FNB to build 1 700-strong data analyst army

Admire Moyo
By Admire Moyo, ITWeb's news editor.
Johannesburg, 01 Apr 2022

First National Bank (FNB) is looking to hire as many as 200 data analysts, as the big-four bank aggressively looks to tap into its rich data assets.

This was revealed by Christoph Nieuwoudt, FNB chief analytics officer, in an interview with ITWeb this week.

With data becoming an extremely valuable resource, Nieuwoudt says FNB already has a 1 500-strong staff complement in its data analytics division, but is struggling to find the requisite skills to fill the 200 vacancies.

Data analytics is the study of data to further interpret and process it to convert it into meaningful insights for making smart decisions.

The increasing interest in the use of data analytics in the banking industry is due to changes in technology, people’s expectations, market structure and behaviour, which prompted banks to put analytics at the core of their business.

Nieuwoudt says FNB is mostly deploying data analytics for fraud detection, risk modelling and credit risk analysis.

The bank also uses the technology to boost its behavioural banking initiatives, something with which the new digital banks are scoring massive success.

“We have got 1 500 data analytics staff in our group, which is not a small number. We think we are the biggest data analytics group in Africa, and we are seeing that other organisations are growing as well. We see that because they are either poaching people from us, or we are competing with them to hire data analytics staff.

Looking for the right skills

“We have very rich data assets, as a retail bank. We have about 10 million customers who earn over R1 trillion a year in salaries, and they spend hundreds of billions at points of sale and other places. It gives us very rich data to work with,” he notes.

As the bank realises the power of data analytics, it recently appointed Nieuwoudt to exploit the vast amounts of data it generates.

“This is a relatively new role − I’ve been in this role for a year-and-a-half; it didn’t exist before I was appointed. I think this is a sign of how data analytics is maturing as a discipline,” he tells ITWeb.

“If you think about the third industrial revolution, which was largely driven by the use of computer technology, companies used to employ chief data officers. Now, with the fourth industrial revolution, and with the rise of machine learning as well as artificial intelligence, a lot of emphasis has shifted to analytics, hence the role of chief analytics officer.”

Christoph Nieuwoudt, FNB chief analytics officer.
Christoph Nieuwoudt, FNB chief analytics officer.

He says this has become an executive position, whereas traditionally, it would have fallen under IT or finance.

While data analyst skills are in high demand, Nieuwoudt laments the skills shortage in SA.

“We have got significant unemployment in South Africa, which is unfortunate. But there is a shortage of IT skills, as well as data analytics skills.”

South Africa is also facing the challenge of emigration of skills, including data analysts, as he points out that the country has been quite strong in producing IT skills. “If you look at the people who are emigrating, you will see it’s a lot of IT people, as well as data analysts. We are still bleeding skills in these areas to other countries.

“We wouldn’t have a strong financial services industry if we didn’t have a strong set of skills. But I think, as an industry, we are not focusing enough on the development of these skills.”

Nonetheless, he says there is hope. “If you look at the focus of universities, a number of new degrees have been launched in fields like data engineering at undergraduate level at a number of universities.”

To retain its data analytics skills, FNB has employed several initiatives, says Nieuwoudt.

“You need to take care of data analytics staff. For example, we have created a data analytics roundtable forum that looks specifically at the needs of this community. We also have chief data analytics officers, other than myself, at other segment and function levels. We have a dozen data analytics officers.

“We are starting to professionalise this the same way people would look at chartered accountants or actuaries, etc, which, I think, is very valuable from a retention perspective.”

Worldwide data reach

Nieuwoudt observes that data analytics is a rapidly-growing field globally. “I guess the competition is not only among financial services firms but different industries. Think about Apple, Google, Amazon, Facebook and the like – they built very big global firms around basically using data and analytics very smartly.”

The fields of IT and data analytics are in many ways related, he says, explaining that whereas IT is involved in the overall technology implementation to support business processes − for example, to run the apps and backend systems, etc − the data analytics staff is more specialised.

There are different roles that deal specifically with data and there are roles that deal with analytics, he notes.

“It’s about using data and analytics to add value to the business, but traditionally, we focused more on things like business intelligence – that would be descriptive data about what’s going on in the business, so people would use things like dashboards and so forth.”

However, FNB moved on from descriptive analytics to predictive analytics and prescriptive analytics, which involves decision-making.

“For example, the bulk of the decisions in a bank are made on an automated basis. From every single payment a bank does − and we do billions of payments in a year − there is a decision model that runs. It decides whether this payment could be fraud or not. It then takes a decision whether to block the payment, or warn the person who is paying that this could potentially be a fraudulent transaction.”

These processes are now highly-automated and this requires specific skills; it’s not purely IT skills, he adds.

“So it requires people with data backgrounds, whether it’s actuarial degrees, maths, economics and statistics, etc.”

FNB is building automated learning algorithms that get better as time goes on. “We need the intelligence to give customers the right offers they need from a money management perspective.”