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Transaction Data Enrichment

Smart data for Credit Scoring

Maximize scoring accuracy with smart transaction data and gain a new layer of insight into the daily lives and behaviors of your clients with 99.99% accuracy

Lower your default risk rate with superior insights

Are you sure you know who you're lending money to?

Even a seemingly decent person...

Analyzing income, expenses, and behavior patterns can take time. Are you certain you truly know who your loan applicant is by the end?

...can actually be someone else

Identifying a risky gambler from a successful manager with a family can be tricky. However, with a structured transaction history based on detailed payment categorization, merchant identification, and purchase location recognition, you’ll know immediately.

Trusted by 50+ global banks and fintechs


Why use enriched transaction data for credit scoring?

Real time scoring for any service

Empower your scoring model with structured insights from real-time transaction history data for any payment service, including PSD2

Avoid reputation damage

Boost your reputation by lending to creditworthy and trustworthy clients and prevent rising delinquencies with useful data insights

Turn subprime loans into your advantage

Uncover your client's subprime loan payment data and leverage these insights to perfectly target your offers or sell own subprime loans.

Your Credit Scoring is only as good
as the entry

Leverage the power of correct payment categories

Make payment analysis truly insightful through segmentation and tagging for each payment.

25 merchant categories and 500+ ready-made store-level tags
Custom categories and tags
Retail, business, investment and CO2 labelling

Far beyond MCC codes

Gain deep insights into specific client lifestyle and predict behaviour with a Four-level transaction categorisation system.

Merchant categories
Unique store-level tags
Categorisation coverage
Data accuracy

Examples of behavior patterns
using enriched categorisation

Meet David, a regular employee who rents an apartment and spends a lot on groceries, water parks, and children's toys, indicating he’s a dad. He regularly pays at 3 locations, likely near his home or workplace. David eats lunch around the office on weekdays and grocery shops in the evenings or on weekends. He’s also an avid weekend traveller who enjoys swimming and cycling. This detailed categorisation reveals his lifestyle and spending habits.

Artificial intelligence in credit scoring? Yes, but...

...there is a piece of European Commission legislation called the "AI Act". Learn how to incorporate AI Act compliance into your risk management strategy.

Read the article

Discover behavioural patterns from spending locations

Knowing where your clients live, where they pay and where they actually live will help you better understand and predict their living expenses.

Street, zip, city, region, county and country
Identification to the level of individual stores in large shopping centres
Physical store, e-shop and online payment recognition

Understand who your
clients actually pay

Get a clean and accurate merchant name for every single transaction (both income and expenditure)

Identification to the level of individual stores in large shopping centres
Sub-brand recognition (e.q. Marks & Spencer vs Marks & Spencer Foods)
Franchise recognition (e.q. Amazon vs Amazon Prime)

Retrieve enriched transaction in 3ms

With high scalability, TapiX is is designed to handle the needs of the world’s largest banks.

Today we enrich over billion of transactions per month across EMEA, LATAM and NCA regions with coverage ranging from 65-85% and 99.99% accuracy.


Recognised merchants


Store-level category tags


Unique locations


Data accuracy


Markets covered

1.5 bln

Enriched Tranactions
per month

Success story

How bunq provides
data-driven insights?

bunq - the Dutch challenger bank was struggling to achieve a high coverage of merchant reconciliation. Learn more about how TapiX helped them through payment data enrichment.

Read success story
"As an entirely mobile bank, the pressures of innovating to match expectations is something that we thrive under. The mobile revolution has made a massive impact on society both in the way we communicate but also the rate at which we want our needs to be met. This is something that our partners at Dateio clearly agree on."

Ali Niknam

Founder & CEO at bunq

"TapiX is a great solution to enhance the customer transactional banking experience. In my view, such solution is a must for any modern bank."

Alexey Kapustin

CEO at Raiffeisen Digital Bank AG

„In a quick 3-month integration, TapiX's data met and surpassed AN4569 standards, enhancing the overall payment experience for our users. We value our cooperation with TapiX as it grants us instant access to accurate global merchant data.“

Alex Friedli

Chief Operating Officer at Swisscard

„We welcome the cooperation with TapiX as it gives us instant access to worldwide merchant data. This way we can provide better payment insights to our users without having to start worry about gathering the data ourselves.“

Leen Asfour

Product Lead at Reflect by Arab Bank

Ready to take the next step?


Bring more value to your users through enriched payment data

How do you ensure data quality?

TapiX uses multiple controls based on statistics, outlier detection and various algorithms to provide you with the best data quality possible. Data quality is supervised by our data team to prevent any mistakes. Due to the complexity of data quality checks, TapiX receives less than 1 complaint per 6 000 000 processed transactions.

Are our clients data secure?

Through the API you only transfer the terminal identifiers. TapiX fulfills the highest security standards and processes no personal information about your clients. We are ISO 27001 certified and GDPR compliant. Dateio stores and processes data in AWS which fulfills the highest security standards.

How do you ensure data quality?

Note that if TapiX returned an “unsolved” shop it might be due to multiple reasons. The data provided might not be sufficient enough to identify the correct shop (e.g. not enough parameters provided) or TapiX simply does not recognize the shop now. TapiX always returns as much information as possible but it is always possible that some information about the shop or the merchant may be missing. Note that the quality of the service improves over time and your data can be solved in the near future.

Be one step ahead

Guides, tips, success stories, industry insights and more

How to Build a Digital Bank in 2024

Learn how banking is evolving to build your own neobank
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The World of ATMs: Why data and cash still go hand in hand

Learn how the ATM environment works and why data matter
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Enhancing Developer Experience in Transaction Data Enrichment

Learn why developer experience is crucial in transaction data enrichment and how TapiX ensures seamless integration, fewer errors, and higher productivity for developers.
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Unlocking Banking Solutions Through Transaction Categorisation

Learn about the transaction categorisation and its role in banking solutions
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Beyond the AI Act: How are banks using AI in 2024

Learn about how banks can use AI in 2024 and beyond
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Understanding the EU AI Act: Impact on AI and Banking Regulations

Learn about the AI Act and how it affects AI systems in banking. Gain insights into compliance, risk assessment, and the importance of high-quality data management under the new legislative framework.
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