The rise of automated lending is begun with finbase!

You may have heard of artificial intelligence (AI) and how it is changing various aspects of our lives, from medicine to the automotive industry. Another area where AI is making an impact is finance, particularly automated lending. We will look at automated lending through AI and take a closer look at the impact it has on creditworthiness assessment.

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Traditionally, lending by banks and credit institutions is based on manual credit checks. Loan applications were processed by human employees who checked various information such as credit scores, proof of income, credit history and more. This process was time-consuming and often error-prone.

In 2022, the credit volume of private households in Switzerland will be around 990.93 billion Swiss francs. (Source Statista).

With the advent of AI and machine learning, the lending landscape began to change. Banks and financial services providers are beginning to implement automated systems that use AI algorithms to process loan applications quickly and accurately. This made it possible to speed up the credit decision-making process and increase efficiency.

The use of AI in credit assessment has far-reaching effects on the entire process. Here are some key aspects that are improved by AI systems:

1. Faster Decisions: AI systems can process loan applications in seconds and make instant decisions. This means borrowers will know more quickly whether they will be approved or not.
2. Improved accuracy: AI algorithms analyze a wealth of data points and create detailed profiles of borrowers. This leads to more accurate creditworthiness decisions and minimizes the risk of making bad decisions.
3. Risk mitigation: By analyzing large amounts of data, AI systems can also identify and point out potential risks. This helps lenders protect their portfolio and reduce loan defaults.
4. Automated monitoring: AI can also play an important role during the loan term by monitoring the borrower's financial situation and alerting you to changes or risks.
5. Personalization: AI enables lenders to offer tailored loan offers based on borrowers’ individual financial needs and creditworthiness.

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Although automated lending through AI offers many benefits, there are also some challenges and concerns:

1. Privacy: Using large amounts of data to assess creditworthiness raises questions about privacy and security. It is important to ensure that sensitive information is appropriately protected.
2. Bias and discrimination: AI algorithms can introduce unconscious bias and discrimination into credit decisions when the data they are based on already has biases. The industry must ensure that AI systems are fair and balanced.
3. Lack of transparency: How AI algorithms work can be complex and difficult to understand for the average consumer. This can affect the transparency of credit decisions.
4. Job losses: Automating credit decisions may result in certain banking jobs becoming obsolete, which may impact employment.
5. Reliance on technology: Over-reliance on AI systems could result in the skills of human loan professionals being neglected.

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Automated lending through AI is expected to continue to grow and evolve. In the future, AI systems could become even more advanced and enable even more comprehensive analysis of creditworthiness. At the same time, regulators and the industry itself will need to take action to ensure that the use of AI is fair, transparent and safe.

For borrowers, automated lending through AI means a faster and more convenient way to obtain loans. For borrowers, it enables more efficient lending and risk reduction. Ultimately, the success of this technology will depend on how well it meets consumers' needs while addressing the challenges associated with its use.

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