Questions around this news
What topics were discussed at the Fintech and AI event?
The event covered fundraising and investment in fintech, practical uses of artificial intelligence in financial technology, and the future of wealth management and retail investing. The release also says Google’s team discussed its AI development program. Sends representatives attended to hear from speakers and meet people working in the industry.
What did Sends say about data quality and AI in fintech?
Sends Director and MLRO Anastasiia Pervushyna said that combining fintech and AI can bring risks, and emphasized the value of events where companies discuss both risks and opportunities. One takeaway reported by the release was that AI results depend on the quality of the data provided to the systems.
How can AI be used in fintech?
Artificial intelligence in financial technology can support tasks such as analyzing data, identifying patterns, automating routine processes, and helping tailor customer services. Its usefulness depends on factors including the quality and suitability of the data and how the system is designed and overseen. The release refers to AI use cases as an event discussion topic, rather than describing a specific application.
What does MLRO mean in a financial services context?
MLRO commonly stands for Money Laundering Reporting Officer. The role generally involves overseeing an organization’s anti-money-laundering controls and handling reports of suspected money laundering in line with applicable rules. Responsibilities and formal requirements can vary by jurisdiction and organization.
Sends Team visited the Fintech and AI event hosted by the Google Cloud
New York, United States, August 23, 2023 -- On the 18th of August, Google Cloud organised the event, which covered the topic of Fintech and AI. Representatives from leading tech companies gathered at Google London HQ to share their experiences. Sends team took part as the attendees to get insights, meet industry pioneers and introduce the company.
At the meeting, speakers, moderators, and panelists helped to explore the Fintech Fundraising & Investment Landscape, Use Cases for AI in Fintech, and The Future of Wealth Management and Retail Investing. Google team also dived into Google's AI development program.
“We are at Sends eager to integrate new technologies, especially regarding AI. In 2023 the world saw successful cases of making AI tools for everybody. But the combination of fintech and AI brings many risks. That is why it is important to organise such events where companies discuss threats and possibilities for improving customer's experience and fintech branch, in general, using AI”, said Anastasiia Pervushyna, Director/MLRO in Sends.
One key takeaway was the importance of data and how the quality of AI comes down to the quality of the data you put into the modules. Sigma Financial AI, vabble.io, Veriom, and other leaders performed at the event.
To learn more about Sends, please visit www.sends.co.
*Sends is a trade name of SMARTFLOW PAYMENTS LIMITED.
SMARTFLOW PAYMENTS LIMITED is registered in England and Wales (Company number 11070048).
Contact Info:
Name: Katy Matiashvili
Email: Send Email
Organization: SMARTFLOW PAYMENTS LIMITED
Address: Office 205, Mappin House 4 Winsley Street, London, England, W1W 8HF
Website: http://sends.co
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Terms explained
- Fintech
- A broad term for technology used to provide or improve financial services, such as payments, lending, or investing.
- Artificial intelligence (AI)
- Computer systems and methods designed to perform tasks that typically require human-like capabilities, such as recognizing patterns, generating content, or making predictions.
- Wealth management
- A service that helps clients plan and manage financial assets, often including investment planning and related financial guidance.
- Retail investing
- Investing by individuals for their own accounts, rather than investing on behalf of institutions or pooled funds.
- Fundraising
- The process of seeking money to support a business, project, or organization, often from investors or lenders.
- Data quality
- How suitable data is for its intended use, including whether it is accurate, complete, consistent, and relevant.
