{"id":15327,"date":"2020-09-18T14:11:45","date_gmt":"2020-09-18T14:11:45","guid":{"rendered":"http:\/\/bulletins.bfconsulting.com\/?p=15327"},"modified":"2020-09-18T14:11:45","modified_gmt":"2020-09-18T14:11:45","slug":"big-data-pushing-online-credit-scoring-in-russia","status":"publish","type":"post","link":"https:\/\/bulletins.bfconsulting.com\/en\/big-data-pushing-online-credit-scoring-in-russia\/","title":{"rendered":"Big Data pushing online credit scoring in Russia"},"content":{"rendered":"

We live in a world where data is abundantly available and has become king. With concerns rising over use of personal data, governments were quick to pass laws (e.g. the General Data Protection Regulation (GDPR) and Russia\u2019s Regulation No. 152-FZ) aimed at ensuring consumers that they (and their personal data) would be protected. But Big Data won\u2019t be stopped, and its uses in the financial industry are becoming clearer every day. We see a big example of this with a joint (between Russia\u2019s United Credit Bureau and private company Yandex) machine learning credit scoring project, which aims to calculate a credit score for consumers based on more than 1,000 parameters gained from the behavior of users online. <\/span><\/p>\n

While this may seem alarming at first, several financial institutions in Russia have already tested the system, are using their own similar system or are in the development process. And the Central Bank of Russia is generally supportive of these initiatives, although it does remind financial institutions and scoring companies of their legal obligation to protect personal data. Nevertheless, Big Data is here to stay, and its influence is likely to only become more prevalent in our lives as companies, including financial institutions, find ways to harness its power to maximize efficiency and produce better overall services.<\/span><\/p>\n

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