Machine Learning in Credit Scoring
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Questions and Answers

According to CTOS, which of the following factors carries the highest weight in their credit scoring system?

  • Credit history length
  • Amount owed
  • Payment history (correct)
  • Credit mix

    • In the context of machine learning (ML) credit scoring, which of the following 'C' components is closely associated with a borrower's ability to repay a loan?

  • Collateral
  • Condition
  • Capacity (correct)
  • Character

    • Which two key metrics are typically predicted by Machine Learning (ML) models in credit scoring, to aid in the credit decision process?

  • Credit history length and credit mix
  • Payment history and amount owed
  • Probability of default (PD) and loss given default (LGD) (correct)
  • Debt-to-income ratio and credit utilization rate

    • In the context of machine learning credit scoring, what type of information does borrower data fall under?

    <p>Hard Information (B)</p> Signup and view all the answers

    According to CTOS, what percentage of a credit score is determined by 'new credit'?

    <p>10% (C)</p> Signup and view all the answers

    Which of the following best describes how AI techniques enhance credit risk management?

    <p>By enabling the integration of large and diverse datasets that were previously unusable. (B)</p> Signup and view all the answers

    Which of the following data types is least likely to be integrated into AI-based credit analysis?

    <p>The borrower's preferred brand of coffee. (C)</p> Signup and view all the answers

    What role do economic, industry, and regulation data play in AI-based credit analysis?

    <p>They affect a firm's business performance and financial stability, impacting credit risk. (A)</p> Signup and view all the answers

    What is the purpose of setting up ESG data platforms in banking?

    <p>To link ESG considerations to credit policies and product offerings (B)</p> Signup and view all the answers

    What is the primary function of GFI Fintech Sdn Bhd?

    <p>Specializing in profiling technology and psychometric credit risk assessment for the finance industry. (D)</p> Signup and view all the answers

    Which of the following is NOT considered a non-bank lending organization?

    <p>Traditional Commercial Bank (D)</p> Signup and view all the answers

    Which of the following best describes the GSSIPS Framework?

    <p>A guideline for delivering impactful sustainable finance (C)</p> Signup and view all the answers

    What principle governs the activities defined under the Sustainability Risk Management of the bank?

    <p>Avoidance of activities on the Exclusion List (A)</p> Signup and view all the answers

    Which data source is most indicative of digital customer information used in AI-based credit analysis?

    <p>Social network activity (A)</p> Signup and view all the answers

    How does behavioral finance impact bank lending practices?

    <p>By influencing borrower decision-making processes (C)</p> Signup and view all the answers

    Which of the following variables is least likely to be factored into creditworthiness data?

    <p>The borrower's political affiliations. (C)</p> Signup and view all the answers

    What is the potential impact of 'Economics, Industry, Regulations' data on credit risk analysis?

    <p>It can significantly affect a firm's business and financial performance, thus influencing credit risk. (C)</p> Signup and view all the answers

    What is one of the segments that the GSSIPS Framework covers?

    <p>Commercial and Wholesale Banking (C)</p> Signup and view all the answers

    What role do P2P sites fulfill in the lending process?

    <p>Managing the entire process, including creditworthiness assessment, loan servicing, payments, and collections. (A)</p> Signup and view all the answers

    Who regulates P2P lending platforms in Malaysia?

    <p>Securities Commission Malaysia (SC). (D)</p> Signup and view all the answers

    What was the total P2P financing amount raised in Malaysia as of end-December 2022?

    <p>Approximately RM3.87 billion. (D)</p> Signup and view all the answers

    What percentage of P2P investors in Malaysia are below 35 years old?

    <p>49% (A)</p> Signup and view all the answers

    In 2022, what was the average amount targeted by the majority of P2P issuers in Malaysia?

    <p>RM50,000 or less. (D)</p> Signup and view all the answers

    What is the primary purpose for which the majority of P2P-raised funds were targeted in Malaysia?

