How Will Deep Learning Impact the Finance Industry?

Original

Artificial intelligence (AI) is not a new concept, but thanks to breakthroughs in deep learning, recent years have seen a rapid resurgence leading to an increasing impact across many industries.

Finance in particular is seeing significant disruption by AI, as deep learning tools and techniques become more widespread and accessible, companies are using algorithms or 'neural networks' that learn from data, allowing computers to make better predictions and take smart actions in real time.

At the RE•WORK Deep Learning in Finance Summit, in London on 23 September, we’ll explore how AI is revolutionising the financial sector, through stock market prediction and forecasting, robo-advisors, mobile banking, blockchain technology and more. Speakers in both industry and academia will share insights into recent breakthroughs in technical advancements and fintech applications alongside academics and startups sharing their work from the financial industry.

By bringing together key influencers to share cutting-edge research and developments, we can explore how to successfully apply artificially intelligent software to enhance and grow the finance, banking and trading industry.

We’ve rounded up the top 5 topics not to be missed at the summit:

  1. Blockchain, the software that underlies cryptocurrencies like Bitcoin, is a new and potentially transformative computational technology. Experts are applying deep learning in blockchain to move and store data securely and privately, dropping the cost and complexity of financial transactions.

  2. Companies are introducing robo-advisors and virtual banking assistants to simplify communications and offer a more personalised experience for customers, that rely on natural language processing (NLP), data mining and human-like reasoning developed by deep learning algorithms.

  3. Deep learning techniques in financial forecasting and stock market prediction include better methods for uncovering market trends, planning investment strategies, identifying the best time to purchase stocks and which particular stocks to purchase.

  4. Data mining is the intelligent analysis of large amounts raw data, turning it into useful information. In the financial sector, data mining allows businesses to learn more about their customers, develop better marketing strategies, increase sales and decrease costs.

  5. Pattern recognition for fraud detection involves training machines to identify patterns, and make predictions with the help of data mining, to seek out suspicious behaviour. Will advancing techniques in deep learning spell an end to fraud?

Don’t miss out; Join the summit to learn more

The Deep Learning in Finance Summit is a unique opportunity to interact with the data scientists, CFOs, financial regulators, CTOs, venture capitalists and software engineers leading the deep learning in finance revolution. Confirmed attendees include HSBC, BlackRock, Santander, Barclays, JP Morgan, Man AHL and Deutsche Bank, as well as leading academic institutions and exciting new startups.

Join the event to learn from and connect with over 200 industry innovators sharing best practices to improve regulations, security and risk in the financial sector. For more information and to register, visit the event website here.

Discounted passes are available until 29 July! Previous events have sold out, so please book early to avoid disappointment. For more information and to register for the Deep Learning in Finance Summit, please visit the website here.

Suggest a speaker for the event here.

 Read more about how AI is impacting finance
View all upcoming RE•WORK summits here.

Big Data Machine Learning Predictive Intelligence Data Mining AI Assistants Pattern Recognition AI Deep Learning Summit Financial Compliance Financial Forecasting Blockchain Retail Finance Deep Learning in Finance Summit FinTech


0 Comments

    As Featured In

    Original
    Original
    Original
    Original
    Original
    Original

    Partners & Attendees

    Intel.001
    Nvidia.001
    Graphcoreai.001
    Ibm watson health 3.001
    Facebook.001
    Acc1.001
    Rbc research.001
    Twentybn.001
    Forbes.001
    Maluuba 2017.001
    Mit tech review.001
    Kd nuggets.001