AHENQOR Technologies Products RetailRecon AI
Product How It Works Controls CFO View Deployment Demo
For CFOs, Finance Controllers & Treasury Teams
AI-Powered Retail Financial Control

Know what was sold. What settled. What’s still at risk.

Reconcile Store Tender, POS, Bank and BNPL. Identify SAR at risk. Assign exceptions. Recover missing settlements. Close with confidence.

Request a working product demo — no commitment required.

Know what was expected, what was received, what settled, what remains at risk, and what is ready to post.

RetailRecon Control Center
This Week
Expected
SAR 2.7M
Settled
SAR 2.61M
At Risk
SAR 68K
Open Exceptions
23
Outside SLA
7
Reconciled
94.8%
StoreProviderExpectedSettledDifferenceAgeOwnerStatus
613ANBSAR 18,420SAR 0SAR 18,420T+3TreasuryEscalated
207MADASAR 9,150SAR 8,900SAR 250T+1Store TeamIn Review
442TabbySAR 6,300SAR 6,300SAR 0T+0FinanceMatched
108TamaraSAR 4,760SAR 4,110SAR 650T+5Provider / BankAwaiting Response
Illustrative Control Center view — sample data, not a live client environment.

Built for finance & treasury teams responsible for

Store Tender Control POS & Bank Reconciliation BNPL Settlement SAR-at-Risk Exposure JV & D365 Posting Control
How It Works

From store tender to close, in five steps

A structured reconciliation and recovery workflow built for finance teams, not another dashboard to interpret.

Upload / Connect

D365 Store Tender, POS, bank and BNPL statements — uploaded or connected directly.

Reconcile

Match on auth code, amount and tolerance; flag duplicates and settlement lifecycle gaps.

Investigate

Identify missing settlement, duplicates, timing differences and mismatches.

Act & Recover

Assign an owner, collect evidence, follow up, and verify recovery.

Close & Post

Approve transactions, create the JV, control the period, and prepare approved JV batches for D365.

Bank Settlement Control

Verify every settlement, three ways

The core control behind RetailRecon AI — matching what a store recorded, what the provider processed, and what the bank actually settled.

Store Tender
✓ matched on amount, auth code & timing
Provider / POS
✓ matched on settlement reference
Bank Settlement
Channels covered
MADA Visa Mastercard AMEX Tabby Tamara Tap
Matching Intelligence

Not just totals — line-by-line matching logic

Every transaction is matched at one of three confidence levels before anything is treated as an exception.

Level 1 — Auto Match
Auth Code + Exact Amount
→ Matched
Level 2 — Tolerance Match
Auth Code + Difference ≤ SAR 1
→ Matched / Approval Rule
Level 3 — Review
Auth Code + Closest Amount
→ Finance Review
No Match
No corresponding record found
→ Exception Case
AI Finance Action Engine

Exceptions, detected, owned, and closed out

Every unmatched item moves through a defined lifecycle — nothing sits unassigned in a spreadsheet.

Detect Understand Assign Act Verify Close
Example: SAR 18,420 settlement missing
Store
613
Provider
ANB
Age
T+3
Likely Cause
Settlement delay
Owner
Treasury
Action
Bank follow-up
Evidence
POS + Bank statement
Status
Awaiting settlement
Sample exception — illustrative, not a real transaction.
0–1 day
10
SAR 18,000
2–3 days
7
SAR 20,000
4–7 days
4
SAR 15,000
7+ days
2
SAR 15,000
Illustrative aging view — 23 open exceptions totaling SAR 68K, aligned to the Control Center above.
Exceptions route to
🏬 Store Team 🏦 Treasury 📊 Finance 🔌 Provider / Bank
Control Architecture

Maker, checker, approver — nothing posts unchecked

Segregation of duties and a locked period, all the way through to D365.

Maker Checker Approver Period Lock JV D365 Audit Trail
D365 Posting Control: approved JV batches are prepared for D365, with direct posting integration on the product roadmap — not yet live in production.
Governance controls
Role-Based Access Evidence Original Values Correction History Approval Timestamp Period Lock Duplicate Posting Protection
Example correction record
Original Value
SAR 4,250.00
Corrected Value
SAR 4,180.00
Reason
Duplicate settlement entry
Approver
Finance Controller
Evidence
Bank statement excerpt attached
Timestamp
Aug 5, 2026 · 14:32
Sample record — illustrative, not a real transaction.
Multi-Country Architecture

Built for groups, not a single store

One data model spanning every entity, currency and payment provider in the group.

Company Country Legal Entity Store Payment Provider Bank GL
Designed for
Multi-Country Multi-Entity Multi-Currency Configurable GL Mapping Local Close Calendars
Settlement Accounting

Reconcile gross sales to the actual bank amount

Finance teams need more than a matched transaction. RetailRecon can separate gross sales, commission, VAT and net settlement so the accounting result is explainable.

Gross Sales

Start from the approved Store Tender / provider transaction value.

SAR 100,000
Expected gross card sales

Commission

Apply configured provider / card commission rules by payment type and effective date.

− SAR 1,550
Illustrative commission

VAT on Commission

Track VAT charged on provider fees separately for accounting and reconciliation.

− SAR 232.50
Illustrative VAT

Net Settlement

Compare the expected net amount against the actual bank settlement received.

SAR 98,217.50
Expected net settlement
Refunds, Chargebacks & Late Settlement

Keep open items alive until the finance story is complete

Refunds, chargebacks and delayed settlements should remain visible and controlled rather than disappearing when the accounting period changes.

