No serious business venture of the 21st century can strategize without relying on Data Science. Our Data Scientist will give you insights and information, which will shape the success of your business for the years to come. Whether you need to understand your clients and their behaviour better or predict a niche market based on past data – we help you with that. We are working with large European banks and insurances, but also mine data for a pharma company, or T-Mobile in Germany. At Profinit, we can guide your business through the Data Science journey from A to Z.
DATA SCIENCE ALGORITHMS
Our team have developed a mighty set of specific Data Science algorithms, that will help you to create business value and mine the gold from your data. These have already been successfully deployed in a number of industries including Banking, Finance, TelCo, and more. The list below serves as a brief introduction. If you understand better how these models work, please download our whitepaper about Data Science algorithms in Banking.
Built to detect all outgoing loan payments from your bank to other banks and financial institutions. Enabling you to offer your clients a loan transfer or a consolidation.
Correlates people in time and space to reconstruct family relationships between clients. This knowledge can be used to improve a person’s risk score or to make a much better-targeted marketing offer. It significantly improved success rates for many of our clients.
Detects employer-employee relationships in transactional data. Subsequently, you can tell which of your clients work together for a single company, determine who is a newbie, who is the boss, who got promoted, and who got fired!
Interest rate optimizer
Optimize your interest rates and increase client satisfaction. Improves acceptance, reduces turnover, and boosts profit by taking into account the price-sensitivity of each client, while still complying with strict banking regulations.
Uses transactional data to find behavioral patterns of your customers and discover their tendencies. The result is a propensity-to-buy score for each individual client and product. Provides insights like: “The propensity to take a consumer loan for this client is 12x higher than average”.
Early warning system
Automated and robust anomaly detection tool with easy-to-use calibration features to cope with complex use-cases like monitoring import errors in very large data warehouses or fault detection in any time series environment.
After gaining experience on many projects from several industries, at Profinit we prefer to start our work by sticking to some basic Data Science methodology.
- Business Understanding
The initial phase of any project is key. At this point we aim to understand and define the purpose of our future data model, who is the client, what are his needs and expectations, and how we are going to measure a successful outcome.
- Data Understanding
Through exploratory data analysis we capture the data essence and start verifying hypotheses about relationships between variables versus the target variable.
- Data Preparation
Preparing the data for modelling is usually the most time-consuming task of a Data Science project. From experience we can tell that upon first encounter data cleaning can take 60 up to 90% of total time dedicate to a project. However, once this step is accomplished and if we use an already purged data source repeatedly, this ratio drops to ca. 10%.
- Modeling & Evaluation & Deployment
What follows is the creative process of modelling, evaluation and final deployment. Continuous tweaking and rethinking inherently play a crucial role during these three stages. Click here to gain access to our whitepaper on Data Science workflows and understand our methods in detail.
DATA SCIENCE ANALYTICS
Data Science is a complex field bringing together only the best quantitative approaches to data. At Profinit, we usually analyse anonymized data on location. This gives the client complete control of access and the information we deal with. In many cases, the client already has a particular question in mind and wants us to deliver the answers. Other times, businesses approach us with their data and are looking for inspiration and help with data mining. We excel at both!
What we see with many clients is that their dedicated teams can struggle with adopting the Data Science toolkit and would benefit significantly from external support and expert guidance. Our Data Science team can help you introduce new approaches and innovative changes within your company and facilitate vivid know-how exchange!