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Focus on data ecosystems
in the era of financial services

Ashvin Parmar
7 September 2022

Constructing data ecosystems has helped financial companies become nimbler and move faster.

When it comes to data, the financial services industry has some of the greatest opportunities but also faces tremendous risks and pressures. As competition increases, along with customer expectations, financial companies are navigating regulatory, security, and privacy minefields along the road to delivering greater innovation.

To successfully make this data journey, finance has become a leading sector in terms of building data ecosystems. As such, it offers critical lessons for companies just starting to explore the possibilities that data sharing can unlock.

“It helps from the bottom-line perspective in terms of bringing greater efficiencies,” according to Ashvin Parmar, Vice President, Insights & Data Practice Leader at Capgemini. “But more importantly, it lays the foundation for innovation. You come up with new products and bring them to market faster.”

Parmar, who works closely with some of the biggest names in finance as well as emerging fintech startups, says the adoption of cloud computing and the shifting economics of data have enabled financial companies to become more aggressive and experimental with how they leverage their data. As the line blurs between traditional financial services and retail experiences, companies know they must rapidly adapt.

“The banks and insurers don’t have a choice but to start to collaborate,” Parmar says. “So, the desire is there to grow and reach new prospects and clients and to service them better. By procuring data from a variety of sources, they can enrich their own data and improve in areas like risk management. They also get a better view of the client and their preferences.”

Constructing data ecosystems has helped financial companies become nimbler and move faster.
For instance, developing robust know your customer (KYC) systems is vital for financial companies from both a security and regulatory perspective to fight fraud and money laundering. But if each company has to build its own KYC platform, it can be costly while offering only limited reach for the data it can access.

A Fintech startup is cutting across this problem, thanks to its neutral KYC platform. This startup has partnered with a wide range of financial players who are sharing their data in its system. Companies that engage them get access to a deeper pool of data without having to create their own algorithms and technology stacks.

“It reduces the cost and you can have better risk management because you’re benefiting from experiences and the data from your competitors,” Parmar says.

Capgemini is working with the fintech startup to create a credit analytics platform that brings in data from a wide range of sources while leveraging Capgemini’s domain expertise in this area, including its risk management model. Parmar believes this joint offering of credit analytics as a service will allow financial firms to remain focused on their core services rather than expending resources on making sure models are up to date and procuring the right data.

Companies can also accelerate their data transformation via 890 By Capgemini, a platform that offers access to ecosystems of industry-specific data that can be combined with exclusive internal data. This curated experience includes data, insights, and outcome exchanges that help companies quickly and securely benefit from the power of data sharing.

Getting started

When a company is ready to take the leap into data sharing, Parmar offers a few guidelines for getting started.

Naturally, a company should have a data-driven culture. But to compliment that, it’s also vital to have a privacy culture.

“Privacy is not just about the technology and the government’s regulations or the processes,” Parmar says. “A culture of privacy has to be there for all the other controls to work properly.”

Capgemini has a lightweight survey created in partnership with leading academics to allow a company to measure its internal privacy sensitivity. The survey delivers a heatmap so companies can see where their privacy blind spots are. That’s the first step toward addressing cultural issues.

From there, companies need to understand their data environment, including its maturity and readiness to undertake data sharing. This should also include a clear inventory of internal IT systems in terms of their capabilities (or lack thereof) for connecting to partners or any type of ecosystem.

Finally, companies need to set clear long-term goals and understand what drives them from a business perspective. Is it data monetisation? Increasing the footprint? These answers will help identify the technology needs and business capabilities required to realise these plans.

“It’s a journey,” Parmar says. “Maybe you start with an internal data marketplace to build your first data exchange platform. And that evolves into an external data exchange. And that morphs into new data products.”

The good news is that once a company is ready to take those steps, cloud providers and hyperscalers now have tools that can help them move quickly. These companies are making massive investments in the technologies and services that are rapidly reducing costs even further and making them more accessible. While the focus was initially on just getting customers into the cloud and saving money, these cloud providers are now offering more sophisticated tools for specific verticals, such as finance.

“If you are a bank, you don’t have to start from scratch,” Parmar says. “There is a tremendous amount of R&D being done to facilitate these data exchanges. The barriers to entry into a marketplace are going away. It’s becoming easier and it’s becoming safer to innovate with data exchanges and data ecosystems.”

Author

Ashvin Parmar

Global Head of FS Generative AI CoE