Artificial Intelligence in Banking

Big Data and Artificial Intelligence are transforming how banks operate across the board – from Robo-Advisors and Fraud Detection to customer service chatbots and churn prediction. Learn all about the best practices, based on our experience, and start your own Data Journey with [at]. 



Artificial Intelligence (AI) is a general term that covers various sub-disciplines within mathematics and computer science. In simple terms, AI are intelligent programs that perform specialized, sometimes highly complex tasks – in many cases better even than humans could. Some of the best known AI methods are Supervised and Unsupervised Machine Learning, Deep Learning, Neural Networks and Natural Language Processing (NLP).

A study by HTW Saar reveals some interesting figures pertaining to Data Science & Artificial Intelligence in banks.


of banking institutions deploy AI applications as part of their regular operations


of these banks have not introduced adequate AI governance


of the surveyed banks have a defined and fully implemented AI Strategy.



AI technologies accelerate banking processes, make money transfers more secure and improve efficiency for back-end operations. Banks can use AI to transform the customer experience by enabling seamless customer interactions 24/7 across multiple channels. But AI banking applications are not just limited to retail banking services. Business clients, investment banking and all other financial services also stand to benefit from AI.

The use of Artificial Intelligence has the potential to enable massive increases in efficiency and yield in all areas. The use of chatbots and robo-advisors can save resources and reduce costs. Customer loyalty can be strengthened with the help of personalized offers and additional functions based on the evaluation of customer Data. Entirely new target groups can be tapped by developing new, Data-driven products, such as (to give an example) microloans, granted directly via smartphone in real time by linking a wide variety of internal and external Data with the aid of intelligent algorithms.

Assessement Workshop

You do not know how to implement your data strategy in your company? With the Data Strategy, our experts will introduce you to the 5 most important elements and present best practices. Afterwards, the current status and the target picture for the 5 dimensions are evaluated. The dimensions include organizational structure, processes & use case pipeline, roles, data governance and IT system landscape. This makes it possible to derive concrete recommendations for action and to develop an individual data strategy.


New Business Models

Unlock new demographics using digital products and channels of distribution.


Reduce Costs

Significantly reduce expenditure of resources through process automation.

Customer Experience verbessern

Identify and react to customer needs with the help of Data-driven solutions.


The use of Data Science and Artificial Intelligence is already having a massive impact on the banking sector. Banks have access to vast amounts of Data that hold enormous potential. In the following, we will introduce a selection of fields in which Artificial Intelligence can be used in banks and enterprises:


Fraud Detection

Detect and successfully combat fraud attempts in real time.

Predictive Banking

Predictive Banking

Provide customers with transparency and predictability regarding their own finances through analysis and Data-driven banking.

Robo Advisors


Tap into new customer segments by automating recommendations and management of investments.


Credit Scoring

Reduce default risks with AI-supported credit scoring tools while also greatly speeding up credit decisions, at times even to the point of making them in real time.



Free up and optimize customer service and back offices by deploying virtual assistants and digital robots in customer communication.

Churn Prediction

Churn Prediction

Identify customers at risk of churn and retain them by addressing them with the right offer in a targeted manner.

Reference projects of our customers

The Data & AI experts at Alexander Thamm have already successfully implemented more than 1.000 projects – including over 100 projects in the finance industry.

Fraud detection using network analysis

Fraud detection using network analysis

  • Fraud is detected earlier or even avoided entirely
  • Novel visualization tool for identifying hubs and product relations
  • Improved identification of client & transactional relationships
Credit Scoring

Credit Scoring

  • Defaulted loans reduced by over 90%
  • Precise determination of default probabilities for each individual client
  • Increased flexibility when granting loans
Community Score with AI

Community Score

  • Evaluation of individual user activity within the community
  • Scores offer users incentives
  • Complete overview of activity in the community
Customer Lifetime Value with AI

Customer Lifetime Value

  • More precise calculation of customer lifetime value
  • Sankey diagram as part of an interactive dashboard to better illustrate client history
  • Interactive visualization of the Customer Journey
Implementation of a Credit Scoring model

Implementation of a Credit Scoring model

  • Implementation of a Random Regression Forest in Spark and H20 (Sparkling Water
  • Automated retraining of the model using current Data made possible
  • Compliance with all risk management requirements
Fraud Prevention for vehicle financing

Fraud Prevention for vehicle financing

  • Number of salary statements that need to be checked manually reduced by 56 %
  • Consistent fraud detection rate
  • Optimization of internal processes


With the help of Data and Artificial Intelligence, we enable our customers to constantly change and adapt in the digital age. We empower our customers to develop their own strengths and accompany them on their way with our [at] Data Journey.

The possible applications of Artificial Intelligence in the banking business are huge and offer incredible potential. With our many years of experience in the financial and banking sector, we can support you in identifying and implementing the right Use Cases to generate real added value from your Data and in developing new business models for your enterprise.


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Our Customers



We have used our experience from over 1.000 projects over the last 8 years to develop a holistic system for Data & AI projects – our Data Journey. An integrated Data Strategy forms the foundation and the framework for generating real added value from Data – what we have dubbed Data2Value. Our Data Lab is all about speed! Their main goal is to test Use Cases as quickly as possible – from the concept phase to the prototype using real Data. In the Data Factory, Use Cases are industrialized into finished products. The absolute main focus is on scaling and the sustainable generation of added value – therefore the end user is just as much the focus here as well. In our DataOps we continuously operate and maintain your platforms and machine learning algorithms.

AT Data Journey


Leader in AI and Big Data

We have been recognized as the # 1 Value Creator in machine learning by CRISP Research as well as a Big Data Leader in Germany by numerous experts.

Technology-independent consulting

We operate independently of manufacturers. We strive to find the right technology for our customers according to their needs and support them in implementing it.

Experts in AI in the insurance industry

We have successfully completed more than 1.000 AI & Data Science projects, over 50 of them within the Finance & Insurance industry.