For banks, card issuers and payment providers
Turn transaction data into
customer moments.
✓
Merchant, category and context for every posting
✓
Consent and purpose documented per signal
✓
Data quality check in two weeks, then CLM
Data quality module available on the platform. Last updated: October 20, 2026
One posting
Example
Raw data
PAYPAL *NETFLX 4029357733 LU · €17.99
MCC 4899 · unknown
Enriched
Netflix · Streaming · monthly · for 14 months
Subscription detected · price +€2 since May
○
Illustrative concept
Your rules
Personal Finance Management
Next Best Action
Top of Wallet
Transaction data
EUDI Wallet
Virtual advisor
Customer Data Platform
Hosted in Frankfurt
Consent first
up to 5×
faster growth for institutions that put data at the center
23 Jan 2027
Visa requirement for enhanced merchant data in the app; Mastercard AN4569 in force since October 2023
≈ 60%
of failed digital conversions are due to unsuitable or generic offers
Raw vs. enriched data
Transaction categorization: the same posting, two worlds.
This is how a posting arrives from the card processor. And this is what it looks like after the five enrichment stages.
SUMUP *CAFE MILCHB MANNHEIM DE 4.80
Café Milchbar, Mannheim · Dining · 3rd visit this week · regular merchant
LH 2201234567 FRA 11/17 412.00
Lufthansa · Travel · flight on Nov 17 · signal “trip ahead” · offer travel mode
STANDING ORDER 850.00 DE89 3704 …
Rent · Housing · monthly · amount +€50 since September · signal “move or rent increase”
SALARY MUSTER GMBH 3,420.00
Salary · Income · 28th of the month · primary-bank indicator · savings nudge after payday
The five enrichment stages
From posting line to signal.
Each stage builds on the previous one. The first three are data quality; the last two turn data into a basis for decisions.
Merchant cleansing
Cryptic descriptors are resolved into merchant name, logo, location and website. Payment-provider prefixes such as PAYPAL, SUMUP or KLARNA are traced back to the actual merchant.
MCC consolidation
Merchant Category Codes are coarse and often set incorrectly. We consolidate MCCs with merchant knowledge into a taxonomy your bank understands: housing, mobility, travel, subscriptions, health, dining.
Categorization and anomalies
Machine learning assigns categories per posting and detects deviations: unusual amounts, new merchants, duplicate charges. The data quality module flags outliers before further processing.
Recurring payments and life events
Subscriptions, rent, salary and installments are recognized as series, including price changes and missed payments. Patterns such as a move, a new child, a trip or a job change are flagged as signals with confidence scores.
Consent governance
Every signal carries purpose, legal basis and consent status. What the customer has not allowed is not used. This makes the signals usable for PFM, Next Best Action and assistants, with audit-proof traceability.
What it enables
Four applications, one data foundation.
Enriched transaction data is not an end in itself. It powers the use cases customers notice and you can measure.
Personal Finance Management
Spending insights, subscription tracker and due-date forecast need clean categories and recognized series. Without stages 1 to 4, PFM stays a transaction list.
KPI: app engagement
Next Best Action
Life-event signals and merchant patterns are, as our blog argues, the most important NBA signal. They deliver the timing, not just the propensity.
KPI: conversion per contact
Retention and account primacy
Salary gone, standing order to a neobank, term deposit maturing: outflow signals are transaction signals. Detected early, there is time to act.
KPI: deposit volume
Virtual advisor
An advisor that should answer “what do I spend on subscriptions?” needs stage 4. An advisor that is allowed to needs stage 5.
KPI: resolved requests
Offer
Data quality check in two weeks.
Before you invest in PFM or Next Best Action, we check what your data can deliver today. You receive a sample analysis of your transaction data with coverage rates per enrichment stage and a prioritized use-case list.
