Building reliability in risk
SAS helps optimize and integrate analytical models across business processes
Well-informed credit decisions
backed by advanced analytics
Banca Mediolanum achieved this using • SAS® Analytics • SAS® Risk Modeling • SAS® Visual Data Mining and Machine Learning on SAS® Viya®
Banca Mediolanum uses SAS Viya to develop high-performing, reliable credit scoring models
Risk management is no longer an abstract function to develop risk models when needed and meet regulatory requirements. It is a strategic business asset used in credit scoring.
At Banca Mediolanum, which has more than 2.2 million customers, risk management is cross-functional and affects each department. The evolution of credit scoring models represents a significant shift at the bank. This path has led to the adoption of sophisticated, advanced analytics solutions based on artificial intelligence technologies, such as machine learning, to increase the reliability of credit scoring models.
Banca Mediolanum has used machine learning and deep learning techniques well before the new regulations were put in place. This allowed us to consolidate our use of advanced technologies in model validation. Stefano Biondi Chief Risk Officer Banca Mediolanum
Technological innovation provides a smooth transition
When the European Banking Authority changed its definition of default to include stricter criteria and change the way banks and financial intermediaries classify clients, Banca Mediolanum had to find a way to adapt.
“Banca Mediolanum has used machine learning and deep learning techniques well before the new regulations were put in place,” says Stefano Biondi, the bank’s Chief Risk Officer. “This allowed us to consolidate our use of advanced technologies in model validation.”
Not only has the bank’s investment in new technology allowed for a smooth adaptation, but it allowed the bank to exceed the threshold of 30 billion euros in assets in its last balance sheet. The profit Banca Mediolanum has gained from adopting reliable, advanced analytics reinforces that it took the right path, providing strong support for needed business improvements as well as a faster time-to-market.
A successful pairing of the best models and the latest technological advancements
SAS solutions have been an integral part of Banca Mediolanum’s successes. The constant innovation SAS supports enables continuous improvement of the bank’s technological platform.
Banca Mediolanum knew credit scoring improvements were the next step. Using SAS Viya, the bank developed several models simultaneously and verified their validity during development. The bank also used machine learning and deep learning techniques in the development phase – both techniques are critical for scoring models in the digital lending domain. The technology SAS provided ultimately strengthened Banca Mediolanum’s credit scoring and improved its service.
Banca Mediolanum – Facts & Figures
euros in assets managed and administered
Transparency and openness, a fundamental shift
“The platform makes available traditional algorithms and the most advanced machine learning algorithms as well as neural networks for sophisticated deep learning,” says Fabrizio Manstretta, Head of Credit Risk Management at Banca Mediolanum. “A fundamental aspect for ensuring clarity in communications with supervisory authorities is model transparency and the ability to easily understand analysis results. SAS allows for all of these crucial components and more.”
Integration is ensured by an open platform, which allows integration with open source codes, in-memory operations and development in container as a service. These features enable a high-performance platform that is accessible online.
“We have seen large improvements not only in terms of faster development and release, but in terms of reliability and security,” Manstretta says.
Implementing the open platform has been a migration path toward an evolved platform. SAS Consulting and technology partners were crucial considering the technical component of the project, the functional and process skills, as well as the collaboration with the internal team.
Next steps: Extend the application of advanced models in business processes
“At the beginning, we started with the needs of risk management, but it was a catalyst for innovation for other business units,” Biondi says. The bank soon realized the power of the advanced analytics laboratory and is working on various projects in model development. This includes the creation of new credit products, as well as exploring the potential of open banking and PSD2 by using the most advanced big data analysis capabilities.
Biondi concludes that Banca Mediolanum’s advanced analytics laboratory, thanks to SAS Viya, has sufficiently prepared the bank for the future, and it’s excited for upcoming opportunities to enhance its services.
We have seen large improvements not only in terms of faster development and release, but in terms of reliability and security. Fabrizio Manstretta Head of Credit Risk Management Banca Mediolanum
The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.