At Norway’s DNB, chief data officer (CDO) Aidan Millar is leading a team that is transforming the bank through data analytics.
The Norwegian bank created a strategy at the end of 2017 to reshape itself as a bank of the future, with the better use of data at the core. It has embarked on a programme of internal education and now has a data analytics tools set in the Amazon cloud being accessed by its large team of data scientists.
But first off, it created the CDO role. The job entailed transforming the company culture before adopting the latest data analytics technologies.
Aidan Millar took on the role about a year ago. With his background in transformation and data analytics, he embarked on a project to reshape the bank for the future through better use of often data which is often found in silos.
Banks collect huge volumes of data as a result of the digitisation of banking. Not only are customers connecting and consuming services digitally, but the way banks are transforming internally, through things like automation, means an explosion of data. Every transaction by a customer creates data as does the completion of back office processes. But business departments need to be able to access, understand and trust this data if they are to make decisions based on them.
At DNB, it all began when business leaders recognised this. “The bank reformulated its strategy with a view of what the bank needs to be in the coming years,” says Millar. “It decided it needed to focus more on data and decided to recruit a CDO.”
DNB has operations across the world, employing 10,000 staff. It is mainly focused on the Nordic region but has offices in London, Singapore and New York as well as across Europe.
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Millar originally worked in the consultancy sector. About 25 years ago, he worked at Anderson Consulting, before joining PricewaterhouseCoopers (PwC). His first foray into financial services was with Dutch bank ABN Amro.
It was his focus on transformation and data analytics that attracted DNB to his CV, as it embarked on the data strategy. “This was a complete transformation, which is why they employed me,” says Millar.
For him, part of the attraction to the role was the culture he found within DNB bank – one conducive with a transformation of the nature and scale planned.
“I arrived in Norway and was impressed with what DNB was doing as well as the extremely interesting culture. I would say it is one of the few banks I would classify as re-evaluating itself as a startup. It is not stuffy and old, but very flat in structure and dynamic.”
“People sit around coffee tables and solve problems,” he says. A lot of this, he says, is down to the CEO pushing this type of culture, as well as its roots in Norway. “DNB is a very forward-leaning organisation in a very digitised society, with high digital penetration.”
The importance of good data
The top executives also understood the importance of good data. “At the executive level, they realised it is all well and good being digitised – but if you don’t have good, clean data, which you can use to create exploitable assets, there is no value,” says Millar.
Most banks suffer from this challenge because they have a lot of technical debt. “This creates a lot of complexity because you end up creating lots of data silos. You have to figure out how you bring all that data together in one place, and make sure it is good quality and relevant to the analytics you are about to perform.”
This is the genesis of the project. In the project’s first year, DNB has been mobilising a federated organisation to exploit data analytics across the business.
Its first challenge involved changing the culture in the business and educating people across it about what can be done with data. “A lot of people may know what is possible, but when you show them what is really possible, it opens up new ideas and concepts,” says Millar.
On the technology side, DNB has implemented Collibra as well as a data quality management tool that connects to it, known as Trillium. Collibra is a centralised tool that brings all the data to a central place where the company can understand it. Everybody in the organisation can then find, use and trust the data.
DNB has these and other data analytics tools in the Amazon Web Services cloud, which is accessed by its data scientists.
Advanced analytics tools
Millar describes these as very advanced analytics tools that can be used which remove the need for programming. “Providing you have good data, it can just be fed into the tools which, through machine learning, do a lot of the algorithmic modelling you had to do yourself in the past.”
“We deployed some leading edge technologies – to get the full context of how we use data in our organisation. That supports our ability to understand how we can reuse some of our processes.”
For example, risk and finance do a lot of the same things, but they don’t talk to each other. These tools mean different parts of the bank exploit the same data sets. Millar says the company is starting to exploit new concepts that the different teams are coming up with.
A lot has been achieved in the first year, with the creation of a data-driven culture – where people understand data – at the top of the list. It also implemented a policy of data ownership so different groups in the bank understand what data they create and how it can be used.
The bank recently hired an extra 50 data scientists, such is its appetite for data-driven transformation.