About the Client
The client is one of the largest European banks with over 145 million customers worldwide. The bank offers a range of products and services for retail banking, mortgages, cards, payments, commercial, business SME, corporate, wholesale, investment, and wealth management.
The bank identified financial crime amongst the top 5 risks that can have a significant impact on the bank’s reputation. Moreover, a recent trend observed was that criminals have increasingly started using financial systems to launder the profits of illegal activity such as human trafficking and terrorism. Furthermore, the UK regulatory changes post-Brexit may add further complexity to Financial Crime Risk Management. Considering these factors, the bank started FCTP with the objective to achieve sustainable compliance to financial crime policies through the improvement of financial crime controls, processes, and systems including anti-bribery and corruption measures, customer risk assessment, screening, and transaction monitoring.
As part of the Financial Crime Transformation Program, the bank wanted to build various workflows namely for customer screening and different levels of due diligence that involved risk profile assessment of a customer and determining the level of due diligence required. The bank also wanted to modernize the flagging process for reporting suspicious activity that currently used ERASE that required a lot of in-house support.
Coforge, with its team of experts, set up a strong cross-functional team comprising data consultants, API developers, BPM experts, and QA practitioners backed by the techno-domain advisory practice.
The solution comprised building a new data ecosystem based on Hadoop, NuoDB, MongoDB, and Vault to decouple data from applications and future proof the system.
Data access was enabled through experience APIs, messaging queues and files, and custom middleware whileNetReveal was used for the alert detection engine for customer screening, transaction monitoring, and customer risk assessment.
Safewatch was used for payment screening and in-house interfaces were leveraged for analysts to raise Suspicious Activity Reports. Case management across financial crime was implemented on the Appian Low Code BPM platform. Analytics and ML tools were built on top of the system. MIS reporting and comprehensive dashboards we developed using MicroStrategyService Layer facilitated by an API-led architecture that was designed and built asynchronously. This helped in mitigating latency and improved performance. The End-to-end BDD testing process was automated.
Agile methodologies were used for separating functional and technical tasks, optimum sprint planning for API dependency, document creation and managing to understand workflows, and on-boarding new resources.
The Appian API Workflow:
- Analysis of data model required for Appian and checking availability of Core/System APIs.
- Design of Experience API (Ex-API) using IBM API connect and shared contract JSON with Appian.
- Publication of EX-API specification on IBM API Market.
- Development of microservice using Spring Boot and pushed code to GitLab.
- Uses CI/CD Jenkins under the hood of RedHat OpenShift PaaS, which runs pipeline from SCM.
- Pushed docker image to Harbor Registry after a successful build and all E2E has passed. A similar image is deployed in OpenShift PaaS for Dev/Pre and Prod environments.
- Configuration YAML files are also deployed using Jenkins pipelines to OpenShift PaaS and services are linked together.
Delivering More Value
The value delivered by Coforge exceeded beyond the scope of the contact:
- 20% reduction in cost and continued optimization
- 40% improvement in provisioning agility
- 30% increase in productivity of analysts in case management
- 45% improvement in release velocity due to simplification of the architecture