Customer experience transformation at Macquarie bank brings legacy system retirement as a bonus

Australia’s Macquarie bank builds a data layer on top of legacy IT systems to transform customer experience

Australia’s Macquarie bank has built a data layer between legacy systems and customers, as it attempts to create an Uber-like customer experience.

The creation of a real-time customer experience was the reason the bank embarked on the project, but the ability to decommission expensive and complex legacy systems has become a valuable byproduct.

Using open source database software with big data and machine learning technologies, the bank’s chief digital officer, Luis Uguina, set out to remove friction from customer experiences.

As the retail banking arm of financial services company Macquarie Group, the bank offers personal banking, wealth management and business banking services to over one million customers in Australia.

Without branches, the digital customer experience is everything, Uguina told Computer Weekly. “We are a fully digital bank. We have no branch network and we don’t plan to have any," he added. At the heart of the bank is its mobile app, which offers a wide range of capabilities and uses intelligence to personalise them for customers in real time.

Uguina said the biggest challenge facing digital-only banks is how they manage the customer experience, because there are no humans to fall back on.

“The problem is that through legacy systems you deliver a poor experience, but this does not matter because you basically have a human that is the interface with the customer,” said Uguina. “Whether you are in the branch or contact centre, it is the same experience because a human is involved.”

Here are some potential options for replacing bank legacy systems

Forget changing systems and try to remove complexity. This is what often happens when the people making the decisions are near retirement or can’t stomach a multi-year, multibillion-pound project.

Buy a modern core banking platform off the shelf, get it working, connect it and migrate everything from legacy systems onto it.

Acquire one of the growing number of new banks with their state-of-the-art IT, and eventually move the whole bank onto these modern systems, which can be tailored to the bank’s needs.

Spend money on a state-of-the-art system and make it pay through acquiring other banks and moving them to the platform.

Artificial intelligence (AI) could solve complexity issues. For example, IPSoft’s AI customer service platform, known as Amelia, can read instruction manuals and automated fixes, and could possibly support legacy transformation.

This changes when a bank is digital only, he said. “When you move into the new world, there are no intermediaries between you and the customer, so the service you deliver is key. It is wrong that you deliver the same level of service that the legacy system is delivering.”

To create the ideal customer experience, the bank decided to redesign it from scratch at the beginning of 2016. Uguina said there were two options in how to approach this.

“We could untangle the spaghetti of legacy systems in the back end for the next five to 10 years. But you cannot wait 10 years to improve customer experience because you don’t know what will happen [to customer habits] over that time,” said Uguina.

“We decided to take a completely different approach. Working with the architects and digital teams, we decided to build a new layer on top of legacy systems.”

Known as the customer experience (CX) layer, it isolates the complexity of the legacy systems.

Read more about financial services

The company is using open source software from DataStax and is moving data from many legacy systems to the new data layer, which is currently on-premise, but could move to the cloud in the future.

The project is being done in three phases. The first part involves moving all the data into the DataStax platform.

The second part, which is currently running, involves putting intelligence in the data layer to run processes such as data analytics and machine learning. “Through this, we now have a 360-degree view of the customer and can react to what they are doing. This is a live entity that makes decisions in real time about what to deliver to the customer and when to deliver it.”

Fintechs increasingly looking to AI

Technologies such as artificial intelligence are increasingly being harnessed by financial technology (fintech) companies and the banks they supply. Uguina said what differentiates Macquarie bank from many new challenger banks that are also harnessing technologies like AI to improve customer services is its size and product and services portfolio.

He said many challengers have fewer product lines so creating digital experiences is easier. “When you are an existing bank with over 1.1 million customers, and have a full range of products and services, you have to deliver a full digital experience.”

Achieving a single view of a customer is complicated when you have many products and channels. Many banks end up translating the complexity they have to customers, by making them complete extra steps to get a service.

Legacy systems becoming defunct

The project will eventually lead to legacy systems becoming defunct. “We are putting in the data and building the smart engine, and then we will decide when to decommission systems,” said Uguina, adding that this would probably take two to three years.

Legacy systems are hugely expensive to maintain, and this cost often sucks up a large amount of the IT budget, leaving limited funds for IT that will drive more business, such as improving customer experience.

Big banks have thousands of systems providing current accounts, savings accounts, mortgages, loans and many more. But the banking industry is at a turning point, and the next generation of IT leaders in the sector are likely to be the ones to take on the legacy systems.

Uguina said 80% of transactions that banks process are read only, such as balance inquiries, and processing these using legacy systems is expensive. “By having all the data in the middle layer, we are reducing the running cost of the whole bank because it is much cheaper.”

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