Data protection needs to be emphasised in the era of Generative AI

Generative AI is a type of artificial intelligence that can create new content, such as text, images, or music, by learning from existing data. This technology has the potential to revolutionize many industries, but it also raises serious data protection concerns.

Both fintechs and traditional financial institutions are shifting their focus from using artificial intelligence (AI) primarily for cost reduction to leveraging its capabilities for revenue generation.

At the same time, we have witnessed one of the biggest risks of generative AI is that it can be used to create synthetic data that is indistinguishable from real data. This could be used to create fake news articles, impersonate real people, or even commit fraud.

Another risk is that generative AI can be used to collect and analyze personal data without people's knowledge or consent. This data could then be used to track people's movements, target them with advertising, or even manipulate their behavior.

To protect against these risks, it is important to emphasize data protection when using generative AI. This means ensuring that the data used to train generative AI models is properly anonymized and that the models themselves are not able to access personal data. It is also important to implement strong security measures to protect the data that is generated by generative AI models.

One of the most promising advancements in this field is the application of generative AI, such as OpenAI’s ChatGPT, powered by deep learning algorithms to generate fresh data samples by recognising patterns within existing data. It has shown tremendous potential to revolutionise various aspects of finance, including risk management, fraud detection, trading strategies, and customer experience.

However, Generative AI holds immense potential for the financial services industry, enabling more accurate credit assessments, personalised customer experiences, advanced fraud detection, and improved investment management.

The advancements of generative AI can bring about positive outcomes for consumers, firms, financial markets, and the overall economy. However, the adoption of this technology also introduces new challenges and magnifies existing risks. Consequently, there is an ongoing debate on how to regulate it to ensure it serves the best interests of all stakeholders.

However, there is a risk of exploiting consumer biases and vulnerabilities, such as misuse of customers’ personal data, if generative AI is not used responsibly.

In summary, while generative AI helps financial institutions to detect and prevent fraud, its impact on consumer protection depends on how it is used and for what purpose. Data protection must remain a priority with robust data security measures, encryption techniques, and anonymisation practices to protect sensitive financial information from unauthorised access. Implementing appropriate access controls and monitoring systems helps mitigate data breaches and maintain the integrity of customer data. 

Dr. Deepak Kumar Sahu, President & CEO, VARINDIA