The Analytics Platform

Turning mountains of data into valuable information

The analytics platform categorises and analyses the income and expenditure of the bank data drawn from your customer’s online banking. This enables you to process the transactions in your systems quickly and in a standardised manner. Our analytics platform is constantly evolving and is checked, maintained and continuously developed by our own team using modern machine learning approaches.

ANALYTICS PLATFORM FEATURES

Digital Account Check
Categorisation and tagging

The platform categorises the transaction data from online banking and provides you with a structured overview of the account data. Our self-learning algorithms guarantee maximum reliability.

Expenditure account

Use our analytics platform to create an expenditure account for your customer using digital data. This way, you can obtain an assessment of their solvency.

prediction icon
Transaction data analysis

In addition to information on cash flow, we also provide reports on chargebacks, distraints, budget surpluses and much more.

Riskshield icon
Risk analysis

Our analytics platform identifies risk characteristics in the transaction data in order to identify creditworthiness and fraud risks at an early stage. As a result, payment defaults can be minimized considerably.

Checks to go

Standardised “checks to go” complement our offering. On request, we can prepare standardised reports for you such as tenant checks, credit checks, salary statements or validation of the account holder.

Report generator

With our report generator, you can easily create individual and tailor-made reports to meet your needs.

ANALYTICS PLATFORM FIGURES

Hit accuracy

Categories

Keywords

Bisher kategorisierte Umsätze

Categorised transactions

HOW TO INTEGRATE THE ANALYITCS PLATFORM

One categorisation – Two data access points

Data access via a banking API and XS2A

The ideal solution for FinTechs and challenger banks without historical customer data

Via the Open Banking platform (banking API), your customer grants one-off access to the required account data. An electronic account statement or a selection of predefined analysis modules (individual indicators e.g. risk characteristics or entire reports) are then called up in real time. The data that has been extracted then runs through the analysis process within the analytics platform.

How it works:

The initial call-up by the provider specifies the scope of the analysis.

The user is then asked to log into their online banking system.

Once the user has successfully logged in, the desired results are made available to the provider.

A specific result is available for each analysis module. In addition, a summary of the results of the individual modules can also be viewed in a PDF document.

Datenanalyse mit Banking API
Datenfluss und Kategorisierung ohne Banking API

Data access without a banking API

The tailor-made solution for major banks and house banks with inventory data

The analytics platform without data access via a banking API is ideal for major banks and house banks, because the challenge for them is not gaining access to customer and account data. Instead, the difficulty lies in getting this enormous wealth of data ready for cross-selling and upselling using modern categorization and analysis.

How it works:

The analytics platform analyses transaction data via an upload function and does not require any technical implementation of our banking API.

By calling up an interface, a financial institution sends the account data to the analytics platform in industry-standard formats, such as CAMT format (XML).

Once the data has been transformed, it is categorised by the analytics platform, prepared in the form of an expenditure account and provided with key figures.

After the analysis, the institution can better assess its customers’ behaviour patterns and derive cross-selling potential from them.

White Paper: Smart Data Analytics in the Financial World

How banks and FinTechs can improve the customer experience with Smart Data and machine learning

New models for analysing creditworthiness are based on approaches such as Smart Data Analytics and machine learning. Learn how banks and FinTechs are redefining the customer experience in our new White Paper: Smart Data Analytics in the Financial World.

What you will find in this White Paper:

✔ What does Smart Data mean and how can the financial world reap the benefits of it?

✔ Why bank managers look for guidance when using new technologies such as machine learning.

✔ Three areas from the financial world where Smart Data improves the customer experience.

✔ How the digitalisation of the financial world is accelerating data growth

✔ Interview with Tobias Ruland, CPO at FinTecSystems

✔ Interview with Dr. Moritz-Alexander Felde, Managing Director at CHECK24 Finanzen

Smart Data Analytics Whitepaper

Get advice now!

Do you have questions or want to find out more about our products and services?
If so, send us a message! To find out how FinTecSystems GmbH processes data, please refer to our privacy statement.

  • This field is for validation purposes and should be left unchanged.

DATA SECURITY

Maximum security through certified data centers

ISO 27001 FinTecSystems

Customer data is stored in a German data center certified according to ISO27001.

SSL Datensicherheit FinTecSystems

SSL-encrypted transmission of all data. Double-encrypted access code

FinTecSystems operates in accordance with the strict German Federal Data Protection Act and the EU General Data Protection Regulation (GDPR).

As featured in