AI Deep Learning for Banks

• Updated on: 2017-05-23
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AI Deep Learning for Banks
As businesses begin to rely more on data-driven Artificial Intelligence applications, the new applications lead to new business issues, security, and privacy concerns. Each bank also needs to have a transparent system for total audit-ability so one can see who did what, and when. Bank can use AI Deep Learning techniques to identify erroneous or incomplete data to avoid misleading decisions.The new AI applications introduce a number of business, security and privacy issues which will have to be addressed. Neural Network, Natural Language Processing, Image Recognition, Speech Recognition and Sentimental Analysis techniques are Deep Learning techniques used in Banks and Financial Services. AI Deep Learning techniques are used to help with anti-money laundering programs, know-your-customer checks, sanctions list monitoring, billing fraud oversight or other general compliance functions, artificial intelligence can:
- Improve efficiency
- Reduce costs and increase profits.
- Make better use of workers’ time and company resources
- Help banks handle their compliance monitoring
- Automate some legal and regulatory work
- Handle most customer service and improve customer experience
- Help in detection of Fraud
- Creates a massive competitive advantage
Bhagvan Kommadi, Founder, Architect Corner has around 20 years experience spanning in the creation of products & incubation of Product Startups. He has done Masters in Industrial Systems Engineering at Georgia Institute of Technology (1997) and Bachelors in Aerospace Engineering from Indian Institute of Technology, Madras (1993).Architect Corner is in CIO Advisor Top 25 Fast Growing AI startups in APAC for 2017. Architect Corner is part of Citi T4I Growth Accelerator.
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Recorded Apr 11 2017 38 mins
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