By Omar Bashir, Technical Director (Financial Services) at Thoughtworks
Artificial intelligence (AI) is already showing its potential in the transformation of Australia’s big banks, from fraud detection to helping employees answer customer questions and software engineers write better code and making smarter apps. In fact, a leading global index recently ranked the Commonwealth Bank as the number one Asia Pacific bank for maturity in using the technology.
As AI technologies become more advanced and regulatory compliance is put into place, there is a need for banks to focus on strengthening their technological foundations and legacy systems; for example, ensuring a data governance framework exists before deploying innovative technologies at scale. Tons of firefighting goes on within siloed teams because existing systems are fragile, making it difficult to scale and be as agile as needed to gain competitive advantage.
While the future is bright, the reality is, banks are not ready to see the full potential of AI – or the new and unknown technologies that come after that.
Why are banks’ tech stacks falling behind?
Australian banks want to be able to implement and test new technological capabilities that will keep their customers ‘sticky’ for the long term. Banks want to continually find ways to engage customers, optimise customer service functions and generally improve brand value. They do not want a lack of innovation and slow access to new, digital services to be the reason for customers to switch, but it is clear some banks struggle to deliver on both counts.
Building new applications, features or even upgrades on top of legacy systems risk creating a jumble of dependencies. To innovate, systems need to be able to adapt to new technologies, and a lot of banks do not employ them. In the case of AI, it is often the case that banks do not have the right quality of data aside from existing legacy platforms being neither scalable nor stable. For AI to become available across the entire organisation, these foundations will need to be in place.
Another underlying cause for banks’ tech stacks to fall behind is many banks approach modernisation and innovation as technology exercises, diverging their outcomes from customer value and how they want their initiatives to deliver. This happens when processes are not aiding business and technology leaders to effectively collaborate which leads to delays in prioritising.
What do banks need to do to get the foundations right?
Fundamentally, banks need to rethink how they rationalise their existing technology estate. This includes legacy systems supporting business capabilities and customer products that have been developed over the life of these systems – sometimes over multiple decades. Many of these capabilities are either no longer relevant to current and emerging business environments, or they have been superseded by newer capabilities better supported by technologies, like AI. Ask yourself: are customers engaging with them? And how are these legacy systems benefiting the business? This intentional strategy will lead to eradicating the technical debt banks have accumulated over the years. The approach will result in banks being able to incrementally apply new technologies suited in the current business environment.
Banks can also benefit from prioritising an engineering culture. This allows them to keep pace with the dynamic technology change and attract the best developers. A healthy engineering culture will also help ensure good engineering practices are followed, will provide a platform to experiment, and empower teams to deliver. For example, continuous integration and continuous delivery should be the norm coupled with automated testing — this will ensure developers don’t waste time maintaining, testing and securing existing code. Additionally, data should be accessible through a data platform with appropriate governance in place.
How is Thoughtworks helping banks in the era of AI?
Thoughtworks see AI as the core play banks and other financial institutions need to embrace in the months and years to come. Doing so will not only help them respond to macroeconomic challenges but also further profitable growth. The available opportunity is driven by what AI algorithms can unlock for banks, such as valuable insights in financial data.
Thoughtworks specialises in empowering organizations to leverage AI and machine learning to solve their most difficult challenges. The global consultancy’s unique approach integrates strategy, design and software engineering to create intelligent, people-centred solutions that augment team’s capabilities and create extraordinary results across vast opportunities. For example, Thoughtworks delivered an open sourced, bilingual language model for a banking customer services solution which reduced the information decay in complaints, thus improving the efficiency of complaints handling and increased customer satisfaction.
For banks, success in AI lies at the intersection of business, people, and technology, and with the right strategy.
