Oxygen Cuts Fraud Losses 50% and Grows Tier Users 15% with Future-Proof Data Strategy

Yalantis helped this leading US neobank transform fragmented data infrastructure into a governed, scalable foundation for data-driven decision-making – enabling targeted marketing and proactive fraud prevention.

50%+

Fraud loss reduction

15%

Tier user growth

User base growth

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“Oxygen’s data architecture was designed for a startup. But they weren’t a startup anymore – they had data flowing in from 17+ systems, and nobody owned any of it. We built the governance framework and scalable infrastructure they needed to operate like the enterprise they’d become.”

– Mykhailo Maidan, CTO at Yalantis

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Data infrastructure struggling to keep up with growth? We build future-proof data strategies.

Manual order processing couldn’t scale – and scattered data eroded customer trust

Client:

Oxygen

Headquarters:

USA

Industry:

Fintech, Neobank

Services:

Data strategy, Data governance, Architecture optimization, BI improvement

Partnership:

Feb 2022 – Oct 2023

Team:

4 IT experts

Rapid growth outpaced the data architecture – and nobody owned the data

Oxygen is one of the leading mobile banking providers in the US, offering innovative personal and business financial solutions to freelancers, solopreneurs, and modern SMBs. They’re currently expanding into embedded finance with non-insurance health benefits – a strategic pivot that demands reliable data infrastructure.

The problem: their data architecture was designed when the company was in its infancy. It couldn’t keep up.

Oxygen used Amazon Redshift for centralized storage and Amazon QuickSight for BI visualization. That worked fine initially. But as the business grew, data started flowing in from over 17 external systems – payment tools, marketing platforms, risk and fraud systems, and more.

Gaps emerged everywhere. No procedures existed to guarantee data quality, accuracy, or compliance. There was no designated ownership for datasets – nobody was accountable when things broke. The architecture simply wasn’t built for this volume.

The business impact was real:

Decision-making slowed by unreliable data
Reporting accuracy suffered, affecting multiple departments
Risk and compliance exposure increased
Information security vulnerabilities emerged
Business agility suffered as change management became painful
Manual system upkeep consumed engineering resources

Oxygen recognized they needed a technology partner who could build a future-proof data strategy – not just patch the current problems, but create infrastructure that would scale with the business.

That’s when they partnered with Yalantis.

Client:

Oxygen

Headquarters:

USA

Industry:

Fintech, Neobank

Services:

Data strategy, Data governance, Architecture optimization, BI improvement

Partnership:

Feb 2022 – Oct 2023

Team:

4 IT experts

Future-proof data strategy: scalable architecture, robust governance, and optimized workflows

Scalable data architecture design

We redesigned the data architecture to handle increasing volumes from 17+ external systems. The new structure is flexible enough to adapt as Oxygen’s business needs evolve – supporting their expansion into embedded finance without requiring another overhaul.

Comprehensive data governance framework

We implemented a governance framework that defines roles, responsibilities, and ownership for every dataset. Role-based access controls and encryption protect sensitive financial data. KPIs now continuously monitor data quality and compliance risks.

User management for admins

System admins can track user contact information, control access levels, communicate directly with users, and monitor/log platform activity. Complete visibility into who’s doing what, when.

Business-domain data organization

We reorganized datasets by business domain rather than technical task – aligning data structure with how teams actually work. This made data more discoverable and meaningful for finance, marketing, risk, and operations teams.

Automated CI/CD for data changes

GitLab CI/CD pipelines now automate and standardize data changes and updates. Manual upkeep that consumed engineering time is replaced with consistent, auditable processes that reduce errors and accelerate deployment.

Optimized QuickSight BI dashboards

We improved data visualization by adjusting BI dashboards in Amazon QuickSight. Better dashboards mean faster, more confident decisions – especially critical for marketing campaigns and fraud detection.

Team training on governance protocols

Technology alone doesn’t solve governance. We conducted training to increase awareness of data governance protocols across the organization – ensuring the framework would be followed after handover.

How Yalantis transformed Oxygen’s data infrastructure in three stages

Over 20 months, we moved from audit to implementation to governance – building a foundation that would scale with Oxygen’s growth rather than constrain it.

Step 1

Stage 1. Auditing data architecture

Before changing anything, we needed to understand the current state. We worked with the Oxygen team to audit and document the entire environment.

This included mapping the current architecture – documenting key systems, data models, pipelines, dependencies, and integrations. We reviewed infrastructure for performance, capacity, security, costs, and gaps. Technical debt, risks, and problems were quantified so we could prioritize effectively.

Critically, we discovered ownership (or lack thereof) for data processes – establishing accountability for the first time.

Step 2

Stage 2. Improving reporting

With the audit complete, we focused on creating a more streamlined and governed data environment. We mapped business processes with relevant data and categorized datasets by business domain rather than technical task.

GitLab CI/CD pipelines automated and standardized data changes and updates. We optimized data storage needs and costs. BI dashboards in QuickSight were adjusted for better visualization and faster decision-making.

Step 3

Stage 3. Establishing data governance

Finally, we implemented a data governance framework designed to sustain the improvements. We defined data governance roles and responsibilities – ensuring someone was accountable for every dataset.

Role-based access controls and encryption were implemented to protect sensitive financial data. KPIs were established to continuously monitor data quality and compliance risks. And we conducted training across the organization to increase awareness of governance protocols.

The business impact was measurable:

User base increased by 5%

Through targeted marketing campaigns enabled by reliable data

Tier users increased by 15%

Via proactive customer engagement driven by data insights

Operational losses from fraud reduced by over 50%

Preventing potential compliance risks

Continuous data quality monitoring

Through defined KPIs and governance processes

Flexible data architecture

That quickly adapts to changing business needs

Clear data ownership established

Accountability where none existed before

Looking forward

With a scalable data infrastructure and governance framework in place, Oxygen is positioned for continued growth. Their strategic pivot into embedded finance – adding non-insurance health benefits to their financial platform – is now supported by data infrastructure that can handle the complexity.

More importantly, the foundation is future-proof. As Oxygen grows and data volumes increase, the architecture and governance will scale with them – not constrain them.

Key milestones of our R&D collaboration.

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