro Madani KC Tulang Bawang Barat. The method used isqualitative approach, type of field research (Field Research). The results of this research arerisk control at PT. BPR Syariah Metro Madani KC Tulang Bawang Barat has been managed well and in accordance with Standard Operating Procedures (SOP), which includes risk identification, risk measurement, risk monitoring and risk control.Customers duplicate teacher certification, bank (payroll accounts), late disbursement of certification funds from the government, teachers or customers are fired from their jobs while the financing process is still pending, or the government revokes certification funds.Implementation of risk management at PT. BPR Syariah Metro Madani KC Tulang Bawang Barat has been carried out by PT. BPR Syariah Metro Madani KC Tulang Bawang Barat starting from the implementation of market risk handling, credit risk and operational risk has been implemented in accordance with the handling program procedures implemented by the bank, it has been implemented in accordance with the risks that arise, the target to be achieved in handling financing risk management has been achieved.

An examination of the 2012–2022 empirical ethical decision‐making literature: A quinary review

AbstractThis review summarizes the empirical ethical decision‐making (EDM) research in business published between 2012 and 2022. Utilizing Rest's (Moral development: advances in research and theory, Praeger, New York, 1986) four‐step model for EDM and Jones' (Acad Manag Rev, 16(2): 366‐395, 1991) theory of moral intensity, 85 articles, resulting in 388 findings, were analyzed. Empirical findings in awareness, intent, judgment, and behavior were categorized by their application to individual and organizational factors resulting in the application of 624 and 62 factors, respectively. A maturing of the research environment is seen through the need for grouping individual factors into themes, essentially forming new connections within EDM research. This article prioritizes new factors and themes, such as bad behaviors, customers and selling, fantasy and imagination, and negative experiences. Additionally, new research in reoccurring themes such as demographics, feelings, personality, and power have elements that were seen in prior reviews but are more nuanced in the current. Furthermore, this quinary review discusses the evolution of EDM research highlighting the relationships studied and modifiers and mediators used. These themes help shape the landscape of EDM research by illustrating the intersectionality of variables. This article advances the understanding of how these foundational models are being nuanced to understand more deeply the EDM process. A call for future research incorporating intersectionality, the continued pursuit of complex relationships, longitudinal research, and major societal and organizational movements is included. Research into the effects of underrepresented demographics such as gender identity, veteran status, and ability is suggested. Furthermore, we question whether Rest (1986) and Jones' (1991) models are inherently Western and if comparing outcomes with a decolonialized research method might give insight into EDM. We present this latest 10‐year collection of EDM empirical research based on Rest (1986) and Jones (1991) as a tool for new and future scholars to utilize in their research endeavors.

A PLAN FOR HANDLING COMPLEX FINANCING IN KPR PRODUCT: BANK JATIM SYARIAH

The need for adequate housing continues to increase very rapidly from year to year along with the increase in population, but there are still many obstacles to fulfilling it. So banking institutions are present as intermediation institutions by offering mortgage financing products. Due to the large number of applications for financing, problems often arise. This research aims to determine the factors that cause financing problems in the iB Barokah KPR product at Bank Jatim Syariah Jombang evidence. The research method used is a qualitative descriptive research method. Data collection techniques come from interviews and observations. The results of this research show that the factors that cause financing problems with the iB Barokah KPR product are caused by external factors (the customer's side) whether caused by intentional or unintentional elements, such as customers affected by natural disasters, the Covid-19 pandemic, and bad customer character. The strategy used to deal with the risk of problematic financing goes through three stages. First, the stage of anticipating problematic financing by conducting a 5C analysis and a psychological approach. Second, the rescue stage user restructuring. Third, the settlement stage is through non-litigation, litigation.

Evaluasi Penerapan Reward dan Punishment bagi Nasabah Kredit pada LPD Kesiman

The growing LPD Kesiman faces various problems, especially the risk of non-performing loans. Efforts made to improve the smoothness of credit payments are by providing rewards and punishments for credit customers. This research was conducted to determine the application of reward and punishment for credit customers and the implications for LPD Kesiman. This research is a descriptive research with a qualitative approach, collecting data by observation, interviews, and documentation. The informants in this study were LPD Kesiman credit employees. The results showed that the implementation of reward and punishment for credit customers at the LPD Kesiman had gone well, rewards were given in the form of ease in managing credit, priority was given to credit, service and faster credit disbursement. Provision of punishment in the form of warning letters up to three times, summons to the LPD Kesiman office regarding bad credit constraints, as well as withdrawing credit collateral to be sold/auctioned to cover the amount of bad customer debt. The application of reward and punishment provides two types of implications for the Kesiman LPD, namely: the impact on credit development and the impact on the level of discipline of customers/debtors at the LPD Kesiman.

