AI Banks Europe Feature Stories

Chetwood’s Jessica Rusu Explains How AI is Used in Banking

Chetwood Financial is a digital bank based in North Wales that has been operating since 2018. They are a challenger bank focusing on using technology to change the way products are designed and sold, aiming to benefit traditionally under-served customers.

Jessica Rusu joined Chetwood as Chief Data officer earlier this year and is passionate about data and risk management in financial services, following the Chetwood mission of using data to help the customer win. She spent the early part of her career in statistics and risk management, working for Ford Motor Company for 10 years before moving on to GE Capital. She has spent the last 6 years before Chetwood at eBay doing e-commerce and data analytics and insights, influencing the corporate analytic strategy.

Here she shares her insights into how AI can best be used in the financial industry and what she thinks the future holds for banking.

Jessica Rusu, Chief Data Officer, Chetwood

How is AI useful in the banking world?

You can use AI for automating the underwriting process, in particular for the unbanked or what we might call ‘thin-file customers’ – customers that don’t necessarily have access to credit. We hope that through the course of using our more sophisticated AI models that we’re able to allow credit decisioning to happen for those individuals automatically upfront and not through some sort of manual underwriting process. The other use cases are chatbots, customer service contacts, and the ability to solve customer problems in real-time. Fraud detection is another very high use case for AI, where we try to make sure that we have all these algorithms running in the background to protect customers and to protect the bank from fraudulent activity that can be detected with algorithms.

Why is it important for banks to have access to and analyse customer data?

We want to be able to offer credit to customers and price for that risk effectively; we don’t want to overcharge or undercharge anyone. So if someone is a higher credit risk and unlikely to be able to pay back their loan then the bank needs to cover for that. We want to get the most accurate price for credit customers and so all of their information really helps us understand how big of a risk they are or whether the customer is creditworthy. Traditionally you’d use credit bureau data from agencies like Equifax or Experian, but also you have your own portfolio of customer behaviour where over time you can start to infer all kinds of interesting relationships from looking at data sources. By bringing this data together you get the most accurate view of customers, in particular of those niche segments that are unbanked. With the kind of algorithms that we’re building now and having access to more innovative sources of information we can hopefully provide more customers with access to credit.

Is leveraging data more useful to challenger banks than traditional banks?

I would say it’s important to all banks, all banks want to be competitive, but there’s going to be a lot more entrenched hesitation to move originations models on to AI machine learning algorithms and away from traditional statistical logistic regression models in larger banks.

In your opinion, when and why did the use of artificial intelligence become popular in the financial industry, banking specifically?

Artificial intelligence has been around for a very long time, since the 1950’s. It has really crept up around us in terms of things that we’ve grown accustomed to like Google searching; when you put in your search terms AI is whats giving you back your results. It’s been around for a while and what’s really made it more tangible is the progress that we’ve had in data storage, data capacity, speed computing etc. All of this has actually enabled AI to work faster and better which is why it’s so much more accessible and why it’s really taking off.

Do you have any predictions as to what the future uses of AI could be?

I predict that there will be a speeding up of the adoption curve in terms of access to credit online, online banking and generally moving away from the traditional high street. I do think that there will be a big pivot to digital banks like Chetwood that are offering complete online banking where you can do everything you need to do digitally through the app and never need to visit a branch. In the past, that may have looked like a disadvantage where the ability to go into a bank and have a conversation was highly valued, but now in this environment, particularly as we’ve seen with Covid,  I think customers are really valuing those sorts of capabilities. And that’s going to speed up the evolution towards digital banks and AI-enabled technologies.


  • Polly is a journalist, content creator and general opinion holder from North Wales. She has written for a number of publications, usually hovering around the topics of fintech, tech, lifestyle and body positivity.

Related posts

Insuretech Company By Miles Announces 5-Year Agreement With Zurich UK

Gina Clarke

25% of Gen-Z Invests in Meme Crypto like Dogecoin

Polly Jean Harrison

Unpacking a Year at Mastercard Through Their 2020 Corporate Sustainability Report

Tyler Pathe