Exploring the Ethics of Data Analytics

Data collection has become a ubiquitous practice that impacts nearly every aspect of our lives. From social media platforms tracking our online behavior to banks collecting our financial information, the amount of data being collected about individuals is staggering. While the collection of data can bring about numerous benefits, it also raises ethical concerns regarding privacy, consent, and trust.

Data Collection and Privacy

One of the primary ethical considerations surrounding data collection is the issue of privacy. When companies collect data about individuals without their knowledge or consent, it can lead to a violation of their privacy rights.

Trust and Transparency

Another key ethical consideration in data collection is the importance of trust and transparency. Individuals must be able to trust that the companies collecting their data will handle it responsibly and ethically. This means being transparent about what data is being collected, how it will be used, and who will have access to it. Especially where sensitive financial information is being collected, trust is essential for maintaining the confidence of customers. Without trust, individuals may be reluctant to share their data, which can hinder the ability of banks to provide personalized services and improve customer experiences.

The contribution of iFactor Pure Analytics in credit risk assessment

iFactor Pure Analytics relies on advanced data analysis and cutting-edge technologies to provide banks and financial institutions with detailed and relevant information about the current performance and growth potential of a business.

The Credit Intelligence Service is developed under all the strict regulations of European banking legislation, as well as GDPR provisions. This includes protecting users’ personal data by implementing robust security measures and ensuring that data is processed in a transparent manner and in accordance with the fundamental rights of individuals, under the specific consent of the bank’s customer. 

iFactor streamlines multiple essential processes in the loan approval flow (as it is constituted, approved and regulated today), from the collection and processing of data, both traditional public data and alternative (more than 12000 alternative data points) to credit analysis (automating all the eligibility criteria in and the calculation of limits specific to each Bank), up to alerts of potential fraud, or signals of business potential, based on predefined use cases and subsequent monitoring, reporting and interdepartmental collaboration. 

Artificial Intelligence and the vast amount of data collected in today’s digital age have profound implications for society. The European Directive AI Act, particularly Article 5, addresses these concerns by setting strict regulations on how AI systems can be used, especially in the context of profiling and data collection. This article aims to prevent the exploitation of individuals’ vulnerabilities and the use of manipulative or deceptive techniques. Specifically, it prohibits:

• Subliminal techniques that influence people’s behavior.
• Individual or group profiling that could lead to unfavorable or discriminatory treatment.
• Exploitation of people’s vulnerabilities due to age, disabilities or socio-economic situation.
• Creating or expanding facial recognition databases through untargeted image collection.

iFactor is developed and operated in compliance with all regulations imposed by the AI ​​ACT and strict banking legislation. Our algorithms and processes are designed to protect users’ personal data, ensuring transparency, informed consent and respect for all fundamental rights and freedoms of individuals. Our product is dedicated to the ethical and responsible assessment of credit risk, without using practices prohibited by AI ACT Art. 5.