Bringing fashion flair to finance: Kshira Saagar, Chief Data Officer, Latitude Financial Services

Kshira Saagar Latitude

Retailers treat customers like their best friends… Banks and financial institutions, however, treat customers like accounts – the relationship is transactional, both in the literal and figurative sense.

A 15-year veteran data cruncher, Kshira Saagar has a passion for decoding the secrets trapped in the language of the digital world. His love for drawing human insights from digital experiences led him to his most recent role at Global Fashion Group (parent company of online fashion hub THE ICONIC) where he served as Global Group Director of Data Science.

Joining credit card, BNPL, and insurance provider, Latitude Financial in October 2020, Saagar has his work cut out for him, as the fast-expanding financial services group moves to build out its data capability, with the immediate priorities of Open Banking conformance and integration of its latest acquisition, digital-only lender Symple Loans on the cards.

In the lead-up to his appearance at FST’s forthcoming Future of Financial Services, Sydney 2021 event, we spoke with Saagar on lessons he’s drawn from the online retail fashion world, his secret sauce for enabling a better enterprise data culture, and enforcing ethical best practice as algorithms emerge as a dominant force in the workings of business.

FST Media: Before joining Latitude, you served a number of years in the retail fashion industry as the resident data boffin. Firstly, what drew you to the financial services sector, and what opportunities did you see in Latitude to fully ply your trade?

Saagar: As someone who loves to understand how people think and behave, you need the kind and volume of data that can only be found in the retail, finance, or gaming industries. But most importantly, as they say, you cannot lie to your doctor, lawyer, or banker. And with that, the ability to work with true, great quality customer information to build smarter and enriched experiences for them was and is a big attraction for me.

Outside the data and tech, Latitude’s leadership is an amazingly accomplished collective, and the people were so welcoming and kind. What more can one ask for in a new role!


FST Media: The retail fashion sector, particularly for those businesses with well developed online presences, has become adept at utilising their vast consumer data assets to, for instance, tailor product lines, adjust pricing in real-time or provide personalised recommendations.

What lessons can financial services organisations take from the online retailers in fully leveraging their data assets to enhance front-line services? 

Saagar: Retailers treat customers like their best friends, for the right reasons mentioned in the question – personalisation at scale, needs-driven marketing and servicing tailored for customer demands. Banks and financial institutions, however, treat their customers like accounts – the relationship is transactional both in the literal and figurative sense.

While it is good in a sense that banks and financial institutions don’t and shouldn’t be overselling a product, unlike the retail context. What they can do more is provide personalised servicing and more needs-based discovery options.


FST Media: Risk management has become an increasingly important function within financial services, and critical for maintaining customer trust. With FSIs’ growing reliance on external partners and outsourced technology solutions, including cloud and X-as-a-Service platforms, and influx of data assets, the management of risk has become infinitely more complex in recent years.

How can financial services organisations move to reduce operational risk without stifling innovation and data-led transformation?

Saagar: If we look at the risk frameworks as guardrails to ensure safe innovation, then they wouldn’t become bottlenecks or roadblocks. There is a good reason that banks and financial institutions have risk guidelines – and if the intent is well understood, the solutions being designed can be very creative and innovative, while still being compliant.

To mitigate the issue of spaghetti components, a well-intentioned and well-thought-out architectural end state is needed.


This should provide clear guidelines both for new tech and for new workforce augmentation to ensure that anything that is built has the right foundations and guardrails.


FST Media: It’s no secret that sound data governance and literacy are key to building a competitive business. In your view, what does an effective data culture look like in the day-to-day functions of a business?

Saagar: An effective data culture is one where people feel three things are happening every day:

  1. Accessibility – the enterprise feels information and insights are accessible to them when they need it and don’t feel stifled, while also being mindful of “secure access”.
  2. Intelligence – the data and information available is enriched with business smarts to be actionable and useful for the enterprise and the customers.
  3. Reliability – the data, insights, and tools have the credibility of being accurate and up to an expected standard.

With these three in play, data literacy and a data culture become much more widespread and easier to implement across the enterprise.


FST Media: As the tide of data swells within organisations, questions remain as to how financial services can and should utilise sensitive consumer data.

How can financial services balance the want to utilise their full suite of data assets with the need to ensure ethical best practice? Further, what is Latitude doing to curtail data misuse?

Saagar: With the growing volume of data capture and increase in access to AI technology, it is important for organisations to have an AI Ethics Charter that clearly mandates: firstly, what the data can and cannot be used for; second, what kind of decisions an algorithm can make; and then how fairness is constantly measured and corrected in any algorithm-driven decision making.

Latitude is working on defining an Enterprise AI Charter that lays these out, so that it creates the necessary awareness among the workforce and will use it to enforce adherence in the real-world algorithms and machine learning pipelines.


FST Media: Predictive and fully omnichannel services have become somewhat of a ‘next frontier’ in the delivery of innovative front-line services. What hurdles do FSIs need to overcome to deliver these capabilities?

Saagar: The ability to deliver omnichannel predictive services for customers is plagued by the age-old Catch-22 of technology vs reality. Organisations can get down to implementing a good omnichannel use case and put it into operation relatively easily – if, of course, there is a clear end outcome for that capability. However, a lot of organisations are stuck on answering who owns this capability, if the capability can be built or bought and, worst of all, if there is value to all of this.

Latitude believes in building for an outcome. Therefore, in the horse vs cart problem of use case vs technology, we put the use case first and build backwards to get the right technology in place.


With the right support from our Architectural Guild, we can ensure that what we build is not a tumour but a muscle growth in the right place.


FST Media: What makes a great data leader today? 

Saagar: All data leaders deliver dashboards, data pipelines and algorithms as needed.

Good data leaders deliver all the above and sell the value of these outcomes to the business.

Great data leaders do all the above and ensure their teams have intellectually challenging problems to solve on an ongoing basis.


Like any other field, great leaders in the data space not only deliver the outcomes, sell the value of it, but also ensure their teams feel that their work is rewarding and recognised as well as provide them with an option to grow in this fast-growing space to become the next data leader.

A featured keynote speaker at the 2021 Future of Financial Services, Sydney conference, Kshira Saagar will outline a framework for developing AI to deliver scale effectively and efficiently.