artificial intelligence
Day by day, generative artificial intelligence technology is proving its game-changing potential in many industrial and production domains as the software behind it takes on more tasks that are limited to humans.
After seeing this success, the business community around the world began to explore how to adopt generative artificial intelligence technology and use its capabilities to improve work efficiency, develop industries, increase productivity, and complete tasks. High precision, no error, low cost.
The devastating weakness of banking services
While the positive changes that generative artificial intelligence will bring to all walks of life are clear, the technology has serious weaknesses in banking services, and some technologists and ethics experts have expressed doubts about the moral integrity of the technology. and class bias, especially with regard to bank loans.
Algorithmic Discrimination
Some experts in machine learning ethics, transparency and accountability say AI-driven systems in financial services could be dumb, subjective and biased if given the choice of who gets a bank loan, as they could say no Loans. , based on their origin, skin color, gender, and even the social group they belong to, suggesting that algorithmic discrimination will be very evident in bank lending mechanisms.
Benefits and threats to the financial industry
Dr Salim Al-Hajj, an expert in corporate strategy and branding, told Sky News Arab Economics that while generative AI brings enormous benefits to the financial industry, it also faces threats due to several weaknesses. This issue must be addressed before this technology can penetrate. In finance, it is pointed out that artificial intelligence makes decisions based on the analysis of the data it provides, but if the data is incomplete or of poor quality, it can lead to incorrect and biased judgments based on flawed data.
unable to interpret information
Al-Hajj said the lending mechanism employed by banks is a complex one, as each case is studied individually, so decisions are made based on multiple factors, including the applicant’s compliance with regulatory requirements, and the generation of artificial intelligence models It may not be possible to understand and interpret the information. Just like a person, this lack of explanation drives it to make a decision to block a loan based on the social group the applicant belongs to, or even on the basis of his gender, race, or nationality, because all of this would be at the bank’s inability to occur without explaining the reasons behind their decision. Clients, auditors and regulators powered by AI.
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A Legacy That Could Influence Artificial Intelligence
Al-Hajj explained that AI software can inherit and mitigate biases present in bank data and legacy systems so that they do not reflect biases in lending decisions, thereby guaranteeing customer protection and preventing them from ethical violations.
Comply with regulatory requirements and standards
Al-Hajj emphasized that the adoption of artificial intelligence in the financial industry must comply with regulations, legal requirements and regulatory standards, such as anti-money laundering (AML) and know your customer (KYC) regulations, in addition to ensuring transparency and accountability. Invest in strong data governance and monitor for weaknesses, maintaining a strong regulatory framework that keeps pace with developments in the field.
cause of issue
Alan Al-Qarih, a writer and analyst in technology and artificial intelligence, told Sky News Arab Economics that the main thing that has to be understood is that there can be imbalances when things happen . The impact on banking and financial services is caused by customer classification mechanisms contained in bank-approved data that human intelligence is able to disguise to avoid allegations of racial discrimination, but when presented to the AI it actually insists on That would expose an imbalance in the mechanics of how some banks make loans.
Hallucinations are another reason
According to Al-Qarih, the second reason for the push for generative AI to amplify bias in banking and financial services is the “illusion” that the technology still has, which has created many problems in many fields, not just in banking. The department said the matter would help lessen the burden on banks to be held accountable for the imbalance, as the generative AI sometimes generates results that contain some kind of ambiguity by analyzing incorrect results due to “illusions”. Provide data as it deems appropriate.
The Solution to AI Bias in Banks
Al-Qareh said that generative artificial intelligence emerged from research labs only a few months ago, so it must be recognized that the problems of bias and stupidity in banking services can be solved by banks relying on more modern systems and data. It is on the method of classifying customers, pointing out that banks should act quickly to reassure technicians and ethicists of the ethical integrity of artificial intelligence technology, and emphasizing that the problem of discrimination should not be generalized to all banks, because there are a large number of banks. All clients rely on transparent and uniform mechanisms.
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