Algorithm and Model based lending


Reserve bank of India Governor Shakitkanta Das has cautioned banks and NBFC’s against being over reliant on algorithms and model-based credit appraisal and lending, especially at the time when increased collaboration with FinTech is facilitating the introduction products and services.


Algorithms and model-based lending refer to the use of sophisticated mathematical models and algorithms to assess creditworthiness, determine lending risk, and make decisions about granting loans. These approaches leverage vast amounts of data to predict the likelihood of repayment by borrowers.

Here's how it generally works:

Algorithms in Lending:

  1. Data Collection: Various data points are collected, including credit history, income, employment status, debt-to-income ratio, spending habits, and more.
  2. Model Development: Advanced statistical models, machine learning algorithms, or a combination of both are used to analyze historical data. These models learn patterns and correlations between various factors and repayment behavior.
  3. Risk Assessment: The models then assess the risk associated with lending money to an individual or a business. They predict the probability of default or late payments based on the collected data.
  4. Decision Making: Lenders use these predictions to make informed decisions about whether to approve a loan, the amount to lend, and the interest rate to charge.


  • Efficiency: Algorithms can quickly process vast amounts of data, leading to faster decision-making.
  • Accuracy: These models can identify patterns and correlations that human underwriters might miss, potentially leading to better risk assessment.
  • Consistency: Decisions are based on predefined criteria, reducing biases that might affect human judgment.

Challenges and Considerations:

  • Data Quality: The accuracy and reliability of predictions heavily depend on the quality and relevance of the data used to train the models.
  • Interpretability: Some complex algorithms might lack transparency, making it challenging to understand how they arrive at specific decisions.
  • Fairness and Bias: Algorithms can inadvertently perpetuate biases present in historical data, leading to unfair lending practices.

Regulatory Oversight:

Regulators often scrutinize model-based lending practices to ensure fairness, non-discrimination, and adherence to laws protecting consumers from predatory practices.

Overall, while algorithms and model-based lending can improve efficiency and accuracy in credit decision-making, it's crucial to continuously monitor and refine these models to ensure fairness, accuracy, and compliance with regulations.

NBFC stands for Non-Banking Financial Company. These are financial institutions that offer various banking services similar to traditional banks but operate without a banking license. NBFCs play a vital role in the financial system by providing credit, investments, wealth management, and other financial services to individuals and businesses.

Characteristics of NBFCs:

  1. Lending and Credit Facilities: NBFCs offer loans and credit facilities like banks, but they cannot accept demand deposits, which means they cannot issue checks and drafts that are payable on demand.
  2. Investment Activities: They also engage in various investment activities such as buying and selling stocks, debentures, bonds, and other market instruments.
  3. Wealth Management: Many NBFCs provide wealth management services, including portfolio management, financial planning, and investment advisory services.
  4. Financial Intermediation: NBFCs act as financial intermediaries, channeling funds from lenders to borrowers, though they do so without being part of the regular banking system.

Key Differences from Banks:

  • Deposit Functions: Unlike banks, NBFCs cannot accept demand deposits from the public.
  • Regulation: While they don't fall under the direct purview of traditional banking regulations, they are regulated by the Reserve Bank of India (RBI) in India or equivalent regulatory bodies in other countries.

Types of NBFCs:

  1. Asset Finance Company (AFC): These companies primarily finance the purchase of physical assets such as machinery, equipment, vehicles, etc.
  2. Investment Company: They invest in securities issued by the government or corporations.
  3. Loan Company: These NBFCs provide loans and advances.
  4. Infrastructure Finance Company (IFC): They specifically cater to the funding needs of infrastructure projects.


  • Financial Inclusion: NBFCs often serve segments of the population that might not have access to traditional banking services, thereby contributing to financial inclusion.
  • Diverse Financial Products: They offer a wide range of financial products, which adds diversity and depth to the financial system.

NBFCs play a significant role in providing credit and financial services to various sectors of the economy, complementing the functions of traditional banks. However, due to their unique characteristics, they are subject to specific regulations to ensure financial stability and protect consumers' interests.

Posted by on 23rd Nov 2023