Credit algorithm: controversies

Credit algorithm: controversies.

Definitions :

        Let’s first define both terms of the subject :

• Controversies refer to disagreements and arguments about something, an object, a system or an opinion.
• Credit Algorithm, also known as “credit scoring algorithm“, is an algorithm mainly used by financial institutions that are lending money such as banks. It allows them to analyse the creditworthiness of individuals and businesses. It is important to underline that there are several different credit scoring algorithms (the most well-known are FICO or VantageScore). Also the lenders can create their own credit scoring algorithm depending on their preferences, their type of credit but also the amount of money they may lend.

How does the Credit algorithm work ?

        It checks a lot of information about the individual and gives him a score according to this data. Then, it is able to simulate the situation and determine which amount of money a client might be able to repay and if he will respect the financial obligations. The algorithm is using multiple factors to calculate the creditworthiness of an individual which are :

• Credit history : This includes information about previous loans, credit cards, and other credit accounts, including their payment history, outstanding balances, and any late payments or defaults.
• Credit utilisation : This measures the ratio of credit used to available credit. (Lower utilisation ratios are generally seen as more favourable.)
• Length of credit history : The longer a person has a credit history, the more data there is to assess their creditworthiness.
• Types of credit : A mix of different types of credit, such as credit cards, instalment loans, and mortgages, can have an impact on credit scores.
• Utility Services : Utility companies, such as gas, electricity, and cable providers, may review a person's credit history before establishing service. A positive credit history can help in obtaining these services without a deposit.
• Recent credit inquiries : Frequent credit applications or inquiries within a short period can negatively affect credit scores.
• Public records : Negative events like bankruptcies, liens, or judgments can significantly lower credit scores

While many people see credit algorithms as AI, actually it is not. Indeed, it is more of a statistical model with various mathematical principles. The data are already defined and registered by the lender, the algorithm will only generate calculations and return a simple score which corresponds to a credit score. Then it will be the lender who will convert the score into the creditworthiness degree of the client and after that, will decide whether or not he should lend money. However, financial institutions have started incorporating AI to complete the credit score and enhance their credit risk assessment processes. In fact, AI can be used to analyse non-traditional data, patterns or trends (for example : social media activity, online behaviour …). These factors were not captured by the credit scoring algorithm but lead to more accurate assessments of creditworthiness.

In which cases the credit score might be required and used for ?

Credit scoring algorithms are used in order to make a credit in differents banks or firms, but on the other hand, it might be asked in particular situations such as :

• Loan Approval : Lenders use credit scores to determine whether to approve loan applications, such as mortgages, auto loans, personal loans, and credit cards. A higher credit score often leads to more favorable loan terms, including lower interest rates and higher borrowing limits.
• Credit Card Issuance : Credit card companies use credit scores to assess the risk of potential cardholders. Applicants with higher credit scores are more likely to be approved for credit cards with better rewards and lower interest rates.
• Rental Applications : Landlords and property management companies may check an applicant's credit score as part of the tenant screening process. A good credit score can improve your chances of being approved for a rental property.
• Insurance Premiums : Some insurance companies use credit scores as a factor in determining auto and homeowners insurance premiums. Higher credit scores may lead to lower insurance premiums.
• Utility Services : Utility companies, such as gas, electricity, and cable providers, may review a person's credit history before establishing service. A positive credit history can help in obtaining these services without a deposit.
• Employment : In some cases, employers may request permission to check an applicant's credit report as part of the hiring process. This is more common for positions that involve financial responsibility or access to sensitive financial information.
• Renting a Car : When renting a car, the rental company may inquire about your credit score. A higher score may lead to more favourable rental terms or reduce the need for a deposit.
• Financial Planning : Individuals use their credit scores as a measure of their financial health. It can help them understand their creditworthiness and identify areas for improvement.
• Financial Decisions : Credit scores can influence financial decisions such as applying for new credit, refinancing loans, and consolidating debt. A good credit score can lead to better options and lower costs.

As a conclusion, maintaining a great credit score means to manage one’s finances and may lead to better loan terms or allow a nice financial flexibility.

Controversies. 

Even though credit scoring algorithms and credit assessment AI are such a useful tool for lenders, they have been the subjects of controversies and heated debates. Most concerns relied on :

• Fairness and Bias : The real concern is about the historical data, while the algorithm will be totally objective, previous data may have been biassed. So if this case has ever happened, the algorithm might perpetuate and even amplify those biases. This will lead to unfair and discriminatory outcomes.
• Lack of transparency : Algorithms and AI are unreadable for common humans so individuals are unable to understand exactly how their credit score is calculated and cannot really challenge the result nor can they complain about unfair decisions.
• Data privacy : The algorithm and especially the AI (if used) will check and analyse every available data which may infringe one’s privacy rights.
• Accuracy and accountability : Some are sceptical about the ability and the reliability of the AI. It is understandable because algorithms and AI are nor infallible, bugs and errors might happen so many won’t put too much trust in this system.
• Access to credit : Several persons are also reluctant to give their data and sometimes find their demand denied because of an algorithm they cannot neither control nor argue with.

On the other hand, the Consumer Financial Protection Bureau (CFPB), tries to convince these persons with regulatory bodies, consumer advocacy groups and the development of guidelines and standards that will promote responsible and ethical AI in credit scoring. Additionally, there are also researches conducted in order to reduce bias in algorithms and increase the transparency in AI decision-making processes.

What are the social and environmental impacts ?

Credit scoring algorithms could not possibly directly affect social or environmental issues but for sure it indirectly causes several consequences.

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