What can AI agents take over in Consumer lending & fintech operations?

tacitrun ships 7 Consumer lending & fintech process blueprints — Loan application intake & document collection, Underwriting & credit decisioning support, Funding & disbursement readiness and Debt-settlement case management & creditor negotiation and more — each stating its inputs, outputs, KPIs and the points where a person stays in the loop. They are the starting point: the domain agents themselves are built by reading your own procedure, and every write they make waits for your approval.

High-volume, decision-heavy consumer lending + debt-resolution operations.

Origination & underwriting

Loan application intake & document collection

Intake an application across channels, verify identity, pull bureau + bank/income data, and assemble a complete, decision-ready file — chasing only the missing stipulations.

Inputs
Application (web / partner / phone) · ID + income / bank docs · Consent & disclosures
Outputs
Decision-ready file · Stipulation request · Fraud / IDV flag
KPIs it moves
Pull-through rate · Time-to-decision-ready · Doc-completeness rate · Fraud catch rate
Systems it usually runs on
Loan origination (nCino / Blend / MeridianLink) · Plaid · IDV (Socure / Persona) · Credit bureau
Where a person stays in the loop
Identity / fraud exception · Adverse documentation

Underwriting & credit decisioning support

Apply the credit policy to a complete file — bureau, DTI, income, fraud signals — auto-approve clean-within-policy cases, and route everything else to an underwriter with the analysis assembled. Never auto-denies credit.

Inputs
Decision-ready file · Credit policy / scorecard · Bureau + income / DTI
Outputs
Clean-within-policy approval · Underwriter review packet · Counter-offer scenarios
KPIs it moves
Auto-decision rate · Approval accuracy · Decision cycle time · Early-default rate
Systems it usually runs on
LOS / decision engine · Credit bureau + FICO · Income / DTI verification
Where a person stays in the loop
Any adverse action / denial — human + ECOA notice · Policy exception / override · Rate / term exception

Funding & disbursement readiness

Confirm all stipulations cleared, run final KYC / OFAC, validate the disbursement target, and stage the loan for funding — funding itself is a gated human action.

Inputs
Approved loan · Cleared stipulations · KYC / OFAC + bank verification
Outputs
Funding-ready package · Held / exception case
KPIs it moves
Time-to-fund · Stip-clear cycle time · Funding error rate
Systems it usually runs on
LOS · KYC / OFAC · Payment processor · Core servicing
Where a person stays in the loop
Fund release / disbursement authorization · OFAC / KYC hit

Servicing & debt resolution

Debt-settlement case management & creditor negotiation

Manage a member’s enrolled debts: prioritize accounts, prepare settlement offers within set authority, track creditor responses, and route every settlement authorization to a human.

Inputs
Enrolled debts + balances · Member dedicated-account funds · Settlement authority / policy
Outputs
Prepared settlement offer · Negotiation status · Authorization request
KPIs it moves
Settlement rate · Avg settlement % · Time-to-first-settlement · Member completion rate
Systems it usually runs on
Debt-settlement platform · Dedicated-account / escrow · Creditor portals · CRM (Salesforce FSC)
Where a person stays in the loop
Settlement acceptance / authorization · Funds movement

Collections & hardship handling

Run compliant, segmented outreach on delinquent accounts, intake hardship / forbearance requests, and route arrangements and any consumer-impacting action to a human.

Inputs
Delinquent account · Payment history · Hardship request
Outputs
Compliant outreach · Proposed arrangement · Hardship case
KPIs it moves
Roll / cure rate · Promise-to-pay kept % · Right-party-contact rate · Complaint rate
Systems it usually runs on
Collections system · Core servicing · Dialer / comms · Payment processor
Where a person stays in the loop
Payment arrangement / settlement approval · Hardship / forbearance grant

Member onboarding & enrollment

Guide a new member through program / loan enrollment — disclosures, dedicated-account setup, expectations — and confirm a complete, compliant enrollment.

Inputs
Enrolling member · Program / loan terms · Required disclosures
Outputs
Completed enrollment · Dedicated account set up · Welcome + plan
KPIs it moves
Enrollment completion · Time-to-activate · Early-attrition rate · Disclosure compliance
Systems it usually runs on
CRM (Salesforce FSC) · Debt-settlement / loan platform · Dedicated-account · E-sign (DocuSign)
Where a person stays in the loop
Suitability / affordability exception

Digital member self-service

Member self-service (status, payments, payoff)

Resolve common member requests digitally — application / loan status, payment, payoff quote, document upload — with guided answers and deflection.