LIKO-S: is green the new grey?

Learning outcomes After reading and analyzing the case study, the students would be able to identify the main stakeholders and decision-makers and their importance and influence on the environment for a product, evaluate the value chain of the product and critical decision-makers, evaluate the various ways to avoid falling into the trap of greenwashing and examine the marketing strategy to market an environmentally friendly product. Case overview/synopsis LIKO-S is a Czech manufacturing and construction company. The company has been designing and creating intelligent solutions, such as green facades or vertical greenery systems, to save energy in building heating and cooling systems. The company launched green facades in the Czech market. However, the main obstacle was the need for supporting data to showcase the positive environmental impact of green facades. Under these circumstances, Libor Musil’s main objective was to overcome prevalent misconceptions about green facades and find a suitable market segment. The situation worried the company, as LIKO-S had heavily invested in developing and marketing the green walls. The management had to tackle this challenge as soon as possible to recover the substantial research and development and marketing investments. Furthermore, owing to lack of information, even genuinely sustainable products were seen as greenwashing. In addition, bad or wrong customer perceptions of these walls might spill over to other products, tarnishing the company’s image and threatening its survival in the domestic market. Under these circumstances, competitors might enter the Czech market, jeopardizing the company’s overall profits. Consequently, Libor was in a great dilemma about managing the financial and reputational risk of the company. Should Libor close the green walls unit, explore different markets/uses or help increase awareness among the general population about green walls by finding a suitable marketing strategy? Complexity academic level The case study was designed for graduate-level students in the strategic management (CSR and innovation module) courses. However, the case could also be an excellent addition to marketing courses dealing with customers’ perceptions of innovative products and strategies to improve the adoption of the product. Supplementary materials Teaching notes are available for educators only. Subject code CSS 3: Entrepreneurship

THE INFLUENCE OF RISK MANAGEMENT AND INTERNAL AUDIT APPLICATION ON THE RISK OF NON-LOOKING LOANS AT BANCO NACIONAL DE COMERCIO DE TIMOR LESTE

The purpose of this study is to provide empirical evidence of the partial effect of the implementation of risk management and internal audit variables on the risk of bad credit at BNCTL. The population in this study were all 123 BNCTL Credit Analysis Managers and Staff. The samples used in this study were 123 BNCTL Credit Analysis Managers and Staff, using a census sampling technique, collecting data using questionnaires distributed as many as 123 and questionnaires that could be used as many as 70 and statistical analysis tool using multiple linear regression analysis. The results of the first test study show that the Application of Risk Management has a Significant Effect on the Risk of Bad Credit in Managers and Staff of BNCTL Credit Analysis. This means that the better the implementation of risk management, the BNCTL will be more efficient and effective in reducing the risk of bad credit customers. Thus, the implementation of banking risk management plays an important role in the effectiveness or minimization of bad credit risk. It is hoped that the risk management implemented by the BNCTL will assist in reducing the risk of bad loans. This is shown by the obtained t-count value of 5,817 greater than the t-table of 1,995, with a significant level of 0,000 less than the error tolerance of 0.05. While testing the second hypothesis, Internal Audit also has a significant effect on Bad Credit Risk. This shows that the better BNCTL implements internal audit, the more efficient and effective the risk of bad loans can be and can be controlled properly. This is indicated by the t-count value obtained of 2,268 which is greater than the t-table of 1,995, with a significant level of 0.027 which is smaller than the 0.05 significance level. The results also show that the coefficient of determination or contribution (R square) of the Variable of Application of Risk Management and the Variable of Internal Audit to the Risk of Bad Credit is 0.394 or 39.4%, meaning that the Risk of Bad Credit can be explained by the Variable of Application of Risk Management and Internal Audit of 39.4% and the remaining namely (100% - 39.4%) = 60.6% Bad Credit Risk, influenced by other variables not examined in this study.

