Banking & Fintech

Banks and fintechs are under converging pressure from digital-native customer expectations, accelerating regulatory scrutiny, and core platforms that were never designed for real-time, always-on financial services.

Modernization is no longer discretionary: institutions must evolve how they build, operate, and govern systems in order to compete, comply, and operate safely at scale, without destabilizing the platforms that already run the business.

Key Challenges We Solve for Banking & Fintech
‍

Legacy cores constraining change

Many institutions still depend on core banking and payment processing platforms that are stable but rigid. Even modest changes—new products, pricing models, or integrations—can require long lead times, vendor coordination, and elevated operational risk. The result is an organization that understands what it needs to build but is structurally unable to move at market speed.

Slow delivery in a fintech-paced market

Digital-native competitors routinely launch new journeys in weeks, while established banks struggle with long release cycles, brittle integrations, and manual controls. In financial services, time-to-market is not just a growth concern; delays directly impact customer retention, competitive relevance, and the ability to respond to regulatory or market change.

Increasing regulatory and operational burden

Requirements across AML, KYC, payments, operational resilience, and third-party risk continue to expand. Many organizations manage these obligations through fragmented tooling and manual processes, driving up cost, audit friction, and the risk of compliance gaps when regulators request evidence of how controls operated in practice.

Fragmented data limiting real-time decisioning

Transactional, customer, and risk data is often scattered across cores, channels, CRMs, and reporting systems. This fragmentation makes real-time fraud detection, credit decisioning, and AI-assisted personalization difficult to implement—and even harder to trust—without sacrificing consistency, explainability, or auditability.

Reliability expectations for always-on finance

Outages, latency, or partial failures in payments and digital channels quickly erode trust and attract regulatory attention. Financial platforms must behave predictably under peak load, market volatility, and failure scenarios—conditions many legacy architectures were not designed to withstand.

Shortage of high-assurance engineering expertise

Modern financial systems require deep skills in concurrency, distributed systems, event-driven architectures, and cloud-native reliability. These capabilities are scarce and difficult to develop internally while teams are under constant delivery pressure, creating long-term dependency on fragile systems and individual “heroes.”

Key Challenges We Solve for Banking & Fintech

Legacy cores constraining change

Many institutions still depend on core banking and payment processing platforms that are stable but rigid. Even modest changes—new products, pricing models, or integrations—can require long lead times, vendor coordination, and elevated operational risk. The result is an organization that understands what it needs to build but is structurally unable to move at market speed.

Fragmented data limiting real-time decisioning

Transactional, customer, and risk data is often scattered across cores, channels, CRMs, and reporting systems. This fragmentation makes real-time fraud detection, credit decisioning, and AI-assisted personalization difficult to implement—and even harder to trust—without sacrificing consistency, explainability, or auditability.

Slow delivery in a fintech-paced market

Digital-native competitors routinely launch new journeys in weeks, while established banks struggle with long release cycles, brittle integrations, and manual controls. In financial services, time-to-market is not just a growth concern; delays directly impact customer retention, competitive relevance, and the ability to respond to regulatory or market change.

Reliability expectations for always-on finance

Outages, latency, or partial failures in payments and digital channels quickly erode trust and attract regulatory attention. Financial platforms must behave predictably under peak load, market volatility, and failure scenarios—conditions many legacy architectures were not designed to withstand.

Increasing regulatory and operational burden

Requirements across AML, KYC, payments, operational resilience, and third-party risk continue to expand. Many organizations manage these obligations through fragmented tooling and manual processes, driving up cost, audit friction, and the risk of compliance gaps when regulators request evidence of how controls operated in practice.

Shortage of high-assurance engineering expertise

Modern financial systems require deep skills in concurrency, distributed systems, event-driven architectures, and cloud-native reliability. These are scarce and difficult to develop internally while teams are under constant delivery pressure, creating long-term dependency on fragile systems and individual “heroes.”

Representative Solutions & Engagements

Core banking and payments modernization
↓

We partner with institutions to modernize core banking and payment capabilities without big-bang rewrites. Starting at the edges—APIs, digital channels, and new product flows—we introduce event-driven integration layers and domain-aligned services that progressively reduce dependency on legacy cores while preserving regulatory approvals and operational continuity.

Typical Outcomes:

→ Reduced reliance on core vendor release cycles

→ Ability to launch new accounts, cards, or payment flows safely

→ Clear, regulator-friendly modernization narratives validated in production

Real-time fraud, risk, and AML platforms
↓

We design streaming architectures that ingest transactions and behavioral signals in real time, enabling earlier detection of fraud and suspicious activity. By combining event processing with governed data pipelines and explainable scoring, these platforms integrate cleanly with case management and reporting systems while maintaining complete audit trails.

