The Retail Banking sector is working through a profound transformation of its economic models since the arrival of new, Full-Digital players. It faces the transformation of the payment industry and the threat from the GAFATIM - Google, Apple, eBay…

The introduction of Digital brings :

  • An overhaul of the bank's front, middle and back-office processes in a bid for enhanced performance
  • An optimization of the banking customer relationship through a new customer segmentation strategy, new formats for bank branches, and the development of digital spheres in an omnichannel rationale
  • The appearance of new customer services through improved support in consumption spheres (spending one's cash reserves) and the monetization of banking data

Banking and financial regulations, and in particular the increased cost of risk, have a profound impact on operators' technical margins. They require a thorough optimization of plans for organizations, technologies and models.

Thanks to its business knowledge and technological expertise, the Keyrus Group, through its consulting and Business Intelligence entities, successfully assists its banking clients with all dimensions of their transformation projects :

  • Transformation of processes, optimization of operational efficiency, new digital and relational strategies
  • Putting in place of new segmentations and geomarketing rationales, and implementation of a digital front-office for the banking relationship

REFERENCES

  • Bank of America Merill Lynch

    Forecast time-dependent information (such as notional volumes, revenues, spreads and exchange rates) sliced by appropriate dimensions (such as channel, broker code, client name, etc.) by utilizing historical data. Batch forecasting of an unlimited number of time series - Automatic choice of best-fitting ARIMA or ETS model based on AIC back testing - Customizable forecast horizon and data aggregation (Day, Week, Quarter, Month, Year) - Determination of forecast accuracy (MAE, MAPE) and prediction intervals - STL trend+season+cycle+noise decomposition (noise-to-information ratio) - Signal analysis by means of frequency decomposition (Fourier).

  • BNP Paribas Fortis

    Improve the customer experience by exposing (real-time) personalised content based on a visitor’s behaviour, and by targeting prospects and non-identified and identified customers to eventually increase sales conversion. Transforming semi-structured data to structured data and linking various data sources acquired an extensive preparation work.

  • BNP Paribas Fortis

    Third-party application maintenance of BNP Paribas Fortis’ MBStore application covering an onsite ETL /BI service centre with Informatica, including both functional and technical enhancements, 2nd and 3rd level application support and defect resolution. The MB Store department is responsible for CRM and Financial Reporting for sales and servicing departments under the responsibility of Commercial Banking and Corporate banking.

  • International banking group

    Categorization of transactions in order to help identify key clients, identify moments of life in the customer lifecycle, … Explore the different data sources and find ways to combine them in order to accurately perform the categorization task, improving on the previously existing model. Key element in future data-driven projects: identification of key clients, identification of moments of life in the customer life cycle, additional input in machine learning algorithms.

  • KBC

    Keyrus supports the KBC Bank Business Intelligence Competence Center team in the development and the management of its BI platforms, including definition of architectures aligned with KBC group policies, sharing knowledge about the BI products catalog and how it can respond to business requirements, and integrating and developing the BI-tools.