Jessica Rusu, chief data officer, Chetwood Financial

How is your organisation using data and analytics to support the corporate vision and purpose?

 

Chetwood Financial is a challenger bank that uses data and analytics to make customers better off. Chetwood has built its technology using low-cost cloud analytics and server-less technologies to enable digital banking.

 

2020 was a year like no other - how did it impact on your planned activities and what unplanned ones did you have to introduce?

 

For customers that were impacted by the Covid-19 crisis, we introduced the ability for customers to take a repayment holiday whereby they were given a reprieve from monthly payments without impacting their credit.

 

Looking forward to 2021, what are your expectations for data and analytics within your organisation?

 

We are introducing several new products - at the heart of this is using machine learning and AI to offer customers the best price, particularly customers under-served by the market.

 

Is data for good part of your personal or business agenda for 2021? If so, what form will it take?

 

Chetwood is the only bank with a reward loan product that actually lowers customers’ interest rates as individuals improve their credit scores. Most banks are not thinking about the good of the customer, only profits. We want to be different and help people build their credit and “reward” customers for managing their finances successfully.

 

What has been your path to power?

 

I have been passionate about data and analytics for c20 years, having first honed my understanding of technology, customer behaviour, and modelling at Ford Motor Company. I gained a broader understanding of risk and macro-economic impacts at GE Capital, where I was responsible for stress testing (testing corporate resiliency to scenarios like the current global pandemic).

 

At eBay, I was responsible for analytics and customer insight where I learned about e-commerce, big data and the ability to embed a data-driven decision-making culture across the organisation, as well as how to build a diverse and talented data team.

 

At Chetwood, as the chief data officer of a challenger bank, I’ve had the opportunity to combine technology and data science to deliver product impact at scale.

 

What is the proudest achievement of your career to date?

 

I had the opportunity to lead a global product and compliance initiative for eBay, ensuring eBay sellers were able to continue to have access to the global markets to grow their businesses. I was able to build a positive working relationship with HRMC and learn about indirect tax, whilst building the compliance product and taking it through a rapid six-month production release. As a result, eBay was able to stand apart from its competitors like Amazon and Alibaba in its relationship with HMRC and continue to allow millions of small and big sellers everywhere to trade in a global market.

 

Tell us about a career goal or a purpose for your organisation that you are pursuing?

 

At Chetwood, I am building a credit decisioning capabilities with “explainable AI” models to offer competitive credit offerings to customers in a different way, exploring new and traditional data sources. This is different from regression-based models that have been used in banking for decades.

 

How closely aligned to the business are data and analytics both within your own organisation and at an industry level? What helps to bring the two closer together?

 

The UK market is at a pivotal point following Brexit and with the digital transformation gaining even further momentum as a result of the global pandemic, forcing customers to do all their banking online. Customer-centricity and designing businesses for scale continues to be the central mission of the chief data officer.

 

What is your view on how to develop a data culture in an organisation, building out data literacy and creating a data-first mindset?

 

It’s important to drive a culture of data-driven decision-making and build technologies that enable data as a real business asset. The diversity of the data team can help drive that forward. Data scientists, econometricians, statisticians, engineers, researchers, insight specialists, and business analysts all play a role in driving the use of data horizontally across the organisation.