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FCA Consultation Paves Way for Mass Synthetic Data Innovation

FCA Consultation Paves Way for Mass Synthetic Data Innovation | Fintech Finance

Nils Bulling, Head of Strategic Innovation, Ecosystem & Digital Assets at Avaloq, responds to the FCA’s consultation, closing today, on the use of synthetic data to support financial services innovation.

The use of synthetic data has increased significantly in recent years as financial institutions recognize its merits for product innovation in a sector where data security and consumer protection are paramount. But there are still many underutilized applications of synthetic data in the financial industry. The FCA’s latest consultation can help firms unlock this potential.

Unfulfilled potential

Synthetic data solutions are based on real data but are free of any client-identifying information. The result is an authentic simulation that looks and behaves like a production environment, with improved volume and security compared to alternatives such as anonymized data or artificial databases.

Synthesized data accelerates innovation, speeds up internal proofs of concept, and leads to far greater security and accuracy when creating new digital banking products. Yet relatively few financial institutions leverage synthetic data to its full potential, with many unsure of where to start.

The earliest adopters use synthesized data to enhance their software development and testing, reduce reputational damage from possible data leaks, and realize cost savings. They also benefit from significantly greater levels of flexibility, as third-party developers, fintechs and partners, as well as staff working remotely in cross-border jurisdictions, can use synthesized data in a secure and compliant way.

Levelling the playing field

A synthesized database speeds up the development process, prevents system failures and offers the freedom to involve partners at will – something that is becoming increasingly necessary in a financial ecosystem. The FCA’s consultation has the potential to level the synthetic data playing field by helping more financial institutions understand how they can capitalize on the technology and deploy it to their benefit.

Developing synthetic data solutions in-house is highly complex and often expensive, especially for smaller and mid-sized financial institutions. By shedding light on industry best practice through this consultation process, there is an opportunity to educate firms on the potential of standardized, cost-effective synthetic data solutions developed by technology providers. This will ultimately benefit clients by accelerating product innovation while maintaining a high level of security.

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