Inputs
Member request (web / app) · Loan / account data · Payment history
Outputs
Self-serve resolution · Payoff quote · Escalation when needed
KPIs it moves
Digital containment · Self-serve adoption · CSAT · Call deflection
Systems it usually runs on
Member portal / app · Core servicing · Payment processor
Where a person stays in the loop
Dispute / hardship / exception

What a blueprint is, and is not

A blueprint supplies the vocabulary, the typical steps, the KPIs and the approval points for a process. It is a starting point, not a pre-built agent: tacitrun builds the domain agents by reading your own procedure, tests them against cases derived from it, runs them in shadow beside your team, and holds every write for a person. Your IT connects the systems and approves before anything goes live.

Questions people ask

How do I give an agent a reference document (e.g. a sample template) to use at runtime?
Two places, both drag-and-drop: (1) for ONE agent, open it → Knowledge tab → drop the file on “Documents it can look up”; (2) for the WHOLE process (available to every agent in it), the process page has a “Documents for this process” card — drop it there. For example, drop a sample proposal template for a Proposal Generator. Whatever the format — PDF, Word, Excel, CSV, HTML, text, OR a screenshot/image (PNG, JPG, etc.) — we handle it: documents convert to clean markdown (tables and headings preserved, not a flattened blob), and images/screenshots are read by vision (Claude) which transcribes all the text and describes what’s in them (e.g. a screenshot of an invoice becomes a markdown table of its line items). Then we cap it to a sensible size for efficient token use, chunk and embed it so retrieval is sharp. It’s added immediately (no IT approval needed, nothing hardcoded) and shows in the document list. From then on the agent searches it live every run and uses it as a reference — e.g. it drafts new proposals in the shape of your template. To have it ALWAYS apply a rule instead of just look it up, use “Teach it” on the same tab (or the Rules tab for enforceable policies).
What is the Salesforce Data Hygiene blueprint, and how do I use it?
It’s a pre-built end-to-end process (a "crew" of 5 domain agents) that replaces the manual job of cleaning up messy CRM data and re-importing it. In the Catalog it shows as a Blueprint with the problem it solves, the outcomes it delivers, and the process mapped to each domain agent: (1) Data Quality Auditor profiles the object and reports duplicates/blanks/malformed/stale records; (2) Duplicate Finder & Merger proposes human-approved merges; (3) Field Standardizer normalizes phone/state/country/titles/casing; (4) Data Re-import Loader picks up a cleaned file (SFTP/SharePoint/Drive) and UPSERTS each row by external ID — so re-runs update the same record instead of creating duplicates; (5) Import Reconciliation Auditor verifies the load matched the source. Adopt each step from the blueprint; we build a private copy in your workspace that you can adapt, connected to your own Salesforce. Every write goes through human approval until you trust it.
What’s a Skill vs a Blueprint?
A Blueprint is a starter process template. A Skill is a reusable knowledge pack a domain agent loads on demand at runtime.
Do you have blueprints for private equity / deal teams?
Yes. Pick "Private equity" in Blueprints to get the full deal lifecycle (origination → diligence → execution & close with IC + signing gates → value creation → exit), plus the cross-portfolio value-creation playbook as standardized levers (working capital, FP&A, pricing/margin, spend analytics, JML access) that deploy identically across every portfolio company. Human-approval gates are built into the deal-close and IC steps. On Ingest, choosing "Private equity" also offers starter templates — Deal Sourcing & Screening, DD Red-Flag Log, IC Memo & Approval, and 100-Day & Value-Creation Plan.

Why offload this process to tacitrun’s AI operating layer

tacitrun is built for exactly this handoff: a business team describes the process it already runs, and the platform turns it into governed domain agents that work across the systems you have, under your IT’s approval, with every write waiting for a person.

Built from your procedure, not a vendor template
Describe the process in plain English or hand over the SOP. tacitrun compiles it into a process graph and composes one domain agent per step, so the agents carry your rules, your exceptions and your vocabulary.
Tested against the process before it can act
Evaluation cases are derived from the graph itself, so a passing agent is one that does what your process says. Then it runs in shadow beside your team on real work before anyone lets it act.
Every write stops for a person
The approval gate sits on the actual call to Salesforce, Shopify, SendGrid, SAP or any connected system. A person accepts, modifies or rejects; the corrected version is what executes; the trace keeps the record.
Runs across the systems you already have
Built-in connectors, your own REST APIs or MCP servers, and on the Enterprise plan your own cloud project and your own models. The systems of record stay where they are; the layer does the work between them.
IT approves, business leads
Business users build and prove; IT connects the credentials, binds the fields and approves before anything goes live. Neither side inherits the other’s risk.

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