Meet Sinead Okosi, Head of Data and Analytics

At Pepper Advantage, we're committed to building centres of excellence, made up of talented individuals that embody a can-do spirit.

This week, we shine the spotlight on Sinead Okosi, Head of Data and Analytics who joined the Pepper Advantage team in 2021.

Sinead is responsible for the strategic enhancement of data and analytics across all business units. Since joining, she has built out a range of innovative data solutions that provide our customers with powerful insights and support the business globally.

Tell us a little bit about what you do.

I’m the head of data and analytics for Pepper Advantage. I am responsible for building data solutions for our business and leading the global data team, which is an essential part of our work. So what do you need to do, what sort of structure do you need to create to make sure all our datasets work together? What sort of policies and tools need to be set up both to ensure the right access for the right people but also keep your data secure? How do we turn our data into information people can use? These are the sorts of questions we are constantly asking and solving for.

Can you tell us about your career path?

I’ve been working in financial data and analytics for 10 years now. I started at a competitor as a client service analyst. It was the start of my journey into the financial data world. From there, I moved from client-facing to a role in the business intelligence team.

At the time, there were two main roles in the Client Services team: business analyst or project manager. I moved into programming by joining the Business Intelligence team after spending a year working with the COO to support the management and analysis of his budget. I have a maths background from University, and I loved the idea of bridging the gap between the credit management and business intelligence sides of the business using data. I did that for three years before moving to a specialist bank to create its entire BI function. That involved creating the data and business intelligence systems from scratch, as well as building the team to construct and maintain those systems. We built a new data warehouse, a data governance system, and rolled out a business intelligence strategy to support the growth of the bank. It was a huge challenge that prepared me well for my role at Pepper Advantage.

What brought you to Pepper Advantage?

My previous roles focused on credit risk, and arrears management across multiple asset classes which has given me insight into the world of credit management. I was approached by Pepper Advantage to build a data strategy and develop innovative data products for the European business, which sounded exciting, and I jumped at the chance.

We started by creating a data warehouse in Spain, with an eye to building things out to include the UK, and Ireland, which evolved to encompass Asian as well as European markets. So all of a sudden I was looking at building an even more international strategy and team.

That sounds like a big shift. Can you map it out how you tackled it?

Step-by-step and country-by-country. We had so many different elements we needed to build, so we ended up looking at which market provided us with the best proof of concept. Spain was a great country for us to build our first data warehouse. It’s a relatively new business and we were able to pilot things quickly in a European-regulated market and figure out how best to manage and archive metadata. Then we took those lessons and applied them to other markets, like the UK and Ireland. You could almost describe the process as setting up a single global strategy by creating different pieces and stitching them together.

In India and Indonesia, there was an even bigger learning curve for me as we were building out a team as well as the data solutions. Now the team is in place, everyone is eager and hungry to show what we can do, and we can move quicker as we do things like build out development patterns. We’re in a position from a platform and people perspective to create something extraordinary.

What was your biggest challenge?

The initial challenge was the amount we had to do in a short space of time. Now it’s more about communicating and coordinating across so many countries and harmonizing so many different types of data.

We’re tackling this by creating standard data definitions across all of Pepper Advantage, but making sure those definitions – what we call symbology – are flexible enough for each market to tailor as they need to. It’s like creating one data language with multiple dialects – we set some principles that are universal, but each market has the flexibility to define critical data sets in its own way. As long as teams are sticking to core principles, they can own their local symbology. That’s proving to be very effective.

What are the top three lessons you learned over this process?

1. Quality over speed – trying to move quickly tends to mean you’ll have to rework things if you don’t have the right resources behind you from the start. Quality first means you won’t have to redevelop second.

2. Think about what you say yes to – choose the right time to start projects. Trying to do everything at once will only slow you down in the end as we have to prioritise resources and balance global and local needs.

3. Adopt key champions in the business – find someone who can be the face of your strategy locally, a product champion. Get someone on the ground who understands what the local use cases and needs are, someone who can tell you whose input you need. They’ll help ensure you think through everything you need to.

What’s next?

Getting more clients onto our platform. We’re focused on how operational teams will use our data, so we create the user experience and visualisations they want. Clients have seen the new way they can view their own data sets with more interactive reporting, and now we’re providing them with operational views of their underlying portfolios. Next, we’ll be adding broader macroeconomic data. Ultimately, we’re building a workspace for clients to leverage data science for credit management.

What does success look like?

A fully self-service platform focused on credit and economics that can answer any question from any client about the markets we operate in, no matter how technologically savvy they are.

And now for something completely different: what would people be surprised to know about you?

I became an aunt when I was four weeks old.  

What was your first job?

I was a hairdresser. I still am sometimes.

Find out more about Sinead Okosi’s background here.