The advent of online banking has changed the face of the industry but now it’s time to be smarter. Michael Allen, vice-president and  EMEA CTO of software intelligence firm Dynatrace, discusses how AI can be deployed to achieve this. 

 

Online banking problems leading to AI discussion

As their customers have become increasingly reliant on online and mobile services in the past few years, banks have undergone massive transformation.

The ongoing quest to offer better experiences for today’s digital-first consumers has forced banks to transition into software businesses as much as they are financial services providers.

However, a transformation of such magnitude has introduced new challenges, which have seen the banks blighted by increasingly frequent IT failures.

Research has shown that organisations suffered an average of six IT outages in the past 12 months, and we’re certainly no stranger to these problems in the UK.

Frequent reports of customers being unable to access online banking, mobile app failures and issues with payment card transactions are a constant reminder of how often IT failures can impact on our abilities to conduct our daily finances.

Banks have always needed to ensure the systems they rely on work perfectly, every time, whatever customers are using them for.

Dynatrace Michael Allen, ai online banking
Dynatrace VP and EMEA CTO Michael Allen

However, given the recent frequency of these incidents and the consequences for customers in our always-on economy, The Treasury Committee recently issued a report that takes a hard stance on IT failures in the financial services industry.

The report finds the “current level and frequency of disruption and consumer harm is unacceptable” and is resulting in customers being “cashless and cut off”.

With the number of bank branches falling – down 17% since 2012 – ensuring online banking services work perfectly for customers has never been more critical.

 

Banking on the cloud

To prevent these failures from occurring, banks first need to understand what’s causing them.

A major contributor has been the rapidly growing scale and complexity of banking IT environments.

As they’ve worked to improve their digital services, banks have migrated their infrastructure to hybrid, multi-cloud ecosystems, providing the agility needed to innovate faster.

However, they still rely on a range of business-critical legacy systems, adding to the complexity of their IT environment.

Banks have also come under pressure to comply with new rules and regulations like PSD2 and open banking, which have demanded further changes in the way their IT systems are designed.

These regulations demand more external connections to a growing number of third-party systems and services, adding further complexity.

As a result, banking IT ecosystems have become highly fragmented, with hundreds of applications, millions of lines of code and billions of dependencies.

Research shows an average transaction – be it a customer checking their balance, a payment being made, or a bank updating a customer’s account information – crosses 37 different systems or components.

It’s no wonder we’re seeing a near-constant stream of banking IT failures – a single point of failure in this complex delivery chain can be incredibly difficult to pinpoint accurately.

However, compounding the challenge is the fact that banks are relying on a range of monitoring tools as they strive to manage the performance of their IT systems.

This forces them to manually aggregate and correlate data from multiple sources to get a holistic view of their IT environment.

As a result, there’s a constant barrage of data and monitoring alerts that makes it difficult for IT teams to interpret and action things quickly enough to ensure customers always enjoy the experience they expect.

 

Why AI must be built into online banking

While it’s understandable that many banks are struggling to overcome these challenges and master the performance of their modern IT systems, the problems that can result have a severe impact for customers caught up in the chaos.

Banking IT failures can see house purchases falling through, small businesses unable to pay staff, and even gas and electricity services cut off after customers are left unable to pay their bills.

If they fail to effectively manage the risks of their complex enterprise cloud environments, banks therefore risk significant revenue and reputational damage.

To protect themselves at a time when UK customers can switch their provider within a week, banks must be able to cut through the complexity of their modern cloud environments to clearly identify the root cause of any emerging IT issue and instantly understand its potential impact on customers and business outcomes.

They also need the ability to remediate the underlying issue quickly, before it turns into an IT failure.

This can’t be achieved by just improving traditional, manual approaches to performance management – banks need a radically different way that is just as transformational as the change that’s taken place in their IT ecosystems.

Explainable AI and automation have to be built into the core of this new approach, allowing banks to understand the development and impact of any fault in real time throughout their entire stack, and then resolve the root cause instantly before it develops into a real, business-impacting problem.

 

AI can avoid the costs of failure in online banking

With a crackdown on banking IT failures seemingly imminent given the recommendations from the Treasury Committee report, banks really can’t afford to delay implementing a more effective approach to the way they monitor customer experiences and digital performance across their complex IT environments.

While throwing more resources, like additional employees, at the problem might seem like a good resolution in the short term, the long-term economics simply don’t make sense and will never solve the underlying issues.

AI is the only way to unlock the real-time insights into application performance and actionable answers that IT teams need to identify issues quickly, to mitigate the impact on customers and improve their digital experience.

Without the intelligence afforded by AI, banks will be unable to improve their resilience against IT failures, leaving them at the mercy of the enforcement powers held by regulators.