know your customer Consent

Permission Controls for Open Banking Differentiation

Challenge

Banks must avoid disintermediation from new Payment Initiation Service Providers (PISPs) and drive customer loyalty in the new open banking ecosystem

Considerations

1. How much do customers want to be known? Customers don’t want to feel that banks are intruding upon their lives or becoming overly familiar with data insight.
2. How do we bring customers on the journey? Banks want to retain and grow customer relationships over the financial services lifecycle, so they need to establish themselves as trusted advisors.
3. How can we consume data from internal sources, as well as expose bank data? This must be controlled and secure to protect the customer, protect the bank and create services that leverage the complete customer view.

Solution

1. Understand the cultural dynamics of the regions where you do business, as well as segmenting your customer base. Begin with an opt-in beta trial that allows customers to self-segment. Ensure new permissions controls are well signposted within banking applications and accompanied by clear educational material about the potential benefits of leveraging open banking permissions, as well as customer advice on protecting personal data. Begin by creating a business case internally that speaks to key stakeholders:

  • Data officer: Involve a stakeholder focused on consumer data to support the flow of independent data lakes into the orchestration layer
  • Head of digital channels: Partner with digital to deploy new controls into mobile and web banking applications
  • Head of payments: Leverage the head of payments as the lynchpin between the wider group, as well as the richer data available in modern payment standards

Begin with a proof of concept based around an opt-in beta testing group. Create an opt-in method for customers to choose what kinds of data they share and for what purpose, to comply with regulation such as General Data Protection Regulation (GDPR). The applications should include notification controls, as well as the option to restrict length of time of access. For customers to fully consent, they need to understand the implications of those permissions, so customer education materials and campaigns will be critical to the success of a beta trial.

2. Map customer desires to the potential services and offerings the bank could provide. Consider why customers use banking services: to save for a house, to care for their families, to travel, etc. This enables the bank to identify specific use cases where a trusted financial partner’s advice might be best received.

For example, young customers might look to be empowered with information before making their first large financial decision. Guide them towards information sources, both the bank’s own and from independent organizations, as well as pushing offers for free face-to-face in-branch consulting.

The end goal is for the bank to be viewed as a trusted financial partner to encourage customer stickiness and drive upsell and cross-sell rates. Measure success via metrics such as the opt-in rate for data sharing, customer attrition levels and customer acquisition via evangelization from current customers.

3. Leverage APIs for both payments and non-payments data, both internally and externally to expose and consume data. An API gateway can simplify the ongoing maintenance of the API library for exposure. To generate the APIs for internal connectivity and external exposure requires a strong data orchestration and management layer. This should be more than an enterprise service bus, as in a banking scenario many messages will be payments-related. A solution built for payments will maintain the non-functional requirements (NFRs) necessary for a two-sided canonical model.

Leverage existing solutions beyond their original purpose. For example, a fraud prevention and management solution may include tools for two-way customer communication. These can be repurposed to deliver the financial services advice opted into by the customer. In fact, an advanced fraud prevention solution will leverage machine learning capabilities that could be repurposed to create models slanted towards CX.

CX optimization

Move towards proactive advice that pre-empts potential poor CX and works to counteract. For example, send an offer to move money from a savings account into a current account to avoid the customer being overdrawn and charged fees.

As the customer confidence grows and consumers opt into wider data sharing, begin to integrate data from external sources. These should improve the customer experience beyond pure financial services advice, as well as grow into other areas of the bank’s business, such as merchant acquiring.

Transport network journey data generated when customers tap in and out using their contactless card or smart device. This could include route choices and usual travel times. Based on this known customer routine, geo location data, known spending patterns and merchant location information, banks could push offers and discounts for a “pick me up” after a delayed journey that can be redeemed at an in-station merchant.

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