Does Skillful Use of Hard Information by Machines Outperform a Combination of Hard and Soft Information of Loan Officers in Lending Decisions?

2019 ◽  
Author(s):  
Prasanna L. Tantri
Keyword(s):  
Soft Information ◽  
Hard Information ◽  
Lending Decisions ◽  
Loan Officers

Loan officer rotation and credit access: evidence from Madagascar

2019 ◽  
Vol 80 (1) ◽  
pp. 51-67
Author(s):  
Yaw Sarfo ◽  
Oliver Musshoff ◽  
Ron Weber
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Frequency Effect ◽  
Content Type ◽  
Credit Access ◽  
Loan Officer ◽  
Microfinance Institution ◽  
Lending Decisions ◽  
Loan Officers ◽  
Loan Approval

Purpose With exclusive data from a commercial microfinance institution (MFI) in Madagascar, the purpose of this paper is to investigate if loan officer rotation (change of loan officer) has an effect on credit access (loan approval) in rural and in urban areas. The authors further analyze how the frequency of loan officer rotation affects credit access in rural and in urban areas. Design/methodology/approach The authors apply propensity score matching to compare credit access between loan applicants who experienced loan officer rotation and loan applicants who experienced no loan officer rotation in rural and in urban areas. Findings Results show that loan officer rotation has a positive and statistically significant effect on credit access. The authors observe further that loan officer rotation has a different effect on credit access in rural and in urban areas. Whilst rural loan applicants who experienced loan officer rotation are more likely to have credit access, urban loan applicants show no statistically significant effect of loan officer rotation on credit access. For the frequency effect on credit access, the authors observe that one loan officer rotation has a positive and statistically significant effect on credit access whereas results are mixed for two loan officer rotations. Research limitations/implications Even though the authors can show that loan officer rotation can improve credit access to loan applicants, especially in rural areas, the conditions in Madagascar are unique. Therefore, results need to be verified in other countries and institutional contexts. Practical implications From the perspective of MFI, the authors recommend that the management of MFI needs to provide better tools to loan officers to improve on the evaluation of agricultural loan products or standardize the assessment of agricultural loan products to improve on lending decisions. Further, if applicable, the authors recommend that MFI should consider using credit worthiness assessment procedures which rely less on loan officer’s judgment for loan evaluation, such as automated systems. From the perspective of loan applicants, the authors recommend that loan applicants should request for a change of loan officer if they experience successive loan applications rejection. Originality/value To the authors’ knowledge, this paper is the first to provide empirical evidence on the effect and frequency of loan officer rotation on credit access in Sub-Sahara Africa, and Madagascar, in particular.

The Right to Decide and the Effective Control Over Small Business Lending Decisions: A Look into Loan Officers’ Real Authority

2017 ◽  
Vol 46 (2) ◽  
pp. 237-268
Author(s):  
Michele Benvenuti ◽  
Luca Casolaro ◽  
Silvia Del Prete ◽  
Paolo Emilio Mistrulli
Keyword(s):  
Small Business ◽  
Effective Control ◽  
Small Business Lending ◽  
Lending Decisions ◽  
Loan Officers ◽  
The Right

scholarly journals Selecting Applicants

Econometrica ◽  
2021 ◽  
Vol 89 (2) ◽  
pp. 615-645
Author(s):  
Alex Frankel
Keyword(s):  
Test Score ◽  
Acceptance Rate ◽  
Soft Information ◽  
Test Results ◽  
Hard Information ◽  
Rate Functions ◽  
Simple Implementation ◽  
Acceptance Rates ◽  
Test Result

A firm selects applicants to hire based on hard information, such as a test result, and soft information, such as a manager's evaluation of an interview. The contract that the firm offers to the manager can be thought of as a restriction on acceptance rates as a function of test results. I characterize optimal acceptance rate functions both when the firm knows the manager's mix of information and biases and when the firm is uncertain. These contracts may admit a simple implementation in which the manager can accept any set of applicants with a sufficiently high average test score.

scholarly journals A Model for Lender-Borrower Trust in Peer-To-Peer Lending

2018 ◽  
Vol 9 (1) ◽  
pp. 15
Author(s):  
Dyah Wahyu Sukmaningsih
Keyword(s):  
Social Capital ◽  
Elaboration Likelihood Model ◽  
Soft Information ◽  
Financial Data ◽  
Trust Building ◽  
Elaboration Likelihood ◽  
Hard Information ◽  
Likelihood Model ◽  
Peer Lending ◽  
Determinant Factor

This research examined factors that influenced lender’s trust towards the borrower. The peerto-peer lending platform facilitated lending mechanism between lender and borrower. However, the loan was often considered as an unsecured loan, since there was a lack of traditional financial data. Using literature review, this research analyzed the determinant factor to establish trust between borrower and lender. Based on Elaboration Likelihood Model (ELM), the result of this research proposes a model for trust building between lender and borrower. The model categorizes information to establish trust into hard information, soft information, and social capital.

