Engineering Innovation in
Digital Finance
We implement AI and Machine Learning methodologies to estimate the future propensity of millions of customers of a leading European banking group to apply for mortgages and credit lines.
Approach & Solution
Approach
One of the leading banking groups in Europe is committed to supporting the economy in the countries in which it operates, particularly in Italy, where it is a leader in every sector of activity (retail, corporate and wealth management).
It constantly works on solutions and products that allow even who is traditionally excluded from credit to be able to build their own life project. To support this mission and be able to provide products such as mortgages and overdrafts, we have used advanced Machine Learning and Deep Learning techniques to create models capable of estimating the future propensity to request / underwrite these products and thus provide support to Marketing campaigns, aimed to develop cross selling.
It constantly works on solutions and products that allow even who is traditionally excluded from credit to be able to build their own life project. To support this mission and be able to provide products such as mortgages and overdrafts, we have used advanced Machine Learning and Deep Learning techniques to create models capable of estimating the future propensity to request / underwrite these products and thus provide support to Marketing campaigns, aimed to develop cross selling.
Solution
The activities of our team followed the iterative methodology CRISP - DM ("Cross Industry Standard Process for Data Mining") suitable for the implementation of Data Science projects, which begins with the study of business requirements and continues with the understanding and preparation of data, converging towards the implementation and evaluation of the model, up to the deployment in production.
The latest AI and Machine Learning technologies were used for development, such as the Tensorflow framework via Python language.
The software was released as a service on the Openshift platform based on docker-container.
The latest AI and Machine Learning technologies were used for development, such as the Tensorflow framework via Python language.
The software was released as a service on the Openshift platform based on docker-container.
Results
Increased redemption of Marketing initiatives
Growth in Cross Selling
Improvement of customer profiling and segmentation
Project value
Innovation
Process performance
Enabling Technologies
AI & Advanced Analytics
Project Team
Data & Analytics
Finance
Nexen
CRM & CX Consulting Services