The National Bank will protect Kazakhstani citizens from the leakage of personal data.
Author - Mansur Ismagulov
The Tech AI
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At the CEVF 2024 National Payment Forum, Kazakhstan's National Payment Corporation and startup Zypl.ai signed a memorandum of cooperation in the field of AI. The partnership aims to utilize Zypl.ai's synthetic data for the secure processing of confidential financial information without the risk of data leaks, enabling the scalable application of artificial intelligence with zero risk to customer data security.
At the CEVF 2024 Venture Forum, the National Payment Corporation of Kazakhstan and the Zypl.ai network signed a memorandum of understanding on cooperation. The interaction will take place in the field of research, development, and implementation of advanced AI algorithms and innovative technologies in the financial sector.
The startup Zypl.ai specializes in creating AI-based software. Its collaboration with the National Bank is an important step for the financial market. It is no secret that the development of artificial intelligence is currently accompanied by the consumption of large amounts of data. And the latter are mainly taken from the cloud. It is difficult to ensure data security there, and in the financial market this is complicated by the fact that their data is considered confidential.
Representatives of the National Bank confirmed that when processing data, it is often necessary to access closed systems with high levels of security. This is necessary so that no one can find out the credit history and other data of bank clients.
The company Zypl.ai is known for its breakthrough in the field of synthetic data generation. Such data fully reproduces real data, but is considered generated if you take each individual person from these synthetic data. Based on them, you can do large-scale things with minimal costs. Thus, the signing of a memorandum between the National Bank and Zypl.ai will allow cooperation in synthesizing data and applying AI to a large number of existing confidential data, but with zero risk to the confidentiality of these data.
Source: er10.kz
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