Increasing use of artificial intelligence (AI) and explainable artificial intelligence (XAI) is likely to see the banking industry moving towards an environment where the customer owns their data and can easily move between banks or other financial organisations with their historical financial information.
Prema Varadhan, chief architect and head of AI at Temenos, says this is a long-term aspiration that traditional banks may struggle to attain in the medium term. However, the first step was taken with the introduction of the General Data Protection Regulation (GDPR) in Europe in 2018. This far-reaching legislation gives consumers the freedom to choose which providers can access their data, the extent of the information shared, and the time period for which the data can be accessed. Varadhan notes that customers are happy to share data where they see a value in return.
“The introduction of GDPR was an encouraging move forward, but we still have a very long way to go,” she warns.
“Big banks are struggling with transformation. Legacy infrastructures that include off-the-shelf products, outdated systems and insufficient data storage systems are going to battle to keep up as the use of AI and XAI change the financial services landscape.”
How will AI and XAI move banking forward?
- Intuitive platforms that respond to customer behaviour
“On a global scale, the banking industry is seeing increased demand for highly personalised, tailored products that require extensive use of AI. This means banks are no longer able to respond to consumer demands with traditional thinking or traditional products that include pricing structures that ignore the customer’s lifetime value. It’s about having big data and then using AI to derive insights from that data so you can deliver value to the customer,” Varadhan explains.
This means that rather than having four or five banking products that customers must fit into, banks will be able to offer specific customers a unique banking product that caters for their individual needs. In an age where bank fees are increasingly under fire, this technology can be used to drive pricing models that leave customers satisfied that they are not paying for services they neither need nor use.
Varadhan explains that in a highly regulated industry such as banking, the use of AI algorithms must be easily explainable to both regulators and customers. “Ideally you want a system that can be interrogated and interacted with. Temenos moved into the XAI space as part of a natural progression in its digital transformation journey. The thinking is that for every problem, there is an explanation offered, and XAI provides bank customers with an intuitive banking platform,” she says.
- Improved security processes
Once restricted to the domain of sci-fi movies – think Blade Runner – biometrics are very much here, and they are here to stay.
Smartphones that include features such as biometric fingerprints and scan-to-pay apps are already removing the need for customers to carry their bank cards around. This also reduces the opportunity for card fraud.
“An increase in the number of advanced economies also means that new systems such as open banking are becoming more common. Open banking refers to systems which use third-party solutions to provide increased distribution channels, for example, the use of retailers such as Checkers or Spar. This highlights the need for improved security,” she points out. AI is already being used to reduce transaction and card fraud through technologies that profile customers’ normal behaviour based on location, device, transaction frequencies and any transaction falling outside of these parameters is treated as an anomaly. This use of AI to trace fraud is done in real-time and has significantly improved banks’ fraud prevention statistics.
- Customer retention
XAI can help banks better understand their customers’ needs so they are able to decide how to improve bank processes and what steps to take next. When a bank practically applies AI, it can improve the way products are offered with the right pricing structures that account for customer interactions. This means that the bank can use XAI to interpret data so that it can build a clear picture of the customer’s expenditure habits, their budget, and their goals.
“This will eliminate the scenario that has developed where traditional bank models are sitting with a plethora of unprofitable products. AI can be used as a bank’s differentiating factor, creating another channel for customer engagement on a deeper level,” Varadhan says.
- A shift in jobs
The increased use of AI also means a change in the employment spectrum. Contrary to popular opinion, this does not necessarily imply job losses but could rather mean a redistribution of functions and creation of new jobs. For example, between 2000 and 2017, Goldman Sachs US reduced the number of traders at its cash equities desk from 600 to just two; but during the same time frame, the company took on 9 000 computer engineers to ensure that it remained ahead of the technology curve.
Challenger banks hit the ground running
New banks, commonly referred to as challenger banks, are already starting to look at advanced analytics and laying down infrastructure to facilitate this.
“The newer, smaller digital banks have a distinct competitive advantage in that they are able to embrace AI from the outset and are not bogged down by traditional, outdated banking systems,” says Varadhana.
“Ultimately, the industry is moving from one where customers had fewer choices to a landscape where technology and disruption will drive consolidation of banks, the introduction of newer, digital channel-based banking, more choice and more insightful banking.”
Brought to you by Temenos.
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