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BankingWhat we do, and an illustrative case

A single commercial bank can improve massively, in onboarding, compliance and credit.

We map how the work really runs from your own systems, measure the gap to best practice, and check every case as it happens.

What a bank can gainPublished results, with their sources

The gains are documented.

  • 20–40%

    lower cost to serve in a frontline domain rewired end to end

    McKinsey, “Agentic AI is here. Is your bank’s frontline team ready?,” 2025 (results reported by banks)

  • 60%

    faster deal turnaround: from 5 days to 2, at one bank

    McKinsey, “Agentic AI is here. Is your bank’s frontline team ready?,” 2025

  • up to 30%

    more efficient AML reviews, and up to 40% better detection, at one bank

    McKinsey, “The fight against money laundering: Machine learning is a game changer,” 2022

  • 16%

    faster corporate onboarding, and 8% cheaper, from workflow tools alone

    PwC, “Effective onboarding for corporate customers” (up to 65% with combined measures)

What commercial banks needCompliance first, faster for clients

Built for how you really run.

  • Compliance first

    KYC and AML gaps caught before the regulator finds them.

  • Faster onboarding

    Corporate clients onboarded in days, not months.

  • Faster credit

    Credit memos and covenant checks built from data.

  • Low-risk start

    One process, 10 weeks. Runs on-prem with open-source models.

Illustrative caseLarge commercial bank: KYC, onboarding and credit

$21M saved a year.

Corporate clients, 10 weeks. An illustrative case, not an AIx2 client result: Illustrative bank running 40,000 corporate KYC reviews a year at $2,598 each (Fenergo, 2023) = $104M. Assumes 20% less effort per review: 40,000 × $520 = $21M a year.

  • $2.6K → $2.1K

    cost per KYC review

    Fenergo, 2023; assumes 20% less effort per review

  • 4 weeks → 3 weeks

    time to credit decision

    Time to decision for small business and corporate loans averages 3–5 weeks (McKinsey, The lending revolution, 2018). Assumes 4 → 3 weeks; not counted in the savings.

  • sample QA → 100%

    KYC files checked

    Up to 90% of alerts from rule-based monitoring can be false positives (McKinsey, The new frontier in anti-money laundering). AIx2 checks every KYC file and alert live.

How we get thereThe ten weeks, step by step

From your own data to live checks on every case.

  1. Step 01: Collecting Data

    Connect core banking, CRM and KYC tools; add loan origination and AML alert data; capture e-mail, Excel and credit memos

    Weeks 1–2

  2. Step 02: Mapping Processes and Data Flow

    Map onboarding from first contact to live; map credit from request to decision; trace every KYC document and check

    Weeks 3–4

  3. Step 03: Gap Analysis

    Find rework, delays and what they cost; flag KYC gaps and repeat requests

    Weeks 5–6

  4. Step 04: Optimal Design

    Ask clients for each document once; fast-track low-risk credit requests

    Weeks 7–8

  5. Step 05: Implementation Live Assurance

    Live QA on every KYC file and alert; flag compliance risk early; track savings against the baseline

    Weeks 9–10