    <p>Working capital. (B)</p> Signup and view all the answers

    In 2022, how many P2P campaigns were successfully funded in Malaysia?

    <p>24,455. (A)</p> Signup and view all the answers

    What percentage of invested funds in Malaysian P2P lending comes from retail investors?

    <p>89% (C)</p> Signup and view all the answers

    What does conservatism bias refer to in decision-making?

    <p>The failure to adequately incorporate new information into beliefs. (A)</p> Signup and view all the answers

    Which cognitive bias is described as the tendency to favor information that supports existing beliefs?

    <p>Confirmation bias (B)</p> Signup and view all the answers

    How does representativeness bias affect the processing of new information?

    <p>By categorizing new information based on past experiences. (D)</p> Signup and view all the answers

    What is the primary consequence of illusion of control bias?

    <p>Overestimating personal skill in influencing outcomes. (B)</p> Signup and view all the answers

    Hindsight bias is characterized by what mistaken belief?

    <p>Outcomes appeared predictable after they have occurred. (C)</p> Signup and view all the answers

    What is a common result of confirmation bias in decision-making?

    <p>Distortion in how evidence is interpreted. (A)</p> Signup and view all the answers

    Which of the following biases could lead someone to disregard significant evidence in favor of a previously held belief?

    <p>Conservatism bias (C)</p> Signup and view all the answers

    What behavior is indicative of belief perseverance biases?

    <p>Ignoring recent events when forming future assumptions. (C)</p> Signup and view all the answers

    Under Section 3 of the Financial Services Act (FSA) 2013 in Malaysia, what is a key characteristic of a leasing business?

    <p>It involves letting movable property for use in business or economic enterprises. (A)</p> Signup and view all the answers

    According to Section 211 of the FSA 2013, what is the classification of a leasing business?

    <p>A financial intermediation activity. (A)</p> Signup and view all the answers

    According to the context, what is the role of the Finance Minister in relation to financial intermediation activities?

    <p>The Finance Minister may designate persons engaging in financial intermediation activities as prescribed financial institutions if they are not supervised by BNM. (A)</p> Signup and view all the answers

    Which of the following is a typical source of funding for leasing companies in Malaysia?

    <p>Shareholder funds, borrowings from financial institutions, and inter-company borrowings. (B)</p> Signup and view all the answers

    Based on the listed companies, which of the following companies is involved in the Malaysian leasing sector?

    <p>ORIX Leasing Malaysia Berhad (D)</p> Signup and view all the answers

    How do factoring companies provide financing to small and medium-sized businesses?

    <p>By purchasing selected sales invoices at a discount. (D)</p> Signup and view all the answers

    What percentage range of the invoice amount do factoring companies typically advance to businesses?

    <p>70% to 90% (B)</p> Signup and view all the answers

    When is the financing amount from a factoring company typically repaid?

    <p>When the sales invoices are due and collected from invoiced customers. (D)</p> Signup and view all the answers

    Flashcards

    ESG data platforms

    Systems developed to collect and analyze Environmental, Social, and Governance data for credit policies.

    GSSIPS Framework

    A guide for delivering impactful sustainable finance within banks, covering various banking segments.

    Sustainability Risk Management

    Measures taken by banks to mitigate risks associated with unsustainable business activities.

    Behavioral Finance

    The study of how psychology influences financial decision-making in banking and lending.

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    Exclusion List

    A list of business activities that banks avoid due to sustainability concerns and risks.

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    Conservatism Bias

    Tendency to stick to previous beliefs despite new, significant information.

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    Belief Perseverance Bias

    The inclination to maintain beliefs despite contradictory evidence.

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    Confirmation Bias

    Favoring information that confirms existing beliefs while ignoring opposing data.

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    Representativeness Bias

    Classifying new information based on past experiences and stereotypes.

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    Illusion of Control Bias

    Belief that one can influence outcomes beyond their actual power.

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    Hindsight Bias

    The belief that past events were predictable after they have occurred.

