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Driving faster, smarter, more consistent and more efficient decision-making
Technology Category
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
Use Cases
- Predictive Maintenance
- Fraud Detection
Services
- System Integration
- Training
The Challenge
As First National Bank (FNB) expanded its business activities within South Africa and in neighboring countries, it found that its decision-support systems were not running optimally in the face of increasing demands from internal users, customers, and regulators. The inflexibility of existing systems was making it slow and costly to adapt rules to meet new requirements, hindering business agility. The existing solution could not support different sets of rules for each country, so FNB was forced to construct multiple instances of the rules engine. This implied the costly replication of rules and associated redevelopment and testing work, and also meant that changes made by head office took too long to propagate out to the subsidiary countries. With up to 40 changes to shared central rules each month, each of which had to be separately tested and deployed across ten countries, the existing approach at FNB was clearly inefficient in development terms.
About The Customer
Established in 1838, First National Bank (FNB) is the oldest bank in South Africa and one of the region’s largest financial institutions. FNB provides banking and insurance products to personal, commercial, corporate and public-sector customers. Like other banks, FNB relies on shared business rules and assessment tools to ensure that it strikes the optimal balance between risk and opportunity in all operations. As it expanded its business activities both within South Africa and in neighboring countries, FNB found that its decision-support systems were not running optimally in the face of increasing demands from internal users, customers and regulators.
The Solution
FNB carried out a major study of decisioning solutions from seven vendors before selecting IBM Operational Decision Manager running on IBM z/OS. During the proof-of-concept phase, IBM Operational Decision Manager proved itself to be the only solution that could handle the volumes of data FNB needed to process. IBM helped FNB fast-track the deployment of Operational Decision Manager to support the fixed go-live date for the internal credit-risk bureau. FNB initially processed decisions in Java running on a standard mainframe processor. By choosing to output the rules files in a binary format and moving the workload to a specialty zIIP processor, FNB both improved the performance and reduced its MIPS consumption. The first new application FNB has built using Operational Decision Manager is Aggregations, which scores customers for credit risk based on an analysis of 24 months of transactional history.
Operational Impact
Quantitative Benefit
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