MiBank Direct PLC
Coelition can help individuals to identify how their behaviours impact themselves and society.
We all create distinct patterns when we interact with large service infrastructures - financial, transport, retail and communications. These patterns are used to predict our behaviours but are not visible to us as individuals.
A hypothetical financial institution, MiBank Direct PLC, has deep understanding of how current spending behaviour maps to future financial status for their internal risk management processes. They decide to generate new data structures that show customers’ interactions without the financial details.
These are used to provide innovative consumer-centric services, developing a dialogue where customers can see how their behaviours compare to others and contribute to different financial outcomes.
Service Provider: MiBank Direct PLC
Operator: MiBank Direct (UK)
Consumer: Personal account holder
Source of Atoms: Any interaction with MiBank services – home PC, call centre & account activities
As a global business, MiBank registers a separate Operator in each of the legal jurisdictions where it has customers. When existing customers opt into the new service the local Operator (MiBank Direct (UK) in this case) will register them with the selected Data Engine. All service interactions can then be recorded directly from the different touchpoints across the business. As the Service Provider, MiBank Direct PLC, can query the Data Engine to identify patterns - alerting the local Operator when services and insight should be offered to an account holder.
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