While AI is the top of technology discussions, there is still uncertainty around it. Aveni recently hosted a webinar ‘AI: Why an executive understanding is so important’, which can be watched here.
It featured a discussion between natural language processing (NLP) scientist Dr Lexi Birch and Aveni COO Jamie Hunter.
Their discussion covered four core topics. These were what AI really is, the main applications of AI within financial services, whether it will really change business and the human factor.
Aveni highlighted five of the key takeaways from its webinar.
Think like a human
The first of these was how AI technology is being trained to think more like a human. They explained that there is a current trend that is leveraging neural networks and deep learning to train the AI to process data in the same way a human brain would.
One of the standard ways to train a machine is through a supervised learning approach. This trains the system with labelled data. An example of this would be giving a neural network the words ‘I have cancer.’ This signal is then propagated across the network and the model can predict if having cancer means the person is vulnerable. If it gets this wrong, the weight is changed by the human and the model improves.
The other method of training a model is with unsupervised learning, which uses unlabelled data. Aveni stated this method is propelling the industry to a new level of performance and capabilities. It also means AI is more realistic and doesn’t need large amounts of human and technical resources.
It said, “From Aveni’s point of view, we depend on speech recognition systems to unlock audio data. We’re able to train useful models with much less data. We don’t need thousands of instances of customers admitting they are vulnerable for the model to learn from it. Instead, we can cluster sentences that have similar properties and with fewer instances of labelled data, create a class label also known as classifier from that.”
Unlocking unstructured data
Aveni highlighted that while financial institutions are fine leveraging structured data like customer and credit data, they are not using their unstructured data as well as they should. This type of data includes audio from customer interactions, videos, emails, PDFs and more.
Communicating with customers is vital for detecting problems and unstructured data gives valuable insights into customer preferences or changes to needs. It also helps the firm better focus on areas that improve the customer experience.
Overcoming bad training data
There are not just positives to AI, there are some challenges firms need to overcome. One of these is inadequate/inaccurate training data. It stated that models can be trained on less data, data is a requirement in all successful AI projects. In some cases, companies struggle to provide the quantity and quality of data needed especially for conversational data.
It said, “Data used to train models can also result in bias. A model is biassed when it provides accurate results for one set of data and inaccurate results for other sets of data. This often happens when the training data isn’t of good quality. For example, transcriptions of women’s voices are less accurate when studies have shown women’s voices are generally clearer. This indicates the NLP models have been trained more on men’s voices than women’s.”
The human and AI relationship
Aveni stated that putting humans at the centre of an AI system is vital. It said, “Firms should leverage artificial intelligence where appropriate, but under human supervision. The most effective AI systems should try to harness the best aspects of both human and artificial intelligence. We call this human+.”
It stated that AI is not suited for scenarios where things change quickly, or problems are not clearly defined. By leveraging humans and AI, they can overcome this challenge. For example, creating models that clearly explain to humans why they are making the predictions that they are making. It should also give some indication of how much certainty they have in these predictions.
Embrace it in the culture
The final major point was that executives need to understand the practical aspects of implementing AI solutions, as well as having realistic KPIs and expectations. Through this, they can better experiment and leverage the benefits of technology.
It said, “Technology is able to drive a culture of innovation, remove blockers, and empower team members. It also encourages collaboration between the company and technology providers. With tightening regulations and growing adoption of technologies like this in the financial services industry, an executive understanding of AI is key. This is the time to explore and participate in AI investments.”
Read the full webinar here.
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