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How a universal bank takes data management to the next level with Ailleron Customer Data Platform?
About the client:
A universal bank that has been operating in one of the CEE countries for about 20 years, serving retail, consumer finance, agricultural, small and medium-sized enterprises, and corporate banking.
Challenges
Due to dynamic growth and scale of operations, the bank identified several business challenges concerning the data architecture.
Regarding aggregated data, growing internal demand for:
real-time data for operational and analytical purpose
better access to data
new data sets for business users
taking advantage of unstructured data
Additionally, new challenges with processing non-aggregated data and real-time events arised.
Challenges were also identified on the IT Department’s side:
increase of new data sources and volume of data
increase of infrastructure cost for data
effective work with data exceeded the capabilities of existing legacy systems & IT technologies used at the time of evaluation
Next-generation Customer Data Platform to the rescue
Financial companies today face a rapidly growing volume and variety of data. Additionally, financial service decision-makers need support to meet
- the challenges of high costs
- the complexity of implementing and managing traditional databases
- the growing competitive landscape
All this requires a next-generation data platform that
- can adapt to meet the most demanding requirements
- is cloud-ready
- scales to meet growing business needs
- is able to adjusts to both transactional and analytical workloads.
The bank decided that current data access by enterprise document management (EDM) doesn’t meet the requirements of a modern digital bank. After evaluation of solutions available on the market, the bank had chosen to build a Customer Data Platform (CDP) with Ailleron.
Ailleron solution for a next-generation data platform
Ailleron Customer Data Platform (ACDP) is a set of tools and technologies that create a comprehensive solution for processing and managing data from various systems.
Our offer was accepted due to:
- flexibility concerning the supported technologies and alignment with the bank’s corporate technology stack
- detailed architecture of ACDP with a clear vision of solving bank’s business & IT challenges
- readiness for a quick start – in only 2 weeks from bank’s approval decision
- availability of experienced specialists – we employ both software development and financial business experts with +10 years of hands on experience & domain background
Main ACDP use cases:
- Providing data for Personal Finance Manager (part of client’s Digital Banking Platform)
- Providing data for 360 Customer Views
Scope of data processed by ACDP includes:
- All customers’ transactions with categories
- Customer personal data
- Products
In this case, ACDP development is based on bank’s data centric architecture principles:
CDP as the primary source of data provided across the whole organization in a specified country
Data Stream Processing as the main data flow from source systems
Data governance and organization based on Data Mesh approach
covering Data Producers, Consumers, and CDP
Main components of ACDP provided during the project
Data Streaming
Core component of ACDP responsible for:
– gathering events and data from source systems (events, CDC Connectors, etc.)
– distribution of events within the whole platform
– data transformations
Data Lakes
Storing data from various sources for analytics purposes:
– data lake with raw data
– data lake with enhanced data
Operational Data Stores (ODS)
ODS are used to store optimized data for external systems (like Internet / mobile banking, CRM, back office applications). In this case, they store domain data like:
– transactions
– products
– customers
– etc.
GraphQL
Provides read-only API and is responsible for aggregation of data from 1 or more ODSes for particular customer views
API Gateway
– Takes all API calls from clients and routes them to the appropriate microservice
– Provides security and access control
Data Hub
Component responsible for data discovery, data governance, metadata management, and data lineage; allows for
– adding tags to data
– describing data attributes
GDPR
Component responsible for data anonymization (when it is required by bank)
Implementation
The project is being carried out in
- agile methodology
- strict cooperation with the bank, including daily meetings & statuses
Crucial roles among Ailleron Team include:
- Data Platform Architects
- Data Engineers
- Data Platform Developers
- Data Analysts
Ailleron Team scaled up from 4 FTE to 12 FTE in just 3 months.
Implementation implies ACDP delivery in a step-by-step process
Project kick-off included some of the following steps:
1. Preparing backlog for next sprints
2. Implementation of ACDP core
data streaming platform, data lakes, ODS infrastructure
3. Integration of the first data source
4. Preparing the complete data flow
5. Measuring the whole data process with KPIs & reconciliations
6. Adding new data sources
7. Etc.
Key parameters (KPI) achieved by ACDP in the project
3 seconds to deliver data in Data Lake and ODS
50 milliseconds to make data available for external systems like PFM, 360 view, etc.
~10 billion records of transactions stored in ACDP
12 defined data sets shared for external systems
ACDP tech stack used in the project
- MongoDB
- Kafka Confluent
- Apache Spark
- Prometheus
- Graphana
- Delta Lake
- OpenSearch
- Zipkin
- Vault
- Fluent ID
- kStream
- Aqhq
- Oracle
- Java
- PySpark
- ksql
Mastering data management gives our client that edge to become the first choice institution for customers looking for future-ready banking. This is a great privilege to see how Customer Data Platform powers highly innovative financial services in a mature market. Seeing real-time data sharing for advanced analytics and key systems, such as mobile banking, online banking, and CRM makes the whole project team proud!
Business Unit Director AI/ML & Data Solutions
Let’s make financial experiences
easy and enjoyable together!
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