STRATEGI KOMUNIKASI PEMASARAN DALAM MEMPERTAHANKAN LOYALITAS PELANGGAN INDOMARET DI KOTA BATAM

Modern retail is a way for companies to retail their products to final consumers for personal needs. Batam City is one of the cities that has a permit to establish a modern retail business, one of which is Indomaret. This study found a problem, namely a decrease in the number of customers in the last 3 years at 3 Indomaret stores in Batam City. The purpose of this study is to describe forms of communication and promotion in maintaining Indomaret customer loyalty in Batam City. This research method uses a qualitative approach with data collection techniques through observation and interviews using purposive sampling method. The research analysis used the credibility test and the transferability test. The results of this study found several factors causing a decrease in the number of Indomaret customers in Batam City, including bad customer experience so that customers were disappointed such as unfriendly service, employees who were not focused and less creative in delivering promotions, product prices did not match the price tags displayed, long service or long queues, internal employee factors that affected sales declines such as not understanding the target market.

Comparison of different approaches using Random Forest for imbalanced credit data

Abstract Credit scoring models are extensively used in credit risk management of individual customers. These models are based on econometric methods using past data about customers, both defaulters and non--defaulters. These models focus on the optimal separation between good and bad customers taking into account two types of errors that appear, namely: the False Positive (Type 1 error) and the False Negative (Type 2 error). The purpose of the project was to focus on the problem of unbalanced data. Different balancing methods have been applied to the data set obtained from the financial institution operating in the European market. Various levels of unbalance have been considered and different statistical assessment metrics have been compared.

The Problem of Murabaha Financing of Islamic Microfinance Institution and The Handling Strategies in Indonesia: A Literature Review

Indonesia is a country with the largest Muslim population in the world and has extraordinary potential in the amount and assets of Islamic microfinance and can be a reference for the application of Islamic Microfinance in other countries. The purpose of this study was to review the problems in murabaha financing at Islamic Microfinance Institution (IMFI) and the treatments. The approach used was a qualitative analysis of Indonesian literature studies about the specific type of murabaha financing with content analysis and thematic analysis techniques. This study found that internal and external factors caused problematic murabaha financing in BMT. Internal factors include the inaccuracy of BMT in 5C (Character, Capacity, Capital, Collateral, and Condition), lack of supervision, procedures violations, facilities and infrastructure, and lack of human resources (HR). Meanwhile, external factors include bad customers, unexpected circumstances of customers, lack of customer income, inflation, and government policies. The actions done by the BMTs to overcome problematic murabaha financing were by implementing BMT guidelines for prospective customers, preventing and repressive supervising, applying a democratic leadership style, applying fines, rescheduling, restructuring and reconditioning write off, auction of collateral, and legal actions. This study recommends strengthening financing selection by improving human resource skills and also variations in handling murabaha financing with a humanist approach.

Analisa Penerapan Metode Naïve Bayes Dalam Memprediksi Kelayakan Calon Nasabah Dalam Melakukan Pinjaman

Financing through loans is common in the financial world, but the loan approval process requires careful assessment to minimize credit risk that may arise. In this study, we propose the application of the Naïve Bayes method as a tool to predict the eligibility of prospective customers in making loans. This research uses historical datasets from banks that include credit information, payment history, and customer profiles. The analysis process begins with data pre-processing to clean and address missing or incomplete data. Next, the extraction of relevant features and selection of variables are carried out to build a prediction model. The Naïve Bayes method was chosen because of its simple and fast nature in classifying data. This model makes use of the assumption of feature independence, which is useful when feature dimensions are high. In the training phase, the Naïve Bayes model will learn from historical datasets to recognize good and bad customer eligibility patterns. The results of this analysis show that the Naïve Bayes method has succeeded in predicting the eligibility of prospective customers with a satisfactory level of accuracy. In addition, the model is able to identify key factors that affect loan eligibility, such as credit history, income, and financial dependents. This study contributes to finance by presenting predictive tools that can help financial institutions make more informed and efficient decisions regarding loan approvals. However, we also acknowledge that the Naïve Bayes method has limitations, such as the assumption of feature independence, which must be considered in the interpretation of prediction results.

