AI in Banking 2019 – Intel

2019 is set to be a big year for Artificial Intelligence in the finance world.

Key Takeaways

  • Advanced analytics and AI are increasingly being used by FSI businesses and should be central to any organisation’s business model transformation

  • 2019 will see improvements in existing AI as firms take steps to improve data quality

  • Collaboration and a shift in culture will be central to the successful evolution of AI strategies in the coming months



Artificial Intelligence (AI) is set to remain one of the key tech trends over the coming year, particularly in the Financial Services Industry (FSI). Offering unparalleled transformative potential, AI should be central to any FSI organisation's business model transformation in the data-driven world.

“As we move into 2019 and beyond, collaboration is key. In order to implement AI in a genuinely effective way, FSI organisations need more collaboration between business leaders and technologists”

So far, we've only seen a fraction of the full scope of advanced analytics and AI, but for financial sector businesses, the benefits are huge. The technology enables organisations to get more from their data, delivering actionable insights in hours or days rather than weeks or months. As well as working more efficiently, AI can help businesses to meet the needs of new regulations such as GDPR. The technology can also help to improve customer service with tools such as AI-powered conversational chatbots along with personalised product offerings based on predictive customer behaviour. On top of that, advanced analytics and AI can also help re-imagine financial services, offering new data-based business models.

So, what's next for advanced analytics and AI in the banking world? The technology will be essential for banks to benefit from the future of Open Banking and PSD2 regulations. While these new rules give challenger banks the chance to compete, they also give traditional banking institutions the opportunity to maximise insights from the new world of standardised data.

The introduction of new regulations also highlights the need for explainable AI. This requires a transparent system where the actions can be easily understood by humans. The aim is to understand exactly how and why AI is making certain decisions. As banks rely heavily on trust, this will be a key area for FSI businesses in the near future. To unlock the full potential of AI, FSI businesses will need to continue to update ageing hardware and software, taking advantage of emerging AI tools.

Organisations will also need to take steps to ensure data quality. This includes consolidating disparate data sources, eradicating duplication and ensuring that data is stored in a usable, standardised format. We’ll also see more jobs being created as a result of the increasing use of AI. As well as more roles centred around ensuring data quality, FSI businesses will need data scientists to help build algorithms and interpret results.

Moving forward, as infrastructure and data quality improves, there will be further advancements in existing AI. For example, the conversational chatbots already used by many banks for customer service, will continue to become more effective, capable of understanding more, and dealing with a wider range of queries.

In order to achieve all of these technological milestones, a cultural shift is essential. It's important that everybody in an organisation understands the role of AI and embraces it. What's more, this change in culture must come from the top down with C-level executives leading the way. As Professor Genevieve Bell pointed out in a speech at the recent Sibos event, it's also important to highlight the human aspect of digital transformation. Businesses must consider how humans can successfully work together with AI.

As we move into 2019 and beyond, collaboration is key. In order to implement AI in a genuinely effective way, FSI organisations need more collaboration between business leaders and technologists. Only then will they will be able to develop successful long-term AI strategies.