Information and Bargaining Power: Evidence from SME Lending in China

2015 ◽  
Vol 14 (04) ◽  
pp. 901-913
Author(s):  
Xiao-Yong Wang ◽  
Wei Zhang ◽  
Xiong Xiong ◽  
Hong-Li Che ◽  
Dehua Shen
Keyword(s):  
Bargaining Power ◽  
Soft Information ◽  
Loan Rate ◽  
Hard Information ◽  
Sme Lending

The bank has the access to hard and soft information about small and medium-sized enterprises (SMEs) in order to manage the informational opacity. We carry out the study about the information and bargaining power between lenders and borrowers. Bargaining power is depicted based on more favorable loan rate. The proxy is regressed on hard information, soft information and other variables. We find out that more favorable hard information (Registered Capital and Proceeds of Sale) increases borrowers' bargaining power in China. We also obtain evidence suggesting that the length of borrowers' business affect the bargaining power.

scholarly journals Soft and hard information in equity crowdfunding: network effects in the digitalization of entrepreneurial finance

2021 ◽  
Author(s):  
Saul Estrin ◽  
Susanna Khavul ◽  
Mike Wright
Keyword(s):  
Network Effects ◽  
Network Externalities ◽  
Information Provision ◽  
Network Size ◽  
Soft Information ◽  
Entrepreneurial Finance ◽  
Digital Environment ◽  
Equity Crowdfunding ◽  
Hard Information ◽  
Information Pooling

AbstractAs a digital financial innovation, equity crowdfunding (ECF) allows investors to exploit the complementarity of information provision and network effects in a reduced transaction cost environment. We build on the underlying distinction between soft and hard information and show that ECF platforms create an environment of greater information pooling that benefits from network externalities. We test our hypotheses using a unique proprietary dataset and find that soft information has a greater impact than hard on the likelihood that a financing pitch will be successful. Moreover, the effects of soft information are amplified by the size of the investor network on the platform and network size also positively moderates the effect of information on the amount invested during each pitch. We conclude that ECF platforms can successfully exploit low transaction costs of the digital environment and bring network externalities to bear on investor decisions. Taken together that these increase the supply of funds to entrepreneurs.

The Knowledge Sharing Model

2010 ◽  
pp. 1241-1263
Author(s):  
Gunilla Widén-Wulff ◽  
Reima Suomi
Keyword(s):  
Knowledge Sharing ◽  
Intellectual Capital ◽  
Value Chain ◽  
Information Resources ◽  
Soft Information ◽  
Insurance Companies ◽  
Business Success ◽  
Information Culture ◽  
Hard Information

This chapter works out a method on how information resources in organizations can be turned into a knowledge sharing (KS) information culture, which can further feed business success. This process is complicated, and the value chain can be broken in many places. In this study this process is viewed in the light of resource-based theory. A KS-model is developed where the hard information resources of time, people and computers are defined. When wisely used, these make communication a core competence for the company. As the soft information resources are added, that is the intellectual capital, KS, and willingness to learn, a knowledge sharing culture is developed, which feeds business success. This model is empirically discussed through a case study of fifteen Finnish insurance companies. The overall KS capability of a company corresponds positively to the different dimensions applied in the model. KS is an interactive process where organizations must work on both hard information resources, the basic cornerstones of any knowledge sharing, and makes constant investment into soft information resources, learning, intellectual capital and process design in order to manage their information resources effectively.

Loan Officer Incentives, Internal Rating Models, and Default Rates*

2019 ◽  
Vol 24 (3) ◽  
pp. 529-578 ◽  
Author(s):  
Tobias Berg ◽  
Manju Puri ◽  
Jörg Rocholl
Keyword(s):  
Order Effect ◽  
Foreign Exchange Rates ◽  
Bank Profitability ◽  
Return On Equity ◽  
Hard Information ◽  
Default Rates ◽  
Internal Rating ◽  
Loan Officer ◽  
Bank Behavior ◽  
Loan Officers

Abstract Manipulation of hard information has been at the center of a wave of investigations into fraudulent bank behavior, such as mis-selling of mortgages and rigging of London Interbank Offered Rate and Foreign Exchange rates. Despite these prominent cases, little is known as to why employees manipulate hard information. Using almost a quarter million retail loan applications, we show that loan officers who face volume-based incentives significantly manipulate ratings even in settings where ratings are computed using hard information only. Manipulation is widespread across loan officers, with low-performing loan officers manipulating more toward the end of the year. These incentives have a first-order effect on bank profitability, reducing return on equity by 1.5 percentage points. We conclude that reliance on hard information does not overcome loan officer agency problems, and it is important for banks and regulators to take manipulation of hard information into account when using hard information for risk assessment and regulation.

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