Uptiq Marketplace

AI Agents for Banks

Domain-trained agents that take on the commercial lending work your team still does by hand: reading borrower documents, spreading financials, drafting credit memos, tracking covenants and keeping the audit trail clean.
Qore AI Platform
Live workflow
Commercial lending workflow
1
Borrower intake
Package received and validated
Complete
2
Document AI
43 fields extracted and traced
95%+
3
Financial spreading
Mapped to bank template
Ready
4
Credit memo
Draft ready for human review
Review

150+

Institutions served

100+

 integrations

95%+

extraction

5 day

Live in 5 business days
What are AI agents for banks?

Software that completes the task, not software that tells you how.

An AI agent for banks reads the inputs, applies the bank's own policy and credit standards, produces a finished work product, and hands it to a person for review.

Unlike rules-based automation, an agent can keep working when borrower documents arrive in unfamiliar formats or financial statements use non-standard line items.

The practical test is simple: does it produce something a credit officer would actually use?

Why banks are deploying agents now

The bottleneck isn't credit judgement.

It is the work around the decision: document handling, re-keying, assembly, monitoring and evidence.
01
Analyst capacity
Move repetitive preparation away from analysts so more time stays with judgement and relationships.
02
Borrower expectations
Shorten the document and assembly work that sits between an application and a decision.
03
Exam-ready records
Apply a consistent standard and keep evidence of what was checked, when, and by whom.
04
No core replacement
Agents operate across the systems already in place instead of asking the bank to replace them.
Where agents fit

Across the lending workflow.

Agents do preparation and monitoring. People do judgement and relationships. No agent approves credit.
Stage
What the agent does
What stays with your team
Intake
Collects and checks borrower documents, flags what is missing, chases the gaps
Relationship, scoping, structure
Extraction
Reads tax returns, statements, rent rolls and entity documents into structured fields
Review of low-confidence fields
Spreading
Maps figures to your spreading template and chart of accounts, builds the historical spread
Adjustments and normalisation calls
Risk analysis
Calculates ratios, runs sensitivities, surfaces trends and outliers against policy
Interpretation and weighting
Credit memo
Drafts the full memo in your house format, cited back to source documents
Credit judgement, recommendation, sign-off
Approval
Assembles the committee package, checks completeness against your checklist
The decision, always
Monitoring
Tracks covenants, ticklers and financial reporting deadlines continuously
Exception handling and borrower conversations
Annual review
Pre-builds the review pack from updated financials
Review conclusions and risk rating
The pattern is consistent: agents do preparation and monitoring, people do judgement and relationships. No agent approves credit.
How Uptiq's bank agents work

Powered by Qore. Grounded in your bank.

Your templates, your chart of accounts, your policy thresholds, your memo format, and your approval gates.
09:42
09:42
Domain-trained, not general purpose
Built around commercial lending documents, terminology, ratios and work products.
Lending policy
Role: Underwriter
Human checkpoint
Approved
Runs inside your systems
Agents read from and write back to the stack you already run.
Why was this flagged?
Reg B §1002.9
Policy 4.2
Agents work together
Start with one or connect the whole workflow.
SOC 2
Encrypted
Your data stays yours
A human always approves
Agents prepare, draft, calculate and flag. Named people review and decide.
Governance, security and oversight

Built to show its work.

Banks do not buy AI on capability alone. They buy on whether it can be explained to a regulator, an auditor and a board.
Traceability by default
Extracted figures link to the source document, page and line.
Approval gates you control
Configure confidence thresholds, review points and role-based permissions.
A complete activity record
Track the input, action, time and reviewer for each workflow.
Human accountability is preserved.
Agents create work products. Named people approve them.
What banks are seeing

Real work. Measurable impact.

41%
faster underwriting
 across the origination cycle
63%
less time
preparing credit memos
36%
less time
spreading financials
95%+
extraction accuracy
spreading financials
3x
more deals per analyst
without adding headcoun
150+
financial institutions
running Uptiq agents
Results vary by starting point, document mix and how much of the workflow is deployed
How long it takes to get live

Start with one workflow.

Most banks start with one agent against one painful workflow, prove it, then expand.

5

business days
Single agent

Connect source systems, load templates and thresholds, validate on real files, then go live with a defined review gate.

30

day
Full suite

Configure the connected workflow from intake through monitoring and validate the complete chain against live volume.

Capabilities

How to choose an AI agent

01
Does it produce a finished work product?
A summary is not a spread. A suggestion is not a memo.
02
Can it show its work?
A summary is not a spread. A suggestion is not a memo.
03
Does it handle your actual documents?
Ask for a test on your own messiest files, not a clean demo set.
04
Does it adapt to your policy and templates?
Or does it expect your bank to change format to suit the tool?
05
Does it connect to your core and LOS?
Integration depth determines whether it saves time or adds a system.
06
Where are the human approval gates?
They should be configurable, visible and enforced.
07
How long until the first real workflow runs?
Measure in weeks. If the answer is quarters, the payback maths changes materially.
FAQ

Questions banks ask.

What is an AI agent for a bank?

How is an AI agent different from a chatbot?

Do AI agents make credit decisions?

Will this work with our core banking system?

How accurate is document extraction?

How long does implementation take?

Is this suitable for community banks, or only large institutions?

How do we handle examiner and audit questions about AI?

What does it cost?

Start with one workflow

See the agents run on your own files.

Bring a real borrower package, the messier the better. See what the intake, extraction, spreading and memo agents produce.

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