Maintaining customer relationships
The bank’s senior leadership knew that one of the most crucial elements of success was effectively servicing customers and building long-term customer relationships and they also recognized technology would further enhance those customer relationships. Specifically, they were looking to improve how data was used to help their relationship managers (RMs) become more responsive to customers. Current technology isolated much of the data, hampering efforts to effectively assign relationship managers (RMs) to optimize service, balance resource workloads and maximize revenue. The bank needed to group customer household and organizational relationships, identify high-value relationships and effectively assign RMs to develop and grow those accounts. This required an innovative data-grouping solution to handle account complexities without negatively impacting customers.
The bank’s leaders had a vision of how client data should be presented to RMs and how that data should be orchestrated to create actionable insights. However, the bank did not have a scalable technology solution to build that vision and would need to take a deep dive into the resources available and the related data sets.
Protiviti teamed up with the bank staff for a comprehensive look at the data environment. Client data was stored in a two-dimensional space, with most data constrained to rows and columns. That made it difficult to build data associations and prevented RMs from garnering insights to better serve their clients.
That challenging data environment presented roadblocks to achieving the bank’s vision, since the data needed to be recategorized while business processes, resource management and data governance policies had to be adapted to support the desired capabilities. The bank’s leadership team was also laser focused on maintaining compliance and meeting regulatory needs and worked with Protiviti to ensure that compliance and other banking regulations were fully met.
The project team used Microsoft Azure to build a graph data structure and associated algorithms to organize and analyze nested banking customer relationships.
The team recognized that change management, resource management and operations were foundational to drive the project forward. They also needed to conceptualize how each group of relationships would be assigned to RMs and whether clients would have multiple RMs or other resources interacting with them. The goal of implementing a data driven solution involved using existing technology in a new way and using recent technologies as needed.
The solution framework identified optimal resource assignments, which drove the need for change management to support adoption of new business processes while maintaining outstanding relationships between RMs and clients.
To ensure both consensus and integrity of group relationships, the team:
- Established consistent logic rules for account linkages
- Defined new policies and processes to assign relationship managers
- Constantly refined the criteria based on new insights gleaned from the advanced analytics
Adopting this approach removed variable decision-making and transformed decision making into data driven processes, based on outcomes from the data algorithm results.