Problem
- Customer struggled with detecting anomalous financial transactions – the current process is labour intense and error prone due to mass volume of the transactions and amount of false positive alerts
Customer
Customer
Customer
Identifying clients that are most likely to have financial problems through an automatic model based on warning indicators to alert credit officers earlier
Customer
Identifying clients that are most likely to have financial problems through an automatic model based on warning indicators to alert credit officers earlier
Customer
Creating a single client view for an international Swiss bank allowing them to track and compute total risk exposure, and meet AML compliance regulations
Customer
Creating a new data pipeline for collateral risk calculations to improve the quality of data information and reporting for end users
Customer
Refactoring an entire codebase making the pipeline run time 7x faster, allowing quicker new feature development, and increasing data quality for analysis
Customer
Aggregating all marketing data into a single view matching leads to customers to gain a better understanding of marketing campaigns performance and costs
Customer
Assessing current custom-made data platform to make recommendations on the best approach and create valuable insights for future platform strategy
Customer
Building up a Neo4j Graph solution to help different divisions map relationships and interactions between people, companies, accounts and assets
Customer
Developing an ML model to identify potential rogue traders and flag them to minimise risk of financial losses and lower need for regulatory cash reserves
Customer
Designing and integrating Tableau to enable secure access to datasets stored on the main Foundry instance
Customer
Optimising platform performance with a set of tools and best-practices combined with coaching, resulting in lower costs and smoother user experience
Customer
Creating a dashboard unifying all trading information resulting in a more holistic understanding for credit risk officers and substantial risk reduction
Customer
Defining and implementing a surveillance framework to identify illegal client behaviour resulting in greatly improved ability to meet surveillance requirements
Customer
Customer
Customer
Developing a centralised solvency and risk assessment model to create risk exposure reports automatically and improve data quality
Customer
Customer
Creating a single client view for an international Swiss bank allowing them to track and compute total risk exposure, and meet compliance regulations