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    Information-Processing Biases

    Distortions in how individuals process information leading to incorrect conclusions.

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    Cognitive Biases

    Systematic patterns of deviation from norm or rationality in judgment.

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    Credit Scoring System

    A method used to evaluate borrower creditworthiness based on financial history.

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    CTOS Malaysia Score

    A credit score calculated using payment history, amount owed, credit history length, credit mix, and new credit.

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    Payment History

    Accounts for 45% of the CTOS score, reflecting on-time payments and defaults.

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    Machine Learning in Credit Scoring

    Utilizes algorithms to assess borrower data, economic indicators, and industry data to predict credit risk.

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    Probability of Default (PD)

    A measure used to predict the likelihood that a borrower will default on a loan.

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    Big Data in Credit Risk Management

    Large data sources used in AI to enhance credit risk models.

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    Borrower Data

    Information about the borrower influencing loan decisions, like age and income.

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    Creditworthiness Data

    Scores that assess a borrower's credit health based on payment history and debts.

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    Economic and Industry Data

    External data points affecting business performance and financial health.

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    Digital Customer Information

    Data collected from digital interactions, like social media use, for credit analysis.

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    Psychometric Credit Risk Assessment

    A credit risk evaluation method using psychological traits of borrowers.

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    FinTech in Lending

    Technology innovations applied in bank lending processes, enhancing efficiency.

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    Peer to Peer Lending

    A method of lending directly between individuals without traditional banks.

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    Leasing Companies

    Firms that let movable property for use in economic activities.

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    FSA 2013

    Law governing financial services and leasing regulations in Malaysia.

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    Leasing Business Definition

    Letting or sub-letting property for business use, regulated by BNM.

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    Financial Intermediation

    Activities where financial institutions serve as middlemen between borrowers and lenders.

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    Factoring Companies

    Lenders that finance businesses by purchasing their sales invoices.

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    Pre-agreed Factoring Lines

    Agreements between borrowers and factoring companies on financing terms.

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    Invoice Purchase Margin

    Percentage of the invoice amount paid by the factoring company, usually 70%-90%.

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    Repayment from Customers

    Financing amount returned when invoices are collected from clients.

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    Venture Capital

    Investment from firms into startups with high growth potential.

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    Malaysia Debt Ventures Berhad (MDV)

    A venture capital company in Malaysia providing funding for startups.

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    Peer to Peer (P2P) Lending

    Financing method connecting borrowers with individual lenders via online platforms.

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    P2P Framework by SC

    Regulatory structure for P2P lending introduced by the Securities Commission Malaysia.

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    P2P Market Growth

    Significant growth in P2P lending issuance and financing in Malaysia.

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    Issuer

    A borrower who raises funds through P2P lending campaigns.

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    Retail Investors

    Individual investors participating in P2P lending platforms.

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    Working Capital

    Funds used to manage day-to-day operational expenses.

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    Study Notes

    Sustainable Finance and Bank Lending

    • Sustainable finance is defined as financial decisions that take into account environmental, social, and governance (ESG) factors of economic activity.
    • ESG factors include environmental factors (mitigation of climate crisis, use of sustainable resources), social factors (human and animal rights, consumer protection, diverse hiring practices), and governance factors (management, employee relations, compensation practices of organizations).
    • Sustainable finance impacts bank lending practice by introducing new sustainability risks and impacting bank credit risk.
    • Banks consider ESG risk in credit analysis and decision.
    • Lenders issued $120 billion in sustainability-linked loans in 2020.
    • Sustainable loans are currently a small portion of the global lending market.
    • Growth in sustainability-linked loans (bonds) is projected from $130 billion in 2020 to exceed $200 billion in 2021.

    Recall - Standard, Complementary, Alternatives for Credit Decisions

    • Standard approach to credit decisions includes 5Cs (Character, Capacity, Capital, Collateral, Conditions).
    • Complementary approaches involve behavioral biases in credit analysis and decision, and sustainable lending.
    • Alternative approach includes credit scoring, machine learning, and artificial intelligence.

