• Edwin Hui, Executive Director and APAC Data Lead
  • Published: 08 February 2022

TIME TO READ: 4 minutes

While you might think the spotlight on data has shifted to the likes of Artificial Intelligence and ESG, data is still the ‘fuel and foundation’ of financial services – and indeed is an integral part of the latter. Without question, there is still work to be done to deliver the lofty promises of data innovation.

Below are the key areas of data opportunity that we believe companies should pay attention to in 2022.


ESG is one of the hottest topics across all industries right now, especially after COP26.

We expect regulations around ESG to become stricter and the granularity of required reporting to become ever finer – and by extension more onerous – in the near future. Also, compliance requirements aside, the public are becoming more focused on ESG and a company’s ability to present (data) validated credentials that prove they are genuinely green and fulfilling their social responsibility – for example in respect of Net Zero – will be a clear competitive advantage.

The challenge for financial institutions is that the necessary data – whether relating to assets that are traded or financed, to companies within supply chains, or to firms’ own clients – is too often incomplete, contradictory or even non-existent. Nevertheless, companies will be expected to accelerate their feasibility studies, and know how and where to collect data and assimilate this into the firm’s internal data infrastructure to feed their corporate ESG strategies. This is a key area that will pick up pace in 2022.

To learn more about Capco’s global ESG programme, please visit our dedicated microsite ESG: Defining the future of sustainable finance

Data governance

While not a new topic, work on data governance will continue to be a priority in 2022.

This initiative was first instigated by the banks, due partly to stricter regulatory reporting, but more recently has become a focus for most insurers. Firms recognize that at different stages of their innovation journey there needs to be a very clear strategy and governance structure for data, otherwise it will create challenges later in the journey. A good analogy is the foundation of a house, which must be solid before you can build on top.

Even in the case of those banks that have kickstarted their data governance programs much earlier, we observe that there is still work to be done to ensure these high-level governance principles actually address issues during the execution of day-to-day business.

Insurers, on the other hand, have a latecomer advantage and can benefit from the lessons learnt and best practices established by their banking counterparts. They have a real opportunity to implement data governance in a ‘cleaner’, smoother way.

Operation Optimization

If Elon Musk and Jack Ma once disagreed on the role of Artificial Intelligence, that now seems like the distant past now, with banks and insurers readily embracing AI as part of their automation journeys.

The core issue preventing a wider adoption of automation technology is usually attributed to there being no single automation platform that can address most use cases, which needs to intertwine different capabilities like optical character recognition (OCR), natural language processing, image/video recognition and robotic process automation, to name a few. Big technology vendors like Google and Amazon ventured into this space early on, but the fact that some financial institutions still want their applications to be hosted on-premise makes cloud deployment a no-go in many cases. Also, in APAC there is of course the requirement for local language support (in many Asian languages, each word is a unique character of its own and that there is no space between each word in a statement), which makes an all-in-one platform even harder to achieve.

Despite these challenges we expect to see firms dive deeper into this area, mainly due to the cost savings that can be achieved down the road. The initial mode of deployment is likely to be highly specific in the short term – for example, automated address checking during customer onboarding. As we see greater maturity, firms will and should consider looking at the future organizational setup where virtual workforce becomes the norm.

Amazon is an example of a pioneer in this space. As they are adopting more and more automation into their processes, they employ a very aggressive re-training plan and go further, offering cash incentive to staff who quit their jobs and start their own businesses.

Data Privacy

Data security has long been a key principle within the overall data governance structure. In the past it was more concerned with the unauthorized access of data by staff. However, with the significant increase of data sharing across different companies and the advent of GDPR requirements, data privacy starts to become an independent program of its own, separate from the enterprise data program.

Another notable trend is how the use of personal data to gain a competitive advantage has suddenly becomes a sensitive topic. For instance, the Chinese regulatory body issued draft regulations in the second half of 2021 aimed at tackling unfair competition through the use of data. This has raised concern over the big internet providers and financial institutions alike, as they now need to study what can be done and what cannot be done. In 2022, we expect firms to continue to invest and study the implication and boundaries that are set forth by the regulations and follow up with remediation actions.

One final point to touch on: there needs to be a more industrialized approach to building up a far larger and diversified pool of data talent. In the short term, a shortage of data skills across different geographies and markets, and the inevitable fierce competition for talent, will remain a big challenge. Capco’s
Associate Talent Programme and Associate Data Programme is just one way in which Capco are helping develop the data experts of the future.

In conclusion, we recommend financial institutions take a pragmatic yet holistic view and plan on what should be done with data in 2022, with the right prioritization, in consideration of the talents available and existing business strategies. We expect the above-mentioned topics of ESG, data governance, and process optimization will be in the agenda for most institutions in 2022 and could each become a multi-year program of their own.