Typical Outcomes:

→ Faster detection of emerging fraud and financial crime patterns

→ Lower false-positive rates through richer context and correlation

→ Improved auditability and regulatory confidence in controls


Open banking and partner API platforms
↓

We help institutions design and operate secure, API-first platforms that support open banking, embedded finance, and ecosystem partnerships. This includes gateway design, throttling, consent management, monitoring, and developer tooling so APIs can be treated as managed products rather than bespoke integrations.

Typical Outcomes:

→ Faster onboarding of fintech and ecosystem partners

→ Improved visibility into API usage, performance, and anomalies

→ Stronger security, consent, and operational controls


Digital channel and experience engineering
↓

Working alongside product and design teams, we build the service layers that power mobile and web banking experiences. Our focus is on low-latency APIs, observability, graceful degradation, and architectures that support experimentation without compromising stability during peak usage or partial failures.

Typical Outcomes:

→ More stable and responsive digital channels under peak load

→ Reduced abandonment in onboarding and lending journeys

→ Faster rollout of experience improvements and experiments
Banking data platforms for analytics and AI
↓

We design governed data platforms that unify transactional, customer, and risk data across systems. Emphasis on data quality, lineage, and explainability enables analytics and AI initiatives to move beyond pilots, supporting real-time decisioning while remaining defensible to regulators and auditors.

Typical Outcomes:

→ Shorter lead time from data ingestion to trusted insight

→ Shared, consistent datasets across risk, finance, and product teams

→ A durable foundation for advanced analytics and AI in production
Embedded teams and capability building
↓

We embed senior engineers and architects directly into client teams, working through existing tools and processes. In parallel, we deliberately transfer knowledge so internal teams gain lasting capability rather than long-term dependency.

Typical Outcomes:

→ Increased delivery throughput without sacrificing safety or quality

→ Reduced reliance on a small number of system “heroes”

→ Measurable uplift in engineering maturity across teams

Tagline

Representative Solutions & Engagements

Ziverge helps banks and fintechs modernize complex systems safely and incrementally, combining hands-on delivery with deep technical rigor. Our work emphasizes correctness, resilience, auditability, and long-term maintainability—qualities that matter in regulated, high-throughput financial environments where failures have material consequences.

Core banking and payments modernization

We partner with institutions to modernize core banking and payment capabilities without big-bang rewrites. Starting at the edges—APIs, digital channels, and new product flows—we introduce event-driven integration layers and domain-aligned services that progressively reduce dependency on legacy cores while preserving regulatory approvals and operational continuity.

Typical Outcomes
→ Reduced reliance on core vendor release cycles
→ Ability to launch new accounts, cards, or payment flows safely
→ Clear, regulator-friendly modernization narratives validated in production

‍

Open banking and partner API platforms

We help institutions design and operate secure, API-first platforms that support open banking, embedded finance, and ecosystem partnerships. This includes gateway design, throttling, consent management, monitoring, and developer tooling so APIs can be treated as managed products rather than bespoke integrations.

Typical Outcomes
‍→ Faster onboarding of fintech and ecosystem partners
→ Improved visibility into API usage, performance, and anomalies
→ Stronger security, consent, and operational controls

‍

Banking data platforms for analytics and AI

We design governed data platforms that unify transactional, customer, and risk data across systems. Emphasis on data quality, lineage, and explainability enables analytics and AI initiatives to move beyond pilots, supporting real-time decisioning while remaining defensible to regulators and auditors.

Typical Outcomes
‍→ Shorter lead time from data ingestion to trusted insight
‍→ Shared, consistent datasets across risk, finance, and product teams
‍→ A durable foundation for advanced analytics and AI in production

Real-time fraud, risk, and AML platforms

We design streaming architectures that ingest transactions and behavioral signals in real time, enabling earlier detection of fraud and suspicious activity. By combining event processing with governed data pipelines and explainable scoring, these platforms integrate cleanly with case management and reporting systems while maintaining complete audit trails.

Typical Outcomes
→ Faster detection of emerging fraud and financial crime patterns
→ Lower false-positive rates through richer context and correlation
→ Improved auditability and regulatory confidence in controls

‍

Digital channel and experience engineering

Working alongside product and design teams, we build the service layers that power mobile and web banking experiences. Our focus is on low-latency APIs, observability, graceful degradation, and architectures that support experimentation without compromising stability during peak usage or partial failures.

Typical Outcomes
‍→ More stable and responsive digital channels under peak load
‍→ Reduced abandonment in onboarding and lending journeys
‍→ Faster rollout of experience improvements and experiments

‍

Embedded teams and capability building

We embed senior engineers and architects directly into client teams, working through existing tools and processes. In parallel, we deliberately transfer knowledge so internal teams gain lasting capability rather than long-term dependency.

‍
Typical Outcomes
‍→ Increased delivery throughput without sacrificing safety or quality
‍→ Reduced reliance on a small number of system “heroes”
‍→ Measurable uplift in engineering maturity across teams

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