As the countdown continues to the NextGen Banking London 2018: The AI Revolution conference, in London (May 17), we examine the rapid move towards Artificial Intelligence (AI) in the financial services industry (FSI) and what organisations need to do to ensure they are not left behind. Not only does AI enable businesses to gain unprecedented insights and address regulatory imperatives, it also allows them to streamline operations and personalise the customer experience. However, it requires not only technological changes, but also a cultural shift within businesses in the financial sector.
The enormous opportunity offered by AI is explored in more detail in a new white paper called "The AI Revolution: Time to get ready", published by Intel and Finextra.1 Central to the paper is the idea that AI is a central component of any banking institution's business model transformation in the increasingly interconnected digital world. The financial sector has taken more time to adapt to the digital landscape than other industries, largely due to the limitations of legacy infrastructure and processes.
In order to unlock the full potential of AI, FSI businesses must update ageing hardware and software, taking advantage of emerging AI tools. The opportunity is significant and wide-ranging, according to the Financial Stability Board (FSB) who stated that the more efficient processing of information, for example in credit decisions, financial markets, insurance contracts, and customer interaction that would be realised by deploying AI "may contribute to a more efficient financial system", provided specific risks are properly managed.
Disruptive AI technology takes a number of forms, from basic Robotic Process Automation (RPA) to more complex processes like cognitive computing and deep learning. AI technologies provide a wide range of use cases in the financial sector, including boosting operations by removing inefficiencies. AI can also give banking organisations a competitive advantage by improving customer interfaces and personalised product offerings based on predicted customer behaviour and needs.
AI technology will also be vital in fulfilling the requirements of new regulatory requirements, such as GDPR (General Data Protection Regulation), which goes into effect from May 25. In particular, RPA will be useful in meeting the new regulations' requirements around regular cleansing of data to ensure that anything that should not be stored is deleted. In addition, RPA may be vital for automating the processes involved with gaining customer consent to use their data, along with any other repetitive processes that are required in large volumes.
Likewise, AI will also be essential to the future of Open Banking. Driven by the new EU Payment Services Directive (PSD2), Open Banking will open up a new world of standardised data and AI will help to maximise the insights that banks and other organisations can obtain from it.
As part of the Open Banking framework, and to make it possible to meet other evolving compliance needs, data must be captured, stored, and shared in a standardised way. And for AI to work to its full potential, it needs usable datasets. That's why it's so important for banking institutions to update legacy systems. As technology evolves, the financial sector has at times been limited by legacy infrastructure, often inherited as a result of company buyouts and mergers. The good news is that, unlike many sectors, the FSI has decades of experience with large datasets and analytical tools. By updating ageing hardware and software and moving towards multi-cloud technology, they can cultivate a suitable framework to implement AI tools.
But re-structuring an organisation to cater for data-driven AI tools isn't all down to technology. It also requires a major cultural shift, with changes emanating from the top of the organisation down. Digital transformation and the implementation of AI should permeate every aspect of the business, and not just be limited to the IT department. New skills and training will likely be required, but enabling access to AI tools across the organisation is vital.
The range of AI tools available to help financial businesses to update their operations is steadily growing. For example, Intel® Saffron™ AI is an AI-based platform that simulates a human's natural ability to learn, remember and reason in real time based on associative memory reasoning technology. By doing this, the platform can find hidden patterns in large datasets that can be translated in actionable and explainable insights. The technology has a wide range of capabilities relevant to the FSI, including credit risk analytics, fraud detection, and improving customer engagement with feedback analytics.
AI is rapidly becoming integral to FSI businesses and those that don't update their infrastructure to support it risk being left behind – in this dynamic landscape, AI can deliver actionable insights in hours or days rather than weeks or months. We've only just begun to scratch the surface of what's possible with AI, but the technology offers huge opportunities. In order to benefit from these, FSI organisations must consider updating legacy infrastructure to support new AI tools and multi-cloud environments.