RefundsLinked to original transaction
ChargebacksTracked as a separate finance exception
Late SettlementCarried forward to the next open period
RecoveryClosed only after settlement is verified
Example: June transaction settled in July
Transaction Date
30-Jun-2026
Expected Settlement
Open at June close
Actual Bank Settlement
02-Jul-2026
Treatment
Carry forward → verify → close
Illustrative control example.
Source File Controls

Control the input before you trust the reconciliation

RetailRecon should confirm that the source data is complete, unique and ready for matching before finance relies on any result.

Completeness Control

Expected file received for the period
Required columns present
Transaction count and total value captured
Store / provider coverage checked

Duplicate & Integrity Control

Duplicate source file detection
Duplicate transaction / auth-code detection
Unique transaction ID control
Rejected / failed / void records handled separately
The CFO View

Where is your money?

The question RetailRecon AI is built to answer, end to end — from expected sales to what's still at risk.

Illustrative CFO Control View — Sample Data
A simplified SAR 100,000 walkthrough example — separate from the Control Center dashboard figures above.
Settlement Lifecycle
Expected
SAR 100,000
Provider Received
SAR 97,400
Bank Settled
SAR 95,900
Reconciled
SAR 94,100
JV Created
SAR 94,100
D365 Posting — Roadmap
SAR 94,100
Exception Recovery
Opening SAR at Risk
SAR 5,900
Illustrative Walkthrough Recovery
SAR 3,200
Pending
SAR 1,900
Escalated
SAR 800
Bar lengths and figures are illustrative only, not drawn to scale and not client data.
Finance Intelligence

See which provider, bank or store is creating the risk

RetailRecon can turn reconciliation output into operational performance signals for Finance and Treasury.

Provider & Bank Performance Scorecard

Compare settlement quality, delay and exception exposure by payment channel.

ProviderMatch %Avg DelayOpen RiskStatus
MADA / ANB98.7%T+1.2SAR 12.4KHealthy
Visa / MC96.9%T+1.8SAR 18.7KWatch
AMEX94.1%T+2.4SAR 21.3KReview
Tabby / Tamara97.5%T+2.0SAR 9.8KMonitor
Other / RemainingSAR 5.8KMonitor
Illustrative sample data — open risk totals SAR 68K, aligned to the Control Center.

Daily CFO Finance Brief

A short management summary of what changed and what needs attention.

SAR at Risk: SAR 68K across 23 open exceptions
Outside SLA: 7 cases require escalation
Largest Exposure: Store 613 · ANB · SAR 18,420
Recovery this week: SAR 31K — Control Center total
Close Status: 94.8% reconciled; 3 stores require finance review
Reflects this week's Control Center totals (see dashboard above) — the SAR 100,000 CFO View walkthrough below uses a separate, smaller illustrative example.

Exception Priority Matrix

Prioritize by value, age, payment channel and close impact rather than reviewing every difference equally.

HIGH VALUE + OLDEscalate Now
HIGH VALUE + NEWInvestigate
LOW VALUE + OLDReview SLA
LOW VALUE + NEWMonitor

Reconciliation Confidence

Show how much of the close is auto-matched, tolerance-matched, or still needs human review.

AUTO MATCH88.6%
TOLERANCE MATCH6.2%
MANUAL REVIEW5.2%
Illustrative sample data.

Close & Audit Pack

Prepare a finance-ready support package for management review and audit evidence.

Reconciliation summary
SAR-at-risk report
Exception aging
Recovery evidence
Correction history
Maker-checker approvals
JV support schedule
Period close status

Store & Finance Performance

Track recurring issues so Finance can distinguish a one-off delay from a repeated control weakness.

Store performance: missing POS pushes, repeated auth issues, late submission
Provider performance: settlement delay, short settlement, duplicate records
Finance performance: case aging, approval time, recovery closure
Retail Finance Health Check

Start with your current reconciliation process

Before a full deployment, AHENQOR can review the current workflow and identify where settlement risk, manual effort and control gaps exist.

  • Source-file and data-quality review
  • POS / bank / BNPL reconciliation flow
  • Exception ownership and aging
  • Settlement delay and SAR-at-risk exposure
  • Close, JV and D365 readiness
Request Health Check

Request a working product demo

Tell us about your reconciliation setup and someone from RetailRecon AI will follow up within one business day.

  • Live walkthrough of the reconciliation workflow
  • Review of SAR-at-risk detection logic
  • JV preparation & D365 integration roadmap discussion
  • No commitment required
Your request will be sent securely to AHENQOR Technologies.
Deployment Options

Start where it makes sense for your organization

RetailRecon AI is early-stage — pricing is scoped per engagement rather than fixed into standard tiers.

Pilot / Proof of Value

Test RetailRecon using representative client data.
Contact us for a commercial proposal
  • Sample or representative data set
  • Core reconciliation engine
  • SAR-at-risk detection
  • Defined pilot scope & timeline
  • Findings & fit report
Request a Pilot Conversation

Enterprise / Multi-Country

Multiple legal entities, ERP integration, JV preparation, security and SLA.
Contact us for a commercial proposal
  • Multi-entity / multi-country setup
  • JV preparation with D365 integration roadmap
  • SSO / role-based access
  • Dedicated support & SLA
  • Custom security review
Contact Us for a Commercial Proposal

Ready to see where your money actually is?

Request a working demo of RetailRecon AI's reconciliation and financial control engine.