Executive summary

ORCA (Open Reusable Core API) is the layer that connects PortX products and fintech partners' applications to the banking cores, CRMs, and other systems financial institutions run. ORCA has evolved into a core banking abstraction layer, with its own common data model and proven runtime resilience. 

This means faster integration of new partners and the option to run more than one core at once, all on one stable foundation.

This matters most for fintechs. Instead of a custom integration project for every bank or credit union, a fintech builds once against ORCA’s common data model, connects each new institution through a simple, repeatable process, and gets real-time access to the core data its product depends on.

What is ORCA?

ORCA traditionally stood for Open Reusable Core API, but technically speaking, the A in ORCA is now for Abstraction. Why does it matter? 

An API passes each request straight to the core, so every app built on it inherits the core's quirks, slowdowns and changes. An abstraction sits in between and translates every core into one standard data model. Applications connect once to that model, and ORCA handles the differences between cores, as well as FI-specific differences, behind the scenes. That standard model is called a common data model. 

What is a common data model and why does it matter in banking? 

A common data model (CDM) is one shared definition of the data entities a bank or credit union works with and how they relate, used across all of its systems. Rather than every system being mapped to every other system’s format, each system’s data is translated once into this common format. With ORCA, PortX does that translation, mapping each system to the ORCA CDM. That keeps data exchange consistent because there is no pairwise point-to-point mapping between systems anymore, improves interoperability and data quality, and makes integration and data management easier to run. 

In banking, where every core stores and defines the same concepts differently, a CDM delivers six things: 

• Standardization: gives every system the same data definitions, formats, and meanings, even when the underlying systems are very different.

• Simplification: swaps many system-specific data structures for one model that any system or application can read and use.

• Interoperability: acts as a common language between systems, applications, and services, so each one integrates with the model once instead of with every other system.

• Consistency: keeps data accurate and aligned across systems by giving them all the same view of entities and relationships.

• Scalability: absorbs new business requirements, new data sources, and changing data structures without major rework.

• Meaning: applying AI, whether chatbots or agents, dashboards or reports adds risk if there is no understanding. AI must be ‘taught’ the relationship between data entities and fields - otherwise it will guess. ORCA provides a grounded ontology, able to explain to your AI what everything means and how it’s all related. Or just use ours, out of the box, a ready-built, secure and complete AI-native platform ready for your use cases today.

For an institution, this means it can move to a new core in stages, or run several cores side by side after an acquisition. Applications connect to ORCA, not to the core, so swapping or adding a core doesn't break them.

How ORCA is simplifying core integration 

ORCA is changing the way that fintechs and FIs can work together.

Simplifying industry data models: The ORCA model was created from analysis of every ORCA-supported banking core, and their specifications, and reconciling them into a single model that defines and holds them all. 

Beyond the ledger: The model carries CRM and customer success data alongside core banking, origination, and KYC data, so a person's CRM data and a borrower's core account data can be tied to the same customer(s).

One source of truth: Schema definitions, transformation logic, API specifications, and documentation are all generated from the common data model. When a field's definition changes, all of them update together automatically, so they cannot drift out of sync. 

Runtime reliability and scale: Without PortX, a fintech connecting to each banking core has to build and run a separate connector for that core for each institution, creating a myriad of narrow, bespoke integrations that grow with every new institution. ORCA replaces that with a single, scalable runtime that adapts to every supported core, and to each institution's own configuration, through a registry of connectors. 

Why both fintechs and banks win with ORCA

For a fintech selling to community banks and credit unions, the hardest part of a deal is usually getting data in and out of the core. Each institution has its own core, often customized, and each one has meant new point-to-point integrations, new mappings, and effort in the way of going live. Growth gets paced by integration work, not demand.

ORCA changes that in three ways:

• Managed or self-service connection. A fintech builds against one document, common data model, then connects to each additional institution via ORCA instead of a new custom implementation. The next FI integration uses the same as the first.

• Scale without adding engineering resources. Core-specific work lives in ORCA's configuration registry, not in the fintech's codebase. The fintech's own integration effort stays flat as it adds cores and institutions, so adoption can grow as fast as institutions sign.

• Real-time, fintech-grade data. ORCA exposes rich, normalized core data in real time, with account, transaction, and customer records tied to the same customer across core and CRM. Fintech-first experiences work as designed instead of falling back to batch files and overnight syncs.

The financial institution gets the other side of the same benefits:

Faster access to fintech products: Institutions can say yes to the fintech experiences their account holders want without opening a new integration project each time.

Reducing the cost and volume of API calls on the core: The new ORCA model keeps its own copy of each institution's data, stored in the same standard format its API already uses. This has the potential for ORCA to answer many requests without calling the core every time, which could significantly cut cost and load on the core. 

ORCA offers a new win:win for the banking industry. 

Would you like to learn more? 

If you are a fintech scaling across institutions or a bank adding new partners, talk to us about ORCA and core integration today.

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Frequently asked questions

What is ORCA?

ORCA (Open Reusable Core API) is PortX's core banking abstraction layer. It sits between applications and the banking cores, CRMs, and other systems an institution runs, and keeps its own common data model, so applications do not depend on any single core's implementation.

How is an abstraction different from a typical API integration?

A typical API passes each request straight to the core, so the core's slowdowns and changes affect every application built on it. An abstraction layer translates every core into one standard data model and catches core changes before they reach applications. Applications connect once, and ORCA handles the differences between cores.

API versus Abstraction - why does this matter for a bank or credit union?

New partners connect once to ORCA's standard data model instead of starting a new integration project. Core migrations can happen in stages, and multiple cores can run side by side after a merger without forcing immediate standardization.

How would a fintech use ORCA for core banking integration?

A fintech integrates once against ORCA's common data model instead of building a separate integration for each core and each institution. New institutions connect through a managed or self-service process, core data is available in real time, and the fintech's engineering effort stays flat as it adds banks and credit unions.

What is a common data model?

A common data model (CDM) is one shared definition of an organization's data and how it relates, used across all of its systems. Each system maps to the model once rather than to every other system, which keeps data exchange consistent and integration simpler.

What are the benefits of a common data model in banking?

A CDM gives every system the same data definitions, formats, and meanings. That replaces many point-to-point integrations with one common language, keeps data accurate across systems, and lets the model take on new data sources and requirements without major rework.

How was the PortX common data model built?

PortX read the real schemas and specifications of 30 core banking systems and reconciled them into one model. Each field is marked as confirmed against real system data or inferred from code, and concepts shared across institutions become well-defined attributes.

How does ORCA keep its APIs and documentation in sync?

Schemas, transformation logic, API specifications, and documentation are all generated from the common data model. A change to the model updates all of them together, so nothing drifts out of sync.

How resilient is ORCA?

ORCA runs active across multiple regions. If a region goes down, the surviving region takes the full load and operations continue without manual failover.