Assessment of the Comprehensive Performance of 5G Base Station using the COPRAS

As wireless internet expands quickly, so does people's anticipation for the effectiveness and efficiency of mobile communication. After 2020, the fifth generation (5G) of cell communication technologies will take over as the primary direction for wireless technology growth. Problems like bad customer experience and inadequate coverage area commonly arise when the size of 5G ground stations progressively grows. Therefore, it is essential to assess the overall performance of 5G access points to identify any issues that may have arisen during base station installation. The "COPRAS (Complex Proportional Assessment)" technique is employed in this research to assess the overall performance of 5G network sites. In this study, specific 5G base stations in an area are chosen for a thorough performance assessment. Factors such as "Signal coverage area (104 m2), Annual average business loadings (kW), Per capita input cost (rupee/person), Electric field intensity (V/m), and User experience degree" are taken into consideration to assess the overall performance of a 5G ground station. The rank of alternatives using the COPRAS method for Base Station 1 is second, Base Station 2 is fifth, Base Station 3 is fourth, Base Station 4 is third, and Base Station 5 is first. The result from the COPRAS analysis shows that the base station with a signal coverage area of 26.7104 m2, annual average business loadings of 22 kW, and electric field intensity of 1.32 V/m is optimized as the best among the 5G base stations considered.

Influence of The Service Quality Dimension on Attitudinal Loyalty and Behavioral Loyalty Moderated by The Level of Internet Usage and Switching Costs

The increase in Indihome subscribers increased but the Fixed Broadband Market Share for Indihome products decreased. It is suspected that there is a decrease in Indihome customer loyalty, supported by data on bad customer loyalty behavior and also the attitude of customer loyalty is not good. Investigation is necessary to find the causes of decreased loyalty, so this research uses the Service Quality internet service provider model for quantitative analysis involving independent variables namely Network Quality, Customer Service, Information Quality and Security, and the dependent variables namely Attitudinal Loyalty and Behavioral Loyalty, and moderator variables namely Internet Usage Lavel and Switching cost. The causal relationship between the eight variables forms a structural equation model (SEM). Data were obtained from 408 Indihome internet customers, and the data were analyzed using WarpPLS 8.0 software.
 The results of this research indicate that the provider must pay attention to information to customers to continue to provide complete, up-to-date, useful and accurate information to make customers loyal. They also need to pay attention to the value of increasing customer loyalty, which in the future customers will continue to subscribe. And they need to improve Customer Service services for Internet users with high intensity. The provider need to increase Security which has a high level of Switching Cost because it can weaken Attitudinal loyalty.

Why are consumers dissatisfied? A text mining approach on Sri Lankan mobile banking apps

PurposeThe motivation of this study is to identify whether the overall rating of a banking app actually reflects the customer opinion and to find the causes for reduced ratings. Thus, these causes lead to the dissatisfaction of customers. Additionally, these insights reflect the overall rating of the app and it is a source of information to the executive management to contemplate on their services and take timely and effective decisions to improve their mobile app.Design/methodology/approachThis research was conducted on ten reputed Sri Lankan mobile banking apps to analyze the textual opinions of the customers. Data were collected from the Google Play Store considering the higher Android consumers in Sri Lanka. Each review was automatically classified into a relevant sentiment (positive, negative or neutral). These classified reviews were examined along with its rating to identify any discrepancies. The trends of the positive and negative reviews of each app were observed separately along with time. Topic modeling techniques were used to identify the causes of such behavior.FindingsAlthough banks expect to perpetuate good customer reviews all the time, there were aberrant negative trends observed during certain time ranges. The results revealed that unstable versions after recent updates, bad customer service, erroneous functional and nonfunctional features are the root causes toward the dissatisfaction of the customers.Originality/valueNo previous study has been done on the textual reviews of Sri Lankan mobile banking apps. Most studies had considered analyzing the reviews of the app on the entire period of its usage, whereas this research finds the trends where negative reviews surpass the positive reviews and analyze the causes of such behavior.

The Evil of Humanity in Shirley Jackson’s “The Lottery” and “The Summer People”

Centered around the evil of humanity concerning backward customs, this paper analyze the indifference and hypocrisy among villagers and even their relatives, as well as their blind adherence to tradition. Base on the previous researches, the further scrutiny of the characters both in “The Lottery” and “The Summer People” by Shirley Jackson provide us with profound reflections. Through the dramatic events of senseless violence and behavior in people’s own lives, Jackson’s stories urge people to reflect on the ugliness of humanity described by the writer, and appeal to people in contemporary society to abandon bad customs so as to transform the evil of humanity into the good of humanity for we should live in a civilized and democratic society.

