# Acin Financial Model

SaaS and data subscription network for operational risk management at Tier 1 financial institutions

- Canonical: https://finamodel.com/startups/acin
- Excel download: https://finamodel.com/startup-models/acin.xlsx
- Category: Fintech
- Model type: SaaS ARR / Valuation
- Funding round: Series A
- Funding: $12M
- Founded: 2020
- Geography: UK-headquartered (Acin Limited); clients include global Tier 1 banks [DECK slide 3]
- Customer: B2B2C

## About the company

Acin is a SaaS and data-subscription network for operational-risk teams at global financial institutions. Its Terminal, common ACIN control identifiers, and benchmark reports replace fragmented, spreadsheet-led risk and control assessment work with a shared industry data layer.

The company is UK-headquartered and sells directly into relationship-led Tier 1 bank accounts. The documented network includes institutions such as Morgan Stanley, J.P. Morgan, UBS, Deutsche Bank, and Société Générale; each additional participant makes the benchmarking dataset more useful.

This financial model is driven by client institutions, annual contract value, subscription tier, and expansion into data or risk-intelligence reports. It should separately track the growth of ACIN identifiers and client adoption, then translate those recurring revenue streams into an enterprise SaaS P&L.

## What's included

- 5-year monthly revenue build with stage-appropriate growth assumptions
- Full P&L, headcount plan, and operating-expense schedule
- Cash-flow statement, runway, and burn-rate tracking
- Valuation via exit multiple with a DCF cross-check
- Returns analysis with MOIC and IRR
- Unit economics including CAC, LTV, payback, and cohort retention

## Product & value proposition

- **Acin Terminal**: web platform for managing, visualising, and benchmarking operational risk & controls data
- **Acin Code / ACIN identifier**: a unique "barcode" for each risk/control instance enabling cross-institution standardisation and network interoperability
- **Network effect**: risk intelligence shared across member institutions - a risk known to one is known to all; Acin acts as network hub
- **Risk Intelligence reports**: bespoke analysis (e.g. Covid-19 WFH, vendor incidents, rogue trading) produced from network data
- **Value pillars**: Data standardisation → benchmarking → network insights; reduces manual/Excel-based RCSA processes; provides regulator-ready quantitative evidence
- Predecessor: Anchura consulting (founded 2010, grew to £12m revenue by 2016); Acin spun out Sep 2017, pivoted fully to SaaS/data by Sep 2018

## Market

No explicit TAM/SAM/SOM figures in deck. Contextual size indicators (all):
- $150bn p.a. gross operational risk losses (ORX Banking Loss Report, 2018)
- $376bn in regulatory fines since 2012 (AFME, Apr 2018)
- $26bn annual regulatory compliance costs (AFME, Apr 2018)
- $411bn OpRisk capital held at top 30 banks

Addressable universe: global Tier 1/2 banks, plus interdealer brokers, exchanges, clearing houses, insurance. Market size figure for Acin's SaaS/data product not stated.

## Revenue model

- Model described as "SaaS and Data Subscription Network"
- Revenue streams implied: (1) subscription fees per institution to access the Acin Terminal and network; (2) data subscription / benchmarking reports; (3) risk intelligence reports
- No per-seat, per-ACIN-code, or ACV figures shown
- Sales channel: direct enterprise sales to Tier 1 FIs (named clients suggest relationship-driven sales)

## Traction & metrics

- Clients named (slide 3 timeline): Credit Suisse, Morgan Stanley, Nomura, Société Générale, JP Morgan, Bank of America Merrill Lynch, Standard Chartered, Deutsche Bank, UBS
- Unique Control Identifiers (ACIN codes) in dataset:
  - Oct 2018: 1,200
  - Jan 2019: 1,400
  - Apr 2019: 2,200
  - Jul 2019: 5,200
  - Oct 2019: 5,900
  - Jan 2020: 35,000
- Case study client ACIN counts: Bank 1 = 45 ACINs; Bank 2 = 163 ACINs; Bank 3 = 333 ACINs
- % control gaps vs. Acin standard: Bank 1 = 32%, Bank 2 = 55%, Bank 3 = 48%
- No ARR, MRR, revenue, or customer count figures disclosed

## Competition / moat

Not explicitly addressed in deck. Implied moats:
- Network effect: data value compounds with each additional institution
- Proprietary ACIN code taxonomy - "barcode for risk & controls" creates switching cost and standardisation lock-in
- Incumbent clients are the world's largest banks, creating credibility barrier for competitors
- Named regulatory references (FCA SM&CR, Basel II/III, ECB, ESMA) suggest deep domain expertise as a moat

## Team & funding ask / use of funds

- Cris Conde (Former President & CEO, SunGard) cited as endorser/advisor
- Founding team: not named in deck
- Prior revenue: Anchura consulting reached £12m revenue by 2016; no Acin-entity revenue or funding history shown

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## Recommended financial model

- **Archetype + why**: B2B SaaS ARR model with network-effect data layer. Acin sells annual subscriptions to financial institutions - recurring, contract-based, high-retention. The ACIN code dataset is the core asset; model should capture both the subscription revenue and the data/network expansion flywheel. A 3-statement is warranted given the institutional client profile and likely investor expectation.

- **Forecast horizon & granularity**: 5 years (FY2020–FY2024), quarterly for Y1–Y2, annual thereafter. Deck dated April 2020; company is early commercial stage.

- **Key drivers & assumptions**:
  - Number of client institutions (FIs) - starting point: ~9 named clients as of April 2020; new client adds per year
  - ACV per client
  - Revenue per client type: differentiate by data subscription tier (number of ACINs licensed/benchmarked)
  - Data/ACIN identifier growth rate - 1,200 → 35,000 unique codes Oct 2018–Jan 2020 (~29× in 15 months);
  - Gross margin, moderate headcount for risk intelligence reports]
  - S&M as % of revenue
  - R&D as % of revenue
  - G&A
  - Churn / net revenue retention
  - Payback period
  - Risk intelligence report revenue

- **Scenarios (Base / Bull / Bear - which variables flex)**:
  - **Base**: 4 new clients/yr, ACV £750k, 75% gross margin, 8% gross churn
  - **Bull**: 7 new clients/yr, ACV £1.25m, faster data network growth driving premium pricing, 5% churn, expansion revenue from upsell
  - **Bear**: 1–2 new clients/yr (long procurement cycles at Tier 1 banks), ACV £500k, higher S&M spend per logo, 12% churn

- **Required sheets / outputs**:
  1. Assumptions (all drivers in one place)
  2. Revenue build (clients × ACV, cohorted by year; ARR bridge: new + expansion − churn)
  3. Income Statement (Revenue, COGS, Gross Profit, OpEx by function, EBITDA, D&A, EBIT)
  4. Headcount plan (S&M, R&D, G&A, risk intelligence team)
  5. Balance Sheet
  6. Cash Flow Statement (incl. SaaS deferred revenue working capital)
  7. KPI dashboard: ARR, clients, ACIN codes in network, NRR, CAC payback
  8. Scenario toggle (Base / Bull / Bear)

## Frequently asked questions

### Is the Acin financial model free?

Yes. The Acin model is a free Excel download with live formulas.

### Can I change the assumptions?

Yes. The workbook is editable and its live formulas recalculate when assumptions change.