Data Foundation
No good model was ever built on bad data
Challenge
The quality of data always affects the quality of analytics, irrespective of the amount of data available. However, turning raw material into semi-finished product ready as input for further analytics, does not only involve technical challenges (requiring IT skills). It involves bridging the gap between the IT and the Modelling-context.
What do we do
We interact between the analytics unit and IT. We do this by establishing a common language between the various stakeholders. In addition we identify and unlock relevant data sources into a dedicated platform. Subsequently we preprocess data to create an appropriate data-analytics platform. This involves: linking data and data cleansing (to enhance its quality). Such is easier said than done. Execution is very demanding and time consuming, and our consultants have the required skills and endurance to get the job done.
Business areas
Our data related services are highly relevant for any business area in which data analytics are applied. In case of more complex questions to answer with data analytics, data challenges will only increase making our services of even more value added. In terms of business areas we focus on financial modelling, financial crime analytics and data analytics (a broader context, also outside the financial sector).
Our experience
We have vast experience in data preparation within large banks aiming at advanced financial risk modelling. Specific challenges that we have dealt with are: unclear data-field definitions, combining different source systems, historical changes in processes (e.g. in work out of loans).
