How to set up the process for credit approval

Published on: 2024-08-10 18:37:05

Every new market entrant needs to define its credit approval process. As credit lending becomes more digital and automated, each step is examined and improved.

The general credit approval process has 8 steps:

  1. Application
  2. Verification
  3. Credit Check
  4. Minimal requirements evaluation
  5. Underwriting
  6. Approval/Denial/Counter-Proposal
  7. Documentation
  8. Funding

These steps may vary depending on the loan purpose and the financial product.

Application

At this step, a customer submits an application for a credit product. The application should include information such as name, address, contact details, employer details, income, and other relevant data. The customer must disclose information about their financial standing. The application form collects the information needed to make a decision.

Verification

The lender can start the verification process to check the customer’s details. This can include checking their credit history, verifying their identity, reviewing past payment records, and any other checks needed to assess the customer’s creditworthiness. The bank or lender can also pull additional customer information from third-party sources, such as criminal records, public records, and other financial information.

Credit Check

At this step, the lender checks the customer’s credit report to assess the customer’s creditworthiness. The credit report includes information such as payment history, credit utilization, debt burden, and more. The report then needs to be evaluated to determine whether the customer is a suitable candidate for the loan.

Minimal Requirements Evaluation

At this stage, the lender evaluates whether the customer meets the minimum requirements for the loan. This includes items such as income, employment status, and other criteria. The customer may also need to provide supporting documents such as tax returns or payslips. Minimum requirements are usually defined as KO rules.

Underwriting

Underwriting is the stage where the lender reviews the customer’s application, verifies all details, and assesses creditworthiness. Based on the information gathered, the lender decides whether the loan can be approved. During this process, the lender may use models or algorithms to estimate the probability of default.

Approval/Denial/Counter-Proposal

After the underwriting process is complete, the lender decides whether to approve the loan, deny it, or offer a counter-proposal. A counter-proposal might include a lower amount, a longer term, or a different interest rate.

Documentation

The lender requires the customer to sign the loan documents. This includes contracts, statements, and other records. Documentation matters for potential debt recovery processes or for securitizing the loan.

Funding

After all documentation has been signed, the lender releases the funds to the customer. In consumer purchase credit or BNPL, the funds may be disbursed directly to a merchant.

How the approval process can be improved

The credit approval process can be improved over time by analyzing data from previous loans and identifying potential risk factors.

This is why it is important to have a well-structured process and a system in place to monitor customers’ payments and creditworthiness over time.

It is also important to keep the process efficient and current to reduce approval time and improve customer satisfaction.

Which parts of credit process can be automated

All parts of the credit approval process can be automated.

Application Process

The application step can be automated with an online form that requires the customer to enter their details. Once the data is collected, it is sent into an automated process.

Verification Process

The verification step can also be automated by checking customer records, running credit checks, and verifying customer identities. These checks can range from face recognition to other checks using third-party services.

Credit Check Process

The credit check process can be automated using AI and machine learning algorithms that assess the customer’s creditworthiness more efficiently and consistently than a human. The decision logic is then put into an inference engine, rule engine, or decision engine.

Minimal Requirements Evaluation

The minimal requirements evaluation can be automated by setting up criteria that the customer must meet to be eligible for the loan. These are usually straightforward business rules.

Underwriting Process

The underwriting process can also be automated by using algorithms designed to assess credit risk. These can be simple rules or machine learning models combined with other logical steps such as decision trees or decision tables.

Approval/Denial/Counter-Proposal Process

The approval/denial/counter-proposal process can also be automated. This can be done by setting parameters such as the amount, duration, and interest rate of the loan within a decision engine.

Documentation Process

The documentation step can be automated by having the customer sign loan documents electronically, or by using digital signature technology

Funding Process

The funding process can also be automated by disbursing the loan funds automatically once the application is approved.

What can prevent automating the whole process

Apart from the lender’s technical capability, automation can also be limited by local regulations or by the maturity of digital infrastructure in the country where the lender operates.

Automation depends on local regulations because in some countries the application step, which usually contains KYC (Know Your Customer) information, must be approved manually.

Also, some countries do not allow electronic signatures for loan documents and require in-person contract signing.

What are the required technologies for automating credit approval process?

The technologies required to automate the credit approval process include:

  • Face recognition & comparison technology: To verify customer identity
  • OCR (Optical Character Recognition): To convert documents into digital format
  • AI/Machine Learning Algorithms: This technology is needed for automating the credit check process because it can assess the customer's creditworthiness more efficiently and accurately than a human.
  • Decision Engines: A decision engine is a platform that uses decision logic to evaluate whether an application should be accepted or rejected. It allows automated decision-making based on predefined business rules.
  • Data Gathering: This technology allows the lender to gather the data needed to assess an application and verify the customer's identity.
  • Digital Signature Technology: Digital signature technology allows the customer to sign loan documents electronically. This is needed to automate the documentation step.
  • API Integration: This allows the lender to integrate with other systems and applications, which improves data gathering and processing.
  • Automated Payment Technology: This technology allows automated disbursement of loan funds once the loan has been approved.
 

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