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Reporting for Artificial Intelligence (AI) and Machine Learning (ML) applications and systems offered and used by Mutual Funds

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..... Intelligence) and ML (Machine Learning) as product offerings by market intermediaries and participants (e.g.: robo advisors ) in investor and consumer facing products. SEBI is conducting a survey and creating an inventory of the AI / ML landscape in the Indian financial markets to gain an in-depth understanding of the adoption of such technologies in the markets and to ensure preparedness for any AI / ML policies that may arise in the future. 2. As most AI / ML systems are black boxes and their behavior cannot be easily quantified, it is imperative to ensure that any advertised financial benefit owing to these technologies in investor facing financial products offered by intermediaries should not constitute to misrepresentation. .....

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..... based application or system as defined in Annexure B , are required to fill in the form (Annexure A) and make submissions on quarterly basis within 15 calendar days of the expiry of the quarter to AMFI. 7. AMFI shall consolidate the information on AI / ML applications and systems reported by Mutual Funds on quarterly basis and submit to SEBI at email id AIML_MF@sebi.gov.in within 30 calendar days of the expiry of the quarter, starting from quarter ending June 2019. 8. AMFI shall ensure that confidentiality is maintained regarding the information received by them from Mutual Funds. 9. This circular is being issued in exercise of powers conferred under Section 11 (1) of the Securities and Exchange Board of India .....

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..... 7.b Does the system disseminate investment or trading advice or strategies? 7.c Is the application / system used in area of Cyber security to detect attacks 7.d What claims have been made regarding AI and ML application / system if any? 8 What is the name of the Tool / Technology that is categorized as AI and ML system / Application and submissions are declared vide this response 9 .....

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..... considered in scope. E.g.: robo chat bots, big data intelligence gathering systems. 2. Neural Networks or a modified form of it. In this case, any systems that uses a number of nodes (physical or software simulated nodes) mimicking natural neural networks of any scale, so as to carry out learning from previous firing of the nodes will be considered in scope. E.g.: Recurrent Neural networks and Deep learning Neural Networks. 3. Machine learning through supervised, unsupervised learning or a combination of both. In this case, any application or systems that carry out knowledge representation to form a knowledge base of domain, by learning and creating its outputs with real world input data and deciding future outputs ba .....

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