Open Positions
Tech Blog
Case Study
News

Industry

Financial & Banking

Financial data and crucial patterns… Or heaps of seemingly unrelated information? Intelligence makes all the difference

Stay ahead, stay secure

Use your huge databases to improve risk management strategies, optimize day-to-day tasks, and gain a competitive edge.

Fraud  detection

Finance forecasting

Risk  Analytics

See case studies

Why smartcat

Simplicity. Streamlined.

ML Solutions in production

data Lakehouse implementations

referrals

offices globally

Partnerships

Shaping the industry together

We believe in partnerships. We collaborate closely with you to co-create data solutions that shape the industry landscape.

what our clients say

“They feel like a partner, not just a contractor”

The best minds should use their brilliance to interpret the findings instead of spending hours sifting through documentation. Harness financial data through AI systems and make decisions rooted in hard analyses.

MR. Work

“I've experienced SmartCat’s experience both in the field of Big Data and general software development and agile planning. With the SmartCat team, we found not only a Strategic Partner to finetune our vision and roadmap but also a team of specialist engineers who are able to deliver high quality in a well-organized way.”

Zeno Lampe

IT Manager

cognism

“SmartCat over-delivered on our project while doing it successfully and on time. Transparency was key to our collaboration. It has been a pleasure to work with them.”

James Isilay

CEO

Invenda group ag

“Working with SmartCat has been an incredible experience. Their team helped us to create an AI-Ready Data Lake platform. What sets SmartCat apart from other options is their approach to their work - they feel like a partner, not just a contractor.”

Petar Jerinic

Cloud Team Lead

Patchai

“SmartCat assisted us since the inception of our product idea and helped us create a Smart and Data-driven-By-Design digital healthcare platform. Patients and doctors, our users, have never been happier.”

Filip Ivančić

COO

Telenor

“Very smart people, great company. With detailed preparation and data sharing principles in mind (GDPR and security) they helped us develop algorithms to get the probability that customers will churn.”

Saša Radovanović

Data Science & CLM Team Leader

Meridian

“Just like everybody else, we had data. But we needed help on how to tackle the issue of extracting useful information from our data. We are totally happy with the state-of-the-art AI engine SmartCat has created for us. This enables us to provide unique experience to our customers by using SmartCat's data-driven AI model."

Nenad Radanović

Head of Software Development

Vakanties.nl

“As a Data Engineer, I was the Project Manager for the vakanties.nl DataOps project. It was a pleasure working with SmartCat on the project, they created a DevOps solution for our data warehouse in Google Cloud. The experts working for SmartCat are very experienced in the field of big data and software engineering. The end result is that we have a scalable, serverless, fully automated CI/CD environment which we can build upon. The SmartCat project members were always punctual, driven and took ownership of the whole process. I will be happy to work together with them in the future.”

Tim Ebbers

Data Engineer

scholarship owl

”We have worked with SmartCat to develop a number of AI-based projects, and since we've been hesitant about the scope and size of the project, SmartCat suggested a "Time and Mastery" model, with min-max estimates and success criteria. SmartCat has blown it out of the water - the quality of work and speed of delivery was top notch, and we gladly paid the max price, because they substantially overachieved the goals we've set together. We've just finished our second project with them, with the 3rd one coming soon!”

David Tabachnikov

CEO

Coosto

”Smartcat helped us out in short term, provided expertise on the matter and responded promptly to additional questions we had. The reason that I would recommend SmartCat is pragmatic approach and honest pricing.”

D. van Roon

IT Director

Turn raw numbers into strategic insights

In a sector where the margin for error is slim and stakes are high, data solutions are the investment that yield significant return. Gain a competitive edge, mitigate risks, prevent fraud, and make informed decisions that drive success in the ever-evolving landscape of finance and banking.

Decoding Data Challenges: From Limited Data to Informed Decisions

Overcome obstacles like limited data and the cold-start problem by using advanced modeling techniques to drive data-driven insights and enhance business strategies.

Make Financial Decisions with Confidence Intervals

Empower users with confidence intervals, providing a range of expected outcomes for informed financial decision-making, backed by data-driven predictions.

Smart Facts Related to our case studies

Think of your data as a gold mine of insights that can help you innovate and grow in ways you might not have thought possible. Here’s a list of usual wins when using data properly.

Limited Data and Cold-Start Challenges

Limited data and the cold-start problem didn’t hinder meaningful predictions of cash flow and purchase patterns for end customers. Leveraging available information and modeling techniques proved effective for driving data-driven insights and enhancing business strategies.

Gain valuable insights from external data

Enhance your invoice history data with macroeconomic indicators and holiday information specific to regions and timeframes. This broader context uncovers hidden purchasing patterns and enriches your predictions.

Uncover hidden patterns through analysis

Dive deep into your data to uncover recurring trends, such as monthly purchase patterns. By understanding the absence or presence of seasonality for individual customers, you can make more accurate predictions.

Embrace the power of longer time frames

When predicting purchases, extend your time frames to 30 days or more. Longer time periods allow you to capture significant patterns and improve prediction accuracy.

Continuously innovate and expand

Embrace ongoing improvement by incorporating data from more companies, clustering customers and companies for enhanced insights, and integrating additional data sources. These steps unlock new possibilities for your models and open doors to innovative applications.