Implementasi Metode K-Means Untuk Memprediksi Status Kredit Macet

A credit card is one of the legal payment media owned by a bank in making a payment transaction within the agreed timeframe. In particular, credit services are provided by institutions or bodies that have the authority to distribute funds in the form of financial assistance to individuals and groups. However, in practice there are bound to be obstacles, especially during payback periods that often occur, such as when a customer wants to submit a Repeat Order or apply for funds again. Obstacles that are usually encountered in the process of granting credit are substandard credit and bad credit payments. Before PT Esta Dana Ventura wants to decide to approve applications for re-granting credit cards from prospective repeat order customers, a classification of assessment criteria is needed to determine the feasibility of granting credit to prospective repeat order customers. This study made the decision to use Data mining clustering classification with Rapidminer tools as a tool to obtain accurate results by processing data using the K-Means clustering method to help PT. Esta Dana Ventura in analyzing potential non-performing loans. By comparing survey data for Repeat Order candidates with previous credit granting data and classifying them in the form of bad or non-bad credit classifications.From the results of research using the k-means method it can produce grouping data into 3 criteria, namely (C0) 69 data with current customers, (C1) 3 data with very current customers, and (C2) 52 data with Bad customers..

Applied of Classification Technique in Data Mining For Credit Scoring

In the development of the banking business, credit issues remain interesting to study and uncover. Most of the problems occur not in the system implemented by the bank, but the problem occurs precisely in the human resources who manage credit, either in their relationship with consumers or in errors on the part of the bank which mispredicts in assessing consumers who apply for credit. Several studies in the computer field have been carried out to reduce credit risk which causes losses to the company. In this study, a comparison of the Naive Bayes, C4.5 and KNN algorithms was carried out which was applied to consumer data that received credit eligibility for good and bad customers. The best prediction results are nave Bayes with an accuracy of 95.95% and an AUC of 0.974. The results of this classification are implemented in the form of a website-based application that can be used to facilitate related parties in the credit scoring system.

Improved C45 performance with gain ratio for credit approval dataset

<p class="AbstractL-MAG"><span>Abstract—</span> People's shopping behavior has undergone many changes after the COVID-19 pandemic. Many people have switched to using the marketplace to make buying and selling transactions. The payment process in the marketplace is relatively easy, especially when using a credit card. The increase in demand for credit must be addressed better by financial providers to minimize bad loans. The best thing in minimizing bad credit is to be more selective in choosing credit customers. Data mining is a field that can study old data to become new knowledge in the future. In data mining, the classification of bad credit customers is mostly done. One of the algorithms that excels in handling credit approval datasets is C45. The C45 model is widely used because it has an output decision tree that is easier to understand in human language. The number of data attributes can affect the performance of the algorithm. Feature selection is a form of attribute reduction to improve data quality and improve classification algorithm performance. Gain ratio is the development of information gain and is the best feature selection model and is widely used by researchers. This study performs a classification using C45 and uses a gain ratio for the selection of credit approval data features. By using the gain ratio, the accuracy of the C45 classification algorithm increased from the previous 94.12% to 95.29%.</p>

Optimal cost-sensitive credit scoring using a new hybrid performance metric

This paper aims to provide an optimal credit rating by using a new hybrid performance metric, including several performance metrics, referred to as the probability of credit scoring correctness. There have been several credit-scoring models proposed in the banking system. These models, either single classifiers or hybrid and ensemble models determine the class of customers (good or bad accounts). The banks need the probability of default to calculate the expected loss and the unexpected loss and then determine whether their capital is adequate. Generally speaking, the proposed model can utilize n classifiers and m performance metrics, the larger n, and m, the more diverse and more reliable the model is as an estimate of customer classes. We evaluated the proposed model using five common classifiers, namely k-nearest neighbors (KNN), support vector machine (SVM), decision tree (DT), AdaBoost, and probabilistic neural network (PNN), and eight performance metrics. To extract the feature, an optimization approach using genetic algorithms and nine different scenarios were used. We have then calculated the optimal parameters of each algorithm simultaneously by defining the cost-sensitive objective function based on the probability of correctly classifying it into two classes 0 (good) and 1 (bad). We evaluated the performance of the proposed hybrid model using the Iranian dataset and the UCI German and Australian datasets. The results indicate the proposed method provides very good scoring performance. Using this approach, the bank can filter its bad customers based on the tolerance it considers for the probability value, so it can decide whether it should provide loans to that customer.