✓
Anonymized sample of 50,000 to 500,000 postings
✓
Coverage per stage: merchants, categories, series, signals
✓
Gaps, error sources and mandate status (Mastercard AN4569, Visa)
✓
Prioritized use cases with data requirements and a first KPI
Timeframe
2 weeks
Result: one report, one decision paper, one proposal for the first use case.
Architecture and integration
Connected to core banking, card processor and CRM.
Enrichment runs as a service next to your systems, not inside them. Data arrives by batch or event stream; results flow back into CDP, data warehouse, app and CRM.
Integration architecture: sources on the left, enrichment in the middle, consumers on the right.
Sources
Core banking (accounts, standing orders), card processor (authorizations, clearing), CRM (master data, consents), scheme data.
Enrichment
Five stages as API and batch job, models per tenant, data quality monitoring, audit-proof logging.
Consumers
Customer Data Platform, data warehouse, banking app, CRM campaigns, virtual advisor.
Comparison
Three routes to enriched transaction data.
In-house rules, scheme data only, or a platform with enrichment and CLM: the routes differ in coverage, maintenance effort and connection to actual use.
Grows slowly, maintained by your own team
Good for card spend, no account postings
Card and account postings, merchant knowledge plus models
Rigid rule sets, drift over time
MCC-based, coarse
ML categorization with anomaly detection
Rarely implemented
Not included
Subscriptions, salary, rent, installments, event signals with confidence
Manual
Not included
Purpose, legal basis, status per signal
Separate projects
Separate projects
Directly into PFM, Next Best Action, advisor
Own infrastructure
Scheme infrastructure
Frankfurt, on-premise on request
Scheme data and ACCELERAID are not mutually exclusive: merchant data from the mandates is taken in as a source in stage 1.
Data protection & security
Privacy is architecture. Built for regulated banking.
Data protection is architecture, not a feature. The platform connects to core banking, card processor, CRM and app and runs where your supervisor expects it to.
Privacy by design
✓
Consent per purpose
✓
Hosted in Frankfurt
✓
PII filter before the model
✓
No cross-tenant training
01
GDPR & DPA
A data processing agreement, purpose limitation and deletion concepts are part of every project, with a joint data protection impact assessment on request. Every use of customer data is tied to a documented purpose and a consent.
02
Hosted in Frankfurt
Private cloud in the ISO 27001 certified data center in Frankfurt, on-premise optional. Data stays in Germany.
03
PII filter before the model call
Personal data is detected and masked before a language model sees a request. No cross-tenant training: customer data only trains the bank's own models.
04
Tenant separation
Each bank runs in its own logically separated environment with its own keys, roles and logs.
05
SOC 2 Type I certified
ACCELERAID is SOC 2 Type I certified; the report is available under NDA. Audit-proof logging is standard.
06
Enterprise hosting
Enterprise hosting in the PCI DSS certified data center. The ISO 27001 and PCI DSS certifications apply to the data center.
Signals are only used with consent and within defined rules. Automated individual decisions within the meaning of Art. 22 GDPR are not intended; assessing individual processing activities is up to your data protection officer.
The agreed configuration, the contract and the related evidence, such as the SOC 2 Type I report, are authoritative.
FAQ
Frequently asked questions about transaction data.
What banks want to know before they start.
What does transaction data enrichment mean?
What are Merchant Category Codes, and why are they not enough?
What do the Mastercard and Visa mandates require?
How long does integration take?
What role does consent play?
Can we use the enriched data outside ACCELERAID?
Which data leaves the bank?
Read on
Where to go next.
From the blog
Data & Technology
Mastercard AN4569 and Visa's Enhanced Merchant Data: When the Bank Has to Explain Every Transaction
CLM & CVM
Why transaction data is the most important signal for Next Best Action
Data & Technology
Enrichment of Bank Transaction Data: How Banks Turn Transaction Data into Strategic Intelligence
What can your data deliver today?
Two weeks, one anonymized sample, one report with coverage rates and prioritized use cases. Then you know where to start.