Skip to content
Industries / Finance

ASC for Finance

Agents for every credit, risk, and compliance decision.

Agents inside the work of finance

Most AI in finance stops at a chart someone still has to act on. ASC deploys agents that read the documents, screen the alerts, score the risk, and take the action inside your core banking, lending, and trade systems. Every decision carries its evidence, its rule, and a human sign-off where the stakes require one.

Agentic operations

Agents on a governed decision stack

Signals rise from your core systems through a governance layer that audits every move, into a decision layer that holds the institution as one model, up to the agents that act. Each agent runs a perceive, decide, act, verify loop, and nothing reaches production without its rule and its evidence.

screenfailpassCore BankingBloombergSWIFTVisa / MastercardStripeTransactionnormalizedSanctions & OFAC screeningcheck 1AML / KYC monitoringcheck 2Credit & exposure limitscheck 3Immutable audit log (SR 11-7)check 4Hold / reviewClearedFraud DetectionAML InvestigationCredit UnderwritingReconciliationLiquidity / TreasuryCounterpartyTransactionTrade / PositionRisk & ExposureLedger Entry

Hover any node to trace its path through the control chain

The full range, from assistants to autonomy

Surface

Assistants & copilots

Policy Copilot
Answers credit and compliance policy questions instantly
Filing Drafter
Generates regulatory filings and disclosure memos
Statement Summarizer
Condenses statements and filings into briefs
Doc Search
Semantic search across policies, contracts, ledgers
Limit Alerting
Flags exposure and covenant breaches early
Analyst Q&A
Answers questions over the knowledge base
Deep

Autonomous, system-integrated agents

Fraud Detection
Knows
card-not-present, account takeover, mule signals
Tech
real-time anomaly detection + gradient-boosted scoring
AML Investigation
Knows
SAR typologies, structuring, sanctions/PEP screening
Tech
graph link-analysis + retrieval-augmented LLM
Credit Underwriting
Knows
PD/LGD, DTI, thin-file alternative data
Tech
gradient-boosted scoring + SHAP explainability
Reconciliation
Knows
GL matching rules, breaks, suspense aging
Tech
fuzzy entity matching + OCR extraction
Liquidity / Treasury
Knows
cash positioning, LCR/NSFR, payment timing
Tech
time-series forecasting + constraint optimization

One embedded team, agents across every stage

  1. 01
    Onboarding
    • Autonomous Onboarding
    • AML Investigation
  2. 02
    Underwriting
    • Credit Underwriting
  3. 03
    Financial Crime
    • Fraud Detection
    • AML Investigation
  4. 04
    Portfolio Ops
    • Liquidity / Treasury
    • Limit & Exposure
  5. 05
    Servicing
    • Dispute & Claims
    • Servicing Copilot
  6. 06
    Reconciliation
    • Reconciliation
  7. 07
    Reporting
    • Filing & Disclosure
    • Audit Trail
Selected work

What we have built in finance

Representative engagements, anonymized. Each began with one workflow where autonomy moved the business, shipped to production.

AML triage

A regional commercial bank

Problem

An AML team of 22 analysts cleared roughly 4,000 transaction-monitoring alerts a month, with more than 90 percent closing as false positives and genuine SAR cases waiting days behind the queue.

What we built

ASC built a triage agent on top of the bank's case-management and core-banking systems. For each alert it pulls counterparty history, transaction context, and prior dispositions, scores it against the bank's own typologies, and drafts the SAR narrative in the bank's template, cited to source records, so an analyst reviews and signs rather than starts from blank.

Outcome

Only the riskiest alerts now reach a human, review time fell sharply, and monitoring cost dropped while SAR quality held.

~40% lower AML cost

Credit underwriting

A digital-first business lender

Problem

Small-business applicants waited five to seven days for a decision because underwriters manually assembled bank statements, tax filings, and bureau data into each credit memo, and volume routinely outran the team.

What we built

ASC built an underwriting agent in the lender's loan-origination system. It reconciles figures across statements, financials, and bureau pulls, runs the lender's own policy and ratio checks, and produces a complete, cited credit memo with a recommendation and the exceptions an underwriter must rule on.

Outcome

Underwriters open a finished memo instead of building one, cutting turnaround and letting the same team carry more volume without loosening policy.

30% faster credit turnaround

Reconciliation

A multi-entity asset manager

Problem

An operations team reconciled custodian, fund-accounting, and internal ledgers largely by hand, working thousands of position and cash breaks a day and routinely clearing them after the settlement window.

What we built

ASC built a reconciliation agent across the custodian feeds, the accounting platform, and the internal ledger. It matches positions and cash, classifies each break by cause, and resolves routine ones end to end against the firm's rules, posting the adjustment and audit trail. Only ambiguous breaks route to an analyst.

Outcome

The daily manual workload collapsed and breaks clear inside the settlement window instead of after it, with full audit trails on every action.

up to 95% less recon workload

The platform

The stack lives in your tenant. Agents act on a decision layer built from your systems, every action audited and reversible, with ownership transferred to your team.

Impact

Outcomes you can underwrite

Gain an advantage

  • AML operations cost down roughly 40 percent, with alert-review time down 70 percent and only about 10 percent of alerts reaching an analyst.
  • Insurance loss ratios improve 3 to 5 points within a year, and a leading fraud pilot cut fraudulent transactions by 40 percent.
  • Governance is built in: every decision keeps its rule, its evidence, and human sign-off where stakes demand it.

Deliver at speed

  • Onboarding moves from days to minutes, and standard loan approvals follow the same path.
  • Claims settle 50 to 70 percent faster, and reconciliation matching workload drops by up to 95 percent.
  • Credit turnaround accelerates 30 percent while application abandonment falls about 35 percent.

Put agents to work in finance

Start with one workflow where autonomy moves the business, and we ship it to production.