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Pankaj Arora, Director of Analytics and Customer Insight (Interim), Tesco Bank

As Albert Einstein once said, “I have no special talents. I am only passionately curious.” In fact, I am passionate about unlocking the power of data. This has been the golden thread throughout my professional career. I am fortunate to have spent over 18 years across the globe with market-leading brands in financial services, gaming, retail, automotive, and management consulting. I have always focused on finding a sweet spot between building analytical capability with the right rigor and having the commercial focus to deliver business impact. My educational background in engineering and MBA helped lay a foundation for that.

 

My current role at Tesco Bank is about transforming the end-to-end customer experience using data. In practice, this means developing the best-in-class analytical capability, building high performing teams, and delivering high customer impact through solid ethical solutions. We are one of the first banks in the UK to develop and test machine learning models in credit decisioning. This has traditionally been a territory of rule-based scorecards. We realised that developing strong ML models with a clear deployment route would not be enough to deliver the business case. So, we invested heavily in building model fairness, model explainability, and simulation capability.

 

Before Tesco Bank, my last two jobs have been contrasting, regarding analytical maturity. With PureGym, I built the data function from scratch to fuel their ambitious growth. Whereas, in my prior role with Zeal (market leader in the online lottery in Germany), the challenge was democratising advanced analytics and influencing cultural change towards data.

What stage has your organisation reached on its data maturity journey?

On a scale of chaotic to fully optimised, we are in the middle of the data maturity curve. We have a well-governed data platform actively used for analysis and modelling. However, we still have data trapped in different systems. Trusted and connected data is one of the core pillars of our data strategy.

 

Tell us about the data and analytics resources you are responsible for

I lead the analytics and customer insight function, which consists of about 100 exceptionally talented analytics professionals, covering data science, decision science, data science engineering, and customer insight. The function sits within the customer centre of expertise. A big part of the team is based around our headquarters in Edinburgh, but we hire talent who could live anywhere in the UK. We actively promote diversity (cognitive, gender, ethnicity, education, industry experience, etc) and inclusivity. The team covers different seniority levels, and we have very well-defined job families with clear progression pathways. We also partner with academia and offer summer internships every year.

What challenges do you see for data in the year ahead that will have an impact on your organisation and on the industry as a whole?

Finding and retaining talent (especially data science and machine learning operations) has been a critical challenge for us, and I think this will continue in 2023. We focus heavily on career development and invest in training, hackathons, and innovation projects. This helps with retention, but the data market remains relatively buoyant despite the recessionary outlook. Also, the data industry is usually one of the first to come out strongly from a slowdown, so demand will continue to outstrip supply. Another data challenge is to create a cross-industry framework for AI ethics. The key here is to treat data ethics end-to-end instead of as an afterthought.

Have you set out a vision for data? If so, what is it aiming for and does it embrace the whole organisation or just the data function?

Our data strategy focuses on building enterprise-wide capability instead of pockets of expertise around technology, data, and analytics. We believe that vision of data can’t exist in isolation, and it has to be synced perfectly with the business vision. In the end, there should only be one strategy and one plan.

 

Have you been able to fix the data foundations of your organisation, particularly with regard to data quality?

Given we are in the middle stage of the data maturity curve, we are in a good spot regarding data quality. We have a data management framework, and our data platform is well-governed. However, we fully recognise that ensuring data quality will be imperative as we connect more data sources to our central platform.

Pankaj Arora
has been included in:
  • 100 Brands 2020 (EMEA)
  • 100 Brands 2022 (EMEA)
  • 100 Brands 2023 (EMEA)