The Cost Gap Is Widening, and Your Core Is Not Moving

Traditional banks operate at a cost-to-income ratio above 60%. Well-run digital lenders operate at roughly 35%, and BCG's 2025 retail banking research finds that gap expanding rather than closing.

You already know where the margin goes. Documents move by hand, applications stall halfway through, and risk signals arrive after the window to act has closed. Every one of those problems has an AI answer somewhere on the market, but most of them don't have an answer built to work with the core you actually run.

That's the real constraint. Not ambition, not budget, and not appetite for AI. The systems of record that make your institution trustworthy are the same systems that make modernization feel impossible.

Manual document handling

Income, employment, and asset documents arrive in every format a borrower can produce. Review is slow, error-prone, and impossible to scale efficiently.

Application dropout

Borrowers abandon applications when the process turns opaque or asks for the same information twice. Every drop-off is acquisition spend you have already paid for.

Late risk signals

Delinquency and churn don't surface in reporting until after the point where outreach would have changed the outcome.

Constant audit exposure

Fair lending, Home Mortgage Disclosure Act, and Consumer Financial Protection Bureau audits require evidence on demand.

You Are Not Behind on AI. You Are Blocked by Two Specific Things.

Most mid-market lenders have already tried. The pattern is consistent enough that it is worth naming plainly.

Roadblock One: The Entrenched Core

More than 90% of mid-market lenders run on FIS, Fiserv, or Jack Henry. These systems are dependable, examiner-tested, and completely essential. They also have no native AI integration layer. The obvious path forward, a full migration, trades a known operational risk for an unknown one over several years.

Roadblock Two: The Pilot Trap

The alternative looks safer: a small use case like a chatbot or a document summarizer. These often don't touch the workflows that actually drive cost, so they stall out. BCG found that 95% generate no financial value at scale from their AI initiatives, and most simply automate routine tasks.

Both roadblocks have the same root cause. The AI wasn't designed to live alongside the core. Ours is.

Wrap Rather than Replace

Your core keeps the system of record. The AI layer sits above it and handles the work that slows lending down.

Layer 1: Your Core Stays

FIS, Fiserv, Jack Henry, Encompass, or whatever you run today remains the authoritative system for accounts, loans, and servicing. The records your examiners trust does not move.

Layer 2: DataBridge Connects

DataBridge is the connective tissue. It normalizes core data into AI-ready formats through secure APIs and open-banking connectors and writes enriched results back to the core.

Layer 3: Lending Intelligence Suite Delivers

The intelligence layer sits above the core and delivers the modern borrower experience. Ready-to-use accelerators in each stage operate under one shared compliance and fraud guardrail, and capability goes live in weeks rather than years.

Book a demo to see this mapped to your stack.

AgilityAI - Lending Intelligence Suite

Four Accelerators, One Guardrail

Three accelerators own a stage of the lifecycle. One runs across all of them. Available as a suite or individually.

Qual-IQ:
Discovery & Pre-Qualification

Qual-IQ ranks every inbound lead by likelihood to close and explains the ranking in plain English. Loan officers open their day to call briefs, draft emails, and a recommended approach for each lead.

Docu-Synth:
Origination & Application

Docu-Synth reads application documents in any format, classifies them, and extracts the data. It flags signs of tampering and reconciles conflicting income figures across sources.

Risk-Right:
Underwriting

Risk-Right explains every risk driver in plain language and shows the "what-if" paths. Underwriters see a defensible rationale and a ready adverse-action notice with each decision.

Lend-Liaison:
Across the Journey

Lend-Liaison holds a natural conversation with borrowers at any hour, captures the facts as they go, and recommends the right product at each step. Loan officers are free from routine questions while maintaining accountability.

Compliance as Infrastructure, Not an Afterthought

Every accelerator includes the AI guardrail layer as a condition of deployment, not an add-on.

Agent policy

Each model has defined boundaries, enforced across every accelerator. No model acts outside its mandate.

Assurance

Audit trails, bias reports, and model-performance logs produce an examiner-ready record of every decision.

Human responsibility

Every autonomous domain has a named, accountable owner, and human override is available at every decision.

The suite is designed to support your compliance program across ECOA and Regulation B, HMDA, the Fair Housing Act, the Fair Credit Reporting Act, and many more.

‍Ask for the full regulatory coverage map in your demo.

What the Research Says Happens Next

Independent research on AI in lending points consistently in one direction.

20-60%

Credit-analyst productivity gains and roughly 30% faster decisions in underwriting from orchestrated multi-agent systems (McKinsey, December 2024)

75%

Increase in completed pre-applications when an AI virtual assistant guides the borrower (BCG, 2025)

30%

Increase in profits for a typical retail bank implementing AI at scale compared with non-AI scenarios (BCG, November 2025)

1.9x

Higher revenue growth at AI-leader banks than at laggards, already measured in 2024 (BCG, 2025)

Marlabs - A Partner, Not Just a Vendor

The technology is half the story. What makes AI deliver in lending is who builds it.

Managed AI operations

We operate and retrain your models as your portfolio evolves so that the system stays current instead of aging in place.

Deep lending experience

We know consumer and mortgage lending in detail, which is why we can design for any point from lead to post-close, not just where a product happens to exist.

MORTGAGE LENDING

30 Days to 3 Min

Our AI-powered intelligent automation cuts loan origination from 30 days to 3 minutes, a 99.9% reduction in cycle time.

Learn More

FINANCIAL RISK MANAGEMENT

2,700 hours to 80 hours

Our generative AI document intelligence cuts complex file review from 2,700 hours to 80, saving $175K-$225K a year.

Learn More

CONSUMER LENDING

3 weeks to < 2 days

Our AI-driven forms platform generates 400,000 forms a month and cuts change cycles from three weeks to under two days.

Learn More

From Discovery to Live

Discovery & assessment

Weeks 1 to 6

Review of your loan origination system, core, and data landscape.

Solution design

Weeks 6 to 14

Accelerators configured to your workflows, data, and compliance posture.

Integration

Weeks 14 to 26

DataBridge connects to the core; accelerators go into your environment.

Testing & go-live

Weeks 26 to 32

Validation, user acceptance, and production release.

Managed operations

Month 7 onward

Monitoring, retraining, and expansion to the next accelerator.

Value arrives in phases, not at the end. Quick wins in the first phase fund and justify the next one.

FAQs

Do we have to replace our core system?

No. Your core remains the system of record throughout. The suite connects through secure APIs and writes results back so that nothing needs to be migrated.

Which core and origination systems do you support?

We support FIS, Fiserv, Jack Henry, Encompass, and Salesforce today and have plans to build additional connectors as engagements require them.

How long before we see something working?

Discovery runs 1 to 6 weeks depending on the complexity of your business needs. The first capability typically reaches production inside the first two quarters with value delivered throughout each phase rather than at the end.

How do you handle fair lending and adverse-action requirements?

We build explainability into the decision rather than add it afterward. Our Risk-Right accelerator produces reason codes designed for CFPB adverse-action notices under ECOA and Regulation B, and continuous bias testing runs across protected classes both before launch and periodically after.

Can we start with one accelerator?

Yes. Each accelerator owns a stage of the lifecycle and delivers value on its own. Most engagements start with the stage where the cost is most visible and then expand from there.

Ready to Move from Pilot to P&L?

Start with a focused discovery session. We map your current lending stack, pinpoint the highest-impact use cases across the accelerators, and design a phase 1 engagement scoped to your institution.

Not ready to book just yet? Check out our free whitepaper “Beyond Optimization: Transforming Business Workflows with Agentic AI” in the meantime.

Book a Demo

Read the Whitepaper

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