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smart data for credit scoring

Lower your default risk rate with superior insights

Maximise scoring accuracy with intelligent transactional data and gain a new layer of insight into your clients' daily lives and behaviours with 99.99% accuracy.

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

Are you absolutely sure you know and understand who your clients really are? What are their habits,needs or wishes? With enriched payment data, you know in an instant.​

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.

How to leverage smart data for credit scoring?

Leverage the power of correct payment categorisation

Tag and segment each individual transaction

25 merchant categories and 500+ ready-made store-level tags
Retail, Business, Investment, Eco and Custom labelling
Subscription labelling

Exceed MCC categorisaton

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

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

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

Tapix enhances any payment type

Bank transfer identification
Card payments, ATM withdrawals and open banking recognitions
Recurring payments, tranwsfers and subscriptions

Get trusted insights and truly understand your clients' lives

Discover more data solutions that empower your analytics teams to make smart strategic decisions.

Be a step ahead

Industry insights

Why MCC codes do not help (much) with payment categorization

We decided to provide our insights into the power of strictly MCC-based categorization and its limits. Categorization is important for credit risk scoring and it is the basis for Personal Finance Management tools. When we analyzed our categorization with MCCs, we saw that only 53% of transactions could be easily and reliably categorized based on their MCC code. Let's have a look at the most frequent problems we identified that make MCC usage more difficult than it may seem at the first glance.
Industry insights

From Chatbots to Credit Scoring: How the AI Act Affects Banking

For the past several years, AI has captured the attention of many industries, including finance and banking, where it’s been helping institutions to automate many important services and solutions. In the meantime, the European Union has taken a significant step forward with the introduction of the EU AI Act.What exactly is the EU AI Act, and why does it matter? In this article, we'll introduce the basics to provide you with a comprehensive understanding before we explore its implications in more detail and check the AI readiness of the banking sector. According to Arizent survey, 56% of users would welcome the help ofAI in their financial recommendation services while 48% see it as a tool for evaluating credit or loan applications.
Industry insights

How to build top-notch personal finance management tools? Focus on data

Rising inflation, economic recession, rising prices of absolutely everything... The times are not exactly conducive to splurging, quite the contrary.

Switch to Tapix today!

Explore how Tapix can help you get the most from transaction data, increase your app engagement and turn UX into your competitive advantage.