Financial services

Reduce risks and operating costs with AI

Traditional financial services providers need to look for better ways to get customers attention, introduce new services as well as protecting their business against issues like fraud or money laundering.

Our team at Gauss Algorithmic has created proven and valuable solutions for institutions like banks and insurance companies that can help them use data and AI to bring innovative services for their customers while reducing risk and overall costs.

Benefits

Engaged customers

Know Your Customer. Processing digital customer data is key to optimizing the consumer experience.

Build trust

Combining new data sources and AI can significantly improve security options and reduce risk.

Efficient processes

Understanding process inefficiencies through the data can help reduce the leakage of revenue.

Accurate decisions in real-time

Accuracy is as important as the speed. Use of machine learning helps continuously improve scoring models.

Increased employee productivity

Automate repetitive tasks with AI and allow your employees to concentrate on bigger problems.

Ease regulatory compliance

Reduce the chances of human error and enable more automated options to comply with areas like anti-money laundering and customer data privacy.

Solutions delivered by top AI experts

We have a proven track record of implementing AI solutions in a number of industries. We’ve had great successes and also discovered dead ends. With many years of experience, we are helping financial services organizations reduce risk when implementing these state-of-the-art technologies

Where we help

Smarter lead generation

Find new customers faster while reducing the costs to acquire them.

automatically generate real customer journeys

enable real-time event processing

use machine learning to cluster similar customer behavior and journeys

enhance customer profiling and segmentation

use external data sources to target new potential customers

Customer experience and personalization

Understand the reasons behind a customer using your product and create a personalized experience.

recommend products & services in real-time

personalize credit decisions

personalize the content of web and mobile

talk to customers their way on their favorite device

provide important customer events in real-time to applications

Risk management

Increased quality and reliability of data can significantly improve and speed up the entire risk validation process.

know customers and get them where they want faster without increasing risk

use new external data to get deeper insights and make better decisions

detect anomalies in customer behavior

automate repetitive processes and reduce human error

Faster prototyping and rapid development

Reduce operational inefficiencies and bring new solutions to the market faster.

modernize your data architecture

introduce cloud and containerization

automate testing

build environments for data science

Case studies

Stories of our successful clients whom we‘ve helped push their business forward using data.

All case studies

Financial services Retail

Raiffeisen Bank – Smart Lead Generation

Discover the needs of your customers at the right time and start talking to them ahead of the competition

More info about Raiffeisen Bank – Smart Lead Generation

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