Finance and Deep Learning

Deep Learning has fast become the new asset in business, influenced by the impressive achievements of start-ups and researchers; large companies, industry leaders, governments and other organisations are rapidly adopting this new technology, seeking competitive advantage in existing applications and an enabling technology for new ventures. 

Rather than focus on task-specific algorithms, Deep Learning teaches computers to learn by example from the training data that they are given. From identifying the contents of an image, turning speech to text (Siri, Cortana, Google Voice and Skype Translate all use Deep Learning), identifying tumours in medical imaging, to autonomous vehicles and defeating the world Go champion, Deep Learning is not only finding application everywhere but demonstrating superior results in many domains. Finance is no exception. With the growing amounts of vast data spreading, how will our compute power be intelligent enough to traverse the spreading information for fast, reliable results? 

Many financial companies are already using Deep Learning for financial modeling. NVIDIA’s Deep Learning Institute now offers workshops and labs on combining the building blocks for financial applications: Deep Autoencoders, or hybrids of Long Short-Term Memory (LSTM) and Convolutional Neural Networks show impressive results in prediction/forecasting, anomaly detection, arbitrage strategies, portfolio creation, pricing securities, risk management, outlier identification, and high-frequency trading. 

Neural Networks are not new to the finance industry either, having completely dominated credit card fraud detection since the late 80’s but, as with most Machine Learning, they required handcrafted features (such as charge size relative to card averages) to work well. Deep Learning not only improves the prediction accuracy of these models but learns the whole problem, finding the relevant features by itself.

Deep Learning can also process vast tracts of data, potentially broadening the sources used in financial modeling and related applications. With huge gaps open in the field of financial modeling, there is the possibility for dramatic innovation. Now is the right time to engage with Novatech.

Sounds like an investment?

Our consultation process can help develop your vision for the applications you are creating. Deep Learning is very computationally expensive and training is almost exclusively done using specific graphics cards, or purpose-built servers. We can help in decreasing your development timescales, introduce you to third parties like NVIDIA and IBM via access to their engineers and software teams, and of course give you access to the hardware with our Proof of Concept where you can trial the hardware free of charge for up to two weeks whilst supported by our engineers and data scientists.

How Deep Learning is utilised is up to the client. How they use it is and the directions it could transport the finance industry into will only be evident as we progress with working more with the technology and developing it into an efficient, intelligent tool.

How could it help you? Ask Novatech and find out. Don’t pay with a loss. Win with Deep Learning artificial intelligence today. 

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