    Introduction to Sustainable Finance

    • Sustainability risk (ESG) impacts bank credit risk.
    • Banking and finance graduates require new finance knowledge and practice in banking & finance.

    Impact of Sustainable Finance to Bank Lending Practice

    • Sustainable finance introduces new sustainability risks and impacts bank credit risk.
    • Bank Credit Analysis and Decision must now consider ESG risk.
    • Banks can gain benefits like higher loan volumes, new value generation, risk mitigation (higher returns for shareholders), lower cost of funding, and brand differentiation.
    • New skills are required for sustainable lending, and banks are transforming lending value chains.
    • New ESG data platforms, ESG scoring models, third-party data are utilized.

    Types of Sustainable Finance – Debts for Corporation and SMEs

    • Green loans are used for financing new or existing eligible green projects.
    • Sustainability-linked loans (SLLs) are allocated for general business purposes, aligning with the borrower's sustainability goals (e.g., reducing greenhouse gas emissions).

    Impact of Sustainable Finance to Bank Lending Practice (Green Loan Principles)

    • Green Loan Principles (GLP) establish a framework for green loans, based on four core components: use of proceeds, process for project evaluation and selection, management of proceeds, reporting.
    • The GLP emphasizes transparency, accuracy, and integrity of information reported by borrowers.

    Impact of Sustainable Finance to Bank Lending Practice (Sustainability-Linked Loan Principles)

    • Sustainability-Linked Loan Principles (SLLP) provide a framework for sustainability-linked loans, based on five core components: selection of KPIs, calibration of sustainability performance targets, loan characteristics, reporting, and verification.

    Impact of Sustainable Finance on Bank Lending Practice

    • Banks have a key role in financing sustainable transformation, gaining tangible benefits like higher loan volumes, new value generation, risk mitigation, new revenue streams from ESG services, and improved brand differentiation.

    Development of Behavioral Finance in Bank Lending

    • Behavioral biases in credit officers (e.g., overconfidence) impact bank credit risk.
    • Corrective measures include education about cognitive errors, actively seeking challenging information, keeping detailed records and updating probabilities objectively.

    Technologies and Bank Lending

    • Fintech technologies are used for automated credit rating, impacting bank credit processes and decisions.
    • Banking & finance graduates require exposure to new finance knowledge and practices.

    Credit Scoring System – Traditional Method

    • Traditional credit scoring systems use hard information like character, capacity, collateral, and condition of the borrower to determine a credit rating.
    • This is typically through "5Cs"
    • A score is assigned, for assessing credit risk.

    Credit Scoring System – Machine Learning (ML) Method

    • Machine Learning (ML) methods use both hard and soft information along with historical performance data for a more refined credit rating.
    • ML selects algorithms to make these refined credit decisions.

    Credit Scoring System – Artificial Intelligent (AI) Method

    • AI utilizes digital/social, economic, and industry data alongside traditional hard and soft information.
    • This refined big data approach allows for more informed and accurate credit decision-making.

    Development of Fintech in Bank Lending

    • Al effectively enhances credit analysis by allowing more comprehensive and accurate assessment of risk (through strengthening credit scoring, portfolio management, fraud detection.)
    • The volume of big data, available through digitalization, plays a vital role and can thus be optimized to improve credit risk assessment models.

    Non-Bank Lending Organizations

    • Leasing companies let out or sublet assets.
    • Factoring companies finance sales invoices, particularly for small and medium-sized businesses.
    • Venture capital companies invest in new projects or businesses, taking on business risk in return for a share of profits.
    • Peer-to-peer (P2P) lending connects borrowers who need money with lenders who want to make a return, managing the entire process from request to collection.

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    FIN367 Sustainable Finance & Bank Lending PDF

    Description

    Test your knowledge on the application of machine learning in credit scoring. This quiz covers key metrics, data types, and the impact of AI on credit risk management. Assess your understanding of how various factors influence credit scoring systems.

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