Jul 3, 2020

Collibra partners with DNB on its digital journey

William Smith
3 min
Aidan Millar, Chief Data & Analytics Officer at DNB, and Steve Neat, VP Sales EMEA at Collibra, speak about harnessing data to deliver transformation
Aidan Millar, Chief Data & Analytics Officer at DNB, and Steve Neat, VP Sales EMEA at Collibra, speak about harnessing data to deliver transformation...

Aidan Millar, Chief Data & Analytics Officer at DNB, and Steve Neat, VP Sales EMEA at Collibra, speak about harnessing data to deliver transformation.

SN: DNB Bank features regularly in the news for its innovation and how, as a financial institution, it is future proofing itself. Aidan, you personally speak passionately about the need to respond to the digital economy and listen to the voice of the customer. Can you share how your organisation is doing that and what part data plays in it?

AM: Norway is actually a highly digitised society. At DNB alone we have over 90% adoption of our digital mobile bank. DNB has reduced from over 200 branches to just 57 today. The company really understands the need to transform and change the new ways of working in this new digital economy we're in. And when it comes to data, I think there’s also an acknowledgement from the executives at DNB that they understand the need to reconnect with our customers. You may be going digital, but if you're not getting to the data layer, you're not really listening to what the customer is asking for.

SN: What does digital transformation mean to you?

AM: A lot of people talk about going digital. But I kind of reframe this and say going digital is not merely a thing in itself, It's a completely new way of doing things. If you're not going and understanding the data flows in your digital processes, then you're not grasping the key issue, which is to understand how data impacts business value chains.

SN: How do you describe the power and relevance of data to your organisation?

Millar: I think data is central to everything we're doing in DNB. It's a completely new way of doing things, and today, DNB is actually a front runner. We've deployed modern, cloud-based solutions to support advanced analytics for Big Data. And we've adopted Collibra to help us understand the complexity of our data landscape and expose and understand the challenges and opportunities that we have. Collibra’s data governance and data privacy products are helping us accelerate some of the changes that we need to make to become purely digital.

SN: What guiding principles do you use to marry your data program to the bank's wider technology and digital initiatives? Can you give us some insight into how you’ve built your data organisation?

AM: That's a big challenge for most organisations, particularly incumbent banks. My response would be that we started with culture - the way that people think and act towards data. You have to start with the business and make it business-relevant, but it also starts with education. An observation I've made is that there's not enough information in information technology.

SN: Where are you now in your program and what's next for DNB’s data and digital journey?

AM: We're on the third and final leg of a three-year program. It has been a remarkable journey. The first leg was all about positioning and implementing the core data platform, processes and frameworks. The second year was about making it stick and actually getting these operational processes in place and adopting them across the organization. That was actually the hardest part. And the third part is the fun part, which is where most people mistakenly jump to first, and that's about how we're growing the bank. We're now in this third leg of harvesting value using some structured data, and also data quality remediation work that we've done, to really deliver improved customer service and intrinsic value.

Read more about Collibra's work with DNB here.

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Jun 19, 2021

AI and the future of global trade

AI
Tradeteq
trade
Finance
Michael Boguslavsky, Head of A...
3 min
Boguslavsky explores AI's potential in trade finance; could it overcome traditional barriers and usher in a new era of financial transformation?

Artificial intelligence (AI) is becoming entrenched in our daily lives, but the technology is still surrounded by misconceptions and skepticism. Ask the public and they may jump to dystopian scenarios where robots have taken over the world. 

While this makes for a good sci-fi blockbuster plot, the reality is different and more benign. Those products that Amazon suggested you buy? AI. That TV series you were recommended to watch on Netflix? AI. That self-driving Tesla car you crave to take for a spin? You guessed it: AI.

There is no single industry that is not being re-shaped by technology. Until recently, however, there was one noteworthy exception: global trade. Fortunately, that is slowly changing.

The mechanism that underpins global trade – trade finance – is an industry that remains largely paper-based and reliant on manual processes. This US$18tn a year industry is now being influenced by a new wave of technological innovation, including AI.

Exploring the potential of AI in Trade Finance

AI refers to the use of computer-aided systems to help people make decisions or make decisions for them. It relies on large volumes of data and models to make sense of information and draw intelligence. 

In trade finance, AI is helpful in analysing quantitative data, and the repetitive nature of trade finance means that there is a lot of non-traditional data at our disposal. 

This means that when trade finance providers need to assess the risks of funding a transaction, AI models can be a very efficient tool for data analysis and reveal intelligence and risks relating to small companies.

AI helps the industry move beyond traditional credit scoring processes, which are often outdated and remain reliant on historical accounting entries – a barrier that prevents small companies from accessing trade finance and has resulted in a $1.5tn global shortfall. 

Overcoming the barriers

AI can tackle this shortfall by creating accurate credit scoring models. This can include a company’s payment history, measure the risks of funding a transaction, identify supply chain risks, and benchmark them against their peer group.

Trade finance providers can use this information to communicate effectively with their SME clients, ultimately helping establish better business relationships.

Towards a technological utopia?

The adoption of AI has the potential to do a lot of good in the industry, and the industry is in the early stages of radical transformation.

Advances are driven by fintechs as well as a willingness to change. The industry is working together to create new infrastructure for distributing trade finance assets to other investors in a transparent, standardised format. 

The creation of infrastructure is possible due to improvements in technology and integrated across the trade ecosystem in cooperation with banks, insurers, and other industry participants. 

It’s collaboration at its best: together, the industry is using technology to re-shape global trade as we know it.

This article was contributed by Michael Boguslavsky, Head of AI at Tradeteq

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