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Financial Services

Legacy systems often result in data being held in silos. Unlocking the value is hard when the costs are so high. The advantages of data pooling for credit and insight purposes can be dramatically undermined when these valued datasets are hacked. Equifax highlighted this.

The overt customer consent required by GDPR threatens to stifle industry data sharing. And as individual targeting becomes less accessible, tightly defined segmentations will become key. InfoSum's aggregated data modelling meets this need.

View Financial Use Cases »

Decentralised collaboration offers a safer way to work together

Retain ownership

All data remains within the ownership and control of the owner at all times.


Link securely connects data silos and automatically standardised data formats.

Immediately available

Simple, fast and easy to use solution that build insightful customer profiles.

GDPR compliant

No further consent required for profiling activity. Data can be immediately withdrawn.

Individual analysis and aggregated results

Whilst output is aggregated and anonymised the actual analysis compares individual records.

PCI compliance

Participating companies do not need to be PCI compliant as no personal payment data is processed.

Financial services use cases

Extend customer knowledge

  • Overlay payment data with lifestyle/ mobile/ location data to build a richer profile of customers.
  • Build up knowledge of the behaviour choices of your best customer and the life events that drive purchases.
  • Overcome payment information segregation. Bring together combined knowledge of shopper’s payment habits e.g. credit, debit, cash or online payment service.

Identify commercial opportunities

  • Select best rewards for new accounts and loyalty base through understanding the appeal and overlap of brands.
  • Advise on the ‘next best product’ for individuals on the basis of their propensity to buy. Use second and third party data to help understand this information.
  • Create strategic alliances with companies who target similar customers e.g. mobile phone insurance.

Evaluate media and data sets

  • Establish attributes of your best customers so you can target digital ads at appropriate groups. Increasingly important as advertising consent becomes tighter.
  • Check the relevance of data lists or addressable media by understanding the overlap with your existing base.
  • Find lookalike customers by comparing datasets and finding non customers who show similar characteristics.

Measure campaign effectiveness

  • Bring together digital media and payment data to measure views vs purchases - helpful in validating campaign conversion.
  • Analyse purchasers of products with that brands existing dataset to see what level of spend is incremental.
  • Compare campaign responders with addressable datasets to establish impact of that media.

Industry data exchange

Open up new opportunities for data collaboration at an aggregate level without the risk of sharing data. Benchmark industry size, customer overlap and uptake of products and services e.g. pensions.

Understand employee behaviour by benchmarking recruitment and churn data with others in the industry. Profile new recruits and understand the demographics of high churn groups.