A Position Paper

Concord's Position on Artificial Intelligence

Concord believes in AI. We use it across the company today, and we have built our own platform to run it inside the controls our clients depend on. The productivity gains compound as we connect more of our systems to each other.

We are also clear about what AI is not. It is not a replacement for human judgment, for the controls our clients rely on, or for the audit trail their regulators expect. AI is an amplifier of how Concord already operates, not a substitute for it.

Concord runs on data we own and judgment we trust. Those are the things we are protecting as we build with AI.

01Why Cosmo

Built on our infrastructure, on purpose.

Cosmo is Concord's Orchestrator for Secure Model Operations. It runs on AWS Bedrock, hosted on Concord infrastructure. It is model-agnostic: we use the right model for each task and swap models as the technology evolves.

We built Cosmo instead of routing teams through ChatGPT or Claude directly, to protect Concord and client data. Every prompt, every retrieval, and every output stays inside our boundary. Nothing trains anyone else's model. Nothing leaves Concord.

Bedrock holds SOC 1, 2, and 3, ISO 27001, HIPAA eligibility, and FedRAMP authorizations. Cosmo adds role-based access, full audit logging, prompt-injection protection, PII detection, and contextual grounding checks that filter the majority of hallucinated outputs. Every interaction is traceable to the data that informed it and the person who reviewed it. That is the standard a CISO and an examiner expect.

The platform

Concord's Orchestrator for Secure Model Operations

02What we believe about generic AI

Powerful tools, but not a credit administration platform.

Public LLMs are powerful tools, and we use them inside Cosmo. They are not, on their own, fit to run a credit administration platform. Three reasons matter for our clients and their auditors.

i · Accuracy

The same question must produce the same answer.

Stanford research found that raw large language models hallucinate on legal questions 58% to 88% of the time.^[1] Even leading commercial tools using retrieval-augmented generation still hallucinate 17% to 43% of the time. In credit administration, the same question must produce the same answer every time, with documentation a regulator can follow. Probabilistic models alone cannot do that.

ii · Safety at scale

Containment is the difference.

Samsung banned ChatGPT company-wide in 2023 after engineers leaked source code. Italy fined OpenAI €15 million in late 2024 after a breach exposed user payment data. In 2025 and 2026, AI agents with production access deleted live customer databases in two separate, well-publicized incidents. The problem is not generic AI. It is generic AI without containment, audit, and human oversight.

iii · Economics

Purpose-built is cheaper than DIY at scale.

Running raw foundation models against enterprise data at the volume our clients require is expensive, unpredictable, and inefficient. API calls, token costs, and infrastructure overhead compound quickly. Gartner expects more than 40% of agentic AI projects to be cancelled by the end of 2027,^[2] citing weak governance and unclear return. A purpose-built platform with structured data, defined use cases, and shared infrastructure is cheaper, it is safer, and a regulator can follow it.

03How we use AI at Concord

Four principles guide every AI decision.

Principle 01

Contained, by architecture.

Cosmo runs in our environment. Role-based access, audit logs, prompt protection, and grounding checks live at the platform layer rather than per use case. Containment is foundational, not added later.

Payment capture works the same way. The agent steps out of the call before any card data is read; collection runs through our PCI Level 1 path with AES-256-GCM tokenization, and we never retain the CVV.

Principle 02

‍Grounded in our own data.

Every answer that matters comes back to data we own and govern. We use AI to read across what is already in our systems, not to invent answers from a public training set. Berkeley AI Research found that 60% of enterprise LLM applications already use retrieval-augmented generation against governed data.^[3] That is what makes outputs trustworthy enough to use.

Principle 03

‍AI assists the work. People own the work.

AI is well-suited to drafting, classification, reconciliation, exception flagging, and summarization. Inside the contact center, we are investing in AI as the agent's coach: real-time guidance, next-best-action prompts, compliance language surfaced in the moment, and quality monitoring across every interaction.

When an AI agent talks to a borrower directly, what it can and cannot do is written down. It does not make credit decisions. It does not assess creditworthiness. It treats every customer the same way and escalates any discrimination claim to a person immediately. We audit for unequal outcomes after the fact.

Credit decisions and creditworthiness assessments stay with people, full stop. So do settlements, payment plans, fee waivers, credit-reporting representations, legal threats, hardship modifications, bankruptcy, and complex covenant interpretation. Anything that touches a borrower in distress goes to a person who can help them. The CFPB has been clear that automated systems cannot block a borrower from a human when statutory rights are in play, and we are aligned with that view.

Principle 04

‍Aligned to how we are already examined.

Cosmo and the work we run on top of it are aligned to SR 11-7 model risk management principles,^[4] the foundation guidance the Federal Reserve and OCC use to examine model use in regulated finance, and to the consumer and commercial credit regulatory frameworks Concord has worked within for decades.

Direction

Where AI takes us next.

The work is already underway, across every part of Concord.

Engineers ship faster. Legal and compliance produce evidence in hours, not weeks. Account teams walk into client conversations already knowing the portfolio. Contact center agents have the right answer in the moment they need it. Accounting catches the exception the morning it appears.

Clients get sharper insight on their portfolios. Borrowers get faster answers, shorter waits, and a person when they need one.

We are building into ConcordLink, into Finley, into eVault, and into our contact center operations. Cosmo is the platform underneath all of it.

Concord team working with Cosmo on roadmap and process — Champions from technology, product, operations, and compliance, working with Cosmo to sharpen our roadmap and our processes.

Footnotes

Dahl, Magesh, Suzgun & Ho, Hallucinating Law: Legal Mistakes with Large Language Models are Pervasive, Stanford RegLab & HAI, 2024. ↩
Gartner, Predicts 2025: AI Agents Reshape the Enterprise, June 2025 — reported figure: more than 40% of agentic AI projects to be cancelled by end of 2027. ↩
Berkeley AI Research, enterprise LLM application architecture survey, 2025. ↩
Board of Governors of the Federal Reserve System & OCC, SR 11-7: Guidance on Model Risk Management, 2011 (and subsequent supervisory guidance). ↩