I was at the House of Lords on Wednesday for an nCino event organised by Business Reporter, exploring how commercial banking can become a revenue engine. Around the table, professionals from different banks shared insights on customer relationships, retention and the daily work of identifying opportunities for growth. It was an interesting setting for a conversation about what banks need to do next.
What caught my attention was how often the discussion returned to data. Relationship managers needed it to understand customers. Retention teams depended on it to recognise changes in behaviour. Across those different responsibilities, the commercial ambition rested on something quite practical: having information that could support a useful decision at the right moment.
Listening, I kept returning to a question. How can we use technology to improve both the quality of that information and the judgement it supports? Banks hold considerable knowledge about their customers, but possessing information does not mean that the person preparing for a meeting can find it, understand it or confidently act upon it.
Consider the relationship manager preparing to meet a business owner. One system holds account activity, another contains lending information, while previous conversations sit in emails or meeting notes. Before discussing the customer’s plans, somebody must assemble the picture. Where records conflict, time goes into establishing what is correct. That is a commercial cost, even when nobody gives it a separate line in the budget.
There is an understandable appetite for technology that brings this information together. Better integration, analytics and artificial intelligence can help colleagues identify patterns, retrieve relevant details and recognise opportunities earlier. Technology can also improve the data itself by detecting duplicates, highlighting omissions and directing errors to somebody who can resolve them. These are useful capabilities when they address problems people actually encounter.
However, a convincing screen can conceal an unconvincing record. If a customer’s circumstances have changed but the underlying information has not, a recommendation may be inappropriate despite appearing precise. A bank can find itself approaching the right customer with the wrong proposition, then wondering why the relationship feels less personal. The investment has improved the presentation without resolving the misunderstanding.
This is why I believe data quality should be discussed alongside revenue. Accuracy, completeness and timeliness influence which opportunities colleagues pursue and which conversations they avoid. They also shape the customer’s experience of being understood. Repeatedly asking for information already supplied, or offering a service that bears little relation to present needs, gives customers reasons to question how well their bank knows them.
Data governance gives that commercial ambition a working structure. Someone must own the information, agree what makes it suitable for a particular purpose and ensure that corrections reach the systems where decisions are made. Privacy contributes by clarifying appropriate access and use. Together, these disciplines help colleagues work with confidence and give customers a relationship they can recognise and trust.
The starting point should be a decision that matters to the business. Perhaps the bank wants to recognise a financing need earlier or understand why valuable customers leave. Identify the information required, examine its condition and establish responsibility for improving it. Then select technology that helps people use it well. Measure the result through preparation time, fewer corrections, relevant conversations and sustainable commercial outcomes.
I left Westminster thinking about the distance between knowing something about a customer and doing something useful with that knowledge. Closing that distance requires investment in systems, people and the information connecting them. For those of us working in privacy and data governance, there is a clear contribution to make: helping the business establish what it can trust, what it can use and where judgement remains necessary. Revenue generation becomes more credible when the bank can explain the evidence behind its next move. That responsibility belongs within the commercial strategy, with leaders accountable for making it work in practice. The customer should feel the difference too.
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Michael Irene, CIPM, CIPP(E) certification, is a data and information governance practitioner based in London, United Kingdom. He is also a Fellow of Higher Education Academy, UK, and can be reached via moshoke@yahoo.com; twitter: @moshoke
