Pankaj Arora, head of data science, Tesco Bank

What has been your path to power?

“The only way to do great work is to love what you do.” – Steve Jobs.

I love unlocking the power of data and this has been my mantra throughout my professional life. For me, the data journey only completes when it leads to actionable insights and creates both business and customer impact. This means balancing the rigour of analytics with a commercial lens.

I describe myself as a data leader with a commercial head. After spending 17 years across gaming, fitness, consulting and automotive sectors worldwide, I took on a new challenge to join financial services (Tesco Bank) over a year ago and I am currently leading a hugely talented team of data science professionals. The uniqueness of the challenge comes from an opportunity to leverage Tesco’s biggest asset (Clubcard data) to shape the bank’s digital transformation.

The core of our data science strategy is built around developing stronger, faster, fairer and explainable analytical solutions. We are now one of the first banks in the UK to successfully build and implement machine learning models in credit decisioning. This has been a massive cultural challenge where traditional regression-based application scorecards have been the norm for decades. With compelling use cases in pricing optimisation, demand forecasting and personalisation, analytics is currently on track to deliver exceptional incremental benefits over five years.

Prior to Tesco Bank, I worked with PureGym (market leader in the fitness sector in the UK) to support its ambitious growth plan to double in size in four years. I built the best-in-class data function from scratch to fuel that growth. Previous to this, I worked with Zeal (market leader in the online lottery in Germany) and led the data transformation, which included democratising machine learning models and influencing cultural change towards data and insights.

I am incredibly proud to have led data teams across industries and countries to transform business performance through data-led decision-making.