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Microsoft Partner: Silver Data Platforms & Data Analytics

Gartner recognizes Profinit in accelerated technology modernization

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Profinit es una de las empresas líderes en Desarrollo de Software a Medida, IA y Ciencia de Datos, Consultoría y Externalización de TI. IDC Research clasificó a Profinit como el tercer mayor desarrollador de aplicaciones personalizadas en la República Checa. Somos parte de Amdocs, un líder mundial en software y servicios para empresas de comunicaciones y medios. Esto nos permite combinar una profunda experiencia técnica con recursos globales y ofrecer soluciones innovadoras y personalizadas que satisfacen las necesidades específicas de nuestros clientes.Clientes clave: Erste Group, O2, BNP Paribas, KBC Group, Vodafone, Deutsche Telekom, Raiffeisenbank, Allianz, Société Générale, Prague Airport, CEZ Group, VIG (Vienna Insurance Group), Edenred, ING, NN, Darag, M.M. Warburg, Amplifi Capital, Confirmo, Bottomline, Nord/LB, BerenbergServicios de Profinit:- Desarrollo de software a medida- Servicios de externalización de TI y Nearshore- Externalización de la gestión de aplicaciones- Diseño y desarrollo BI/DWH- Ciencia de datos e IA- Integración empresarialLos principales clientes de Profinit incluyen empresas bancarias, de seguros, farmacéuticas y de telecomunicaciones en Europa Central y Occidental. La empresa también presta servicios a una serie de otras organizaciones del sector público y privado.Los clientes utilizan los servicios y productos de Profinit en Alemania, Austria, el Benelux, el Reino Unido y otros países, donde Profinit opera en modo nearshore.La empresa desarrolla y mantiene sistemas vitales de banca por Internet y otras aplicaciones bancarias, sistemas de gestión de pólizas de seguros, portales B2B y B2C, sistemas EPM, soluciones de prevención de fraudes e incluso un sistema de software de misión crítica para un aeropuerto internacional.Para más información visite los siguientes sitios web:- https://profinit.eu- https://bigdataforbanking.com- https://systemsmodernization.com

Profinit

Our client, Raiffeisenbank CZ, offers an outstanding online service and is continuously pushing out new products to meet customer needs and expectations.The bank was keen to maintain its position in the industry, so we looked at how we could use state-of-the-art technology to help them.Working alongside our client, we asked the question, “How can we use this collected data fully, in a way that enables us to offer bank customers an even better service?” Our answer came via applying advanced data analytics and machine-learning methods to the problem – enabling us to make competitive loan consolidation offers to the right customers.

Competitor loans consolidation for Raiffeisenbank

Equa bank – a fast-growing Czech challenger bank and long-term Profinit partner – asked our team to create a propensity-to-buy scoring model (hereafter “propensity model”) that would help identify clients likely to apply for future consumer loan products. The project involved compiling data from the 2-year transactional history of 400,000 Equa clients as well as analysing the socio-demographic and product information available for this specific group.

Propensity-to-buy scoring for loans offers

Our long term client Raiffeisenbank CZ was looking for the complex delivery of a big data Hadoop platform to enable the bank to perform analytical business use cases across large amounts of transactional data. Computations of such massive volume are not possible to achieve by standard DWH capacity. For this reason, a brand new parallel processing big data platform had to be built from scratch. Tools for solving business cases with data science – and their implementation into the client’s environment – were needed as a part of the solution.Profinit came up with analytical use cases and began designing and implementing a complete, end-to-end analytical solution. Together with bank data in-house specialists, the Profinit team selected the suitable hardware, sizing and the right variant of Hadoop distribution. The Profinit DATA_FRAME Automation tool was used for the fast design of the architecture and implementation.

Big data platform for Raiffeisenbank

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