By: Dr Zhitao Xiong, Head of Data Science (Frollo)
Open banking is transforming the financial landscape, paving the way for groundbreaking innovations. And at Frollo, we’re at the forefront, using agile data science to unlock the full potential of this open data ecosystem.
Why agile?
The Open Banking landscape is constantly changing. Consumer Data Right (CDR) regulations are frequently updated, data formats vary, and user needs shift rapidly. Traditional data science methods simply can’t keep up with this pace. That’s where agile data science comes into play.
Our solution is to adopt the agile data science approach. This approach focuses on adaptability, collaboration, and continuous improvement. By breaking down projects into smaller tasks and incorporating feedback, data scientists can quickly react to evolving regulations and data formats and provide stakeholders with tangible results. This iterative process allows for faster outcomes and efficient delivery of valuable insights.
Our approach to agile data science
Building an agile team takes focus and commitment. Three core principles guide us:
- Tangibility: Don’t wait for the perfect model; deliver tangible results early and often.
- Quality: Focus on delivering high-quality solutions within each sprint without overloading subsequent cycles.
- Trust: Underpromise and overdeliver. Build trust by consistently meeting expectations.
So far, the results are promising:
- 94% planning accuracy: Our agile approach ensures we deliver on our promises.
- Exceeding expectations: We consistently deliver features beyond our planned scope, pushing the boundaries of innovation.
- Cross-functional collaboration: Our data scientists work seamlessly with other teams, ensuring solutions address real-world challenges.
Where the rubber hits the road
Taking an agile approach to data science in Open Banking has enabled us to quickly iterate and learn from new data sources and customer feedback, leading to some significant business benefits:
- Understanding customer profiles: We enrich bank transaction data with diverse sources, formats, and spending behaviours. This paints a comprehensive picture of users’ financial health, empowering lenders and guiding individuals towards informed decisions.
- Conquering complexity: The ever-changing CDR landscape and diverse data nature demand a nimble approach. Our agile team, equipped with cutting-edge language models and expert systems, navigates these challenges with ease.
- AI/ML unlocks hidden insights: We harness the power of machine learning to decipher patterns and trends in the Open Banking data pool. This leads to a better understanding of financial behaviours and market dynamics, informing smarter business decisions.
- Goodbye, endless modelling: We say farewell to lengthy development cycles. Our agile approach delivers data products within weeks, thanks to a two-week release window. The key? Separating R&D from deliverables and prioritising rapid deployment.
And the benefits are clear:
- Enhanced customer experiences: Deeper insights lead to better products and services tailored to individual needs.
- Optimised efficiency: Agile data science streamlines our operations, saving time and resources.
- Staying ahead of the curve: We adapt quickly to industry shifts and regulatory changes, ensuring our offerings remain relevant.
IDEaS-a-plenty
As we navigate the evolution of Open Banking, our team is committed to pushing the boundaries of innovation while safeguarding the integrity of our proprietary methodologies. This comes together in our hybrid Artificial intelligence (AI) system, IDEaS: Integrated Data Enrichment as Services.
IDEaS powers our Financial Passport and enrichment services, as well as the Frollo money management app, with industry-leading accuracy in Open Banking transaction enrichment.
See for yourself in the Frollo app, or get in touch with our team to learn more.
