Can you bank on your customer data? An MDM guide for Financial Services

It’s frustrating when you receive an email with your name spelled wrong, or a supposedly ‘personal’ offer that’s completely irrelevant to you. It’s especially frustrating when it’s from an organization that you already have a relationship with, like your bank, insurer or any Financial Services provider: you’ve entrusted them with your data, why aren’t they getting it right? 

For those of you in the Financial Services sector, it’s time to step back and think: is this the experience you’re giving to your own customers? 

To answer that question with confidence, you need to know whether you can truly bank on your data to tell you the complete truth about your customers, and it isn’t always an easy question to answer. Data Quality can be complex, particularly if data is collected, stored and used across multiple departments in your organization – which it so often is in finance. 

Here, we look at the complications that surround customer data in the Financial Services sector, and how customer MDM can simplify them. 

One customer, multiple data profiles

In financial organizations, one person can be a customer across many different service lines or engage with a whole range of departments. A mortgage customer could also have home insurance and a current account. They could have an active complaint going through customer care, while elsewhere they are waiting for approval on a loan. 

It’s a wealth of information that could paint a detailed picture of the customer – who they are, what they have, what they need, their behaviour, their relationship with the organization – but too often gets lost between the gaps instead. The result is a fragmented experience for the customer and lost opportunities for your business – not to mention the risks that missing or duplicated information presents from both a regulatory and commercial perspective. 

Let’s draw on an example from our guide on customer MDM: 

  • Your financial organization has a current account customer, Mr Sam Brooks. 
  • Your insurance department has a Ms Sam Brooks, with the same address. 
  • Marketing has a Ms Sam Brooks, too, who shares an email address with Current Account Sam. 
  • Then there’s Sam Brookes who is going through collections on a loan repayment. 

Are these the same customer? If so, which one is telling the truth? Are you sending Mr Sam Brooks annoying misgendered marketing communications, or could you be collating two Sam Brooks together who are completely unrelated? 

The important question to ask here is, how could you know? Can you really bank on the customer data you have, if there are so many different versions in silos across the business? 

It could be that each version is, at this moment, showing the same information – but data isn’t static, it’s fluid. What happens when Insurance Sam reports a change of address, but that information doesn’t filter through to collections? You’re instantly at a disadvantage and unable to see the entire view of that customer.

How can I know if my customer data is reliable?

There are several ways to find out whether your data is reliable – some better than others. 

  • Firstly, a mistake happens that demonstrates that your data isn’t up to standard. It could be a customer complaint, a compliance issue, or a failure of communication between two corporate divisions, but we can all agree it’s never the best way to ascertain your data’s reliability. 
  • Secondly, you can undertake a Data Quality exercise, which will show you how accurate your data is, and help you to improve it in that specific moment. What it won’t do is help you to rely on your data moving forward. 
  • Thirdly, you can take steps to get a single view of every customer, across the entire organization, by implementing customer Master Data Management (MDM). 

For financial organizations like yours, this single view is becoming increasingly important as your offering becomes more complex, your customer touchpoints become more digitized, and you find yourself competing with fast, flexible, data driven newcomers to the market. 

What should a single view of the customer look like? 

A single view of the customer essentially presents one data profile on an individual, including all of that person’s data from across the organization. Rather than having a data profile that covers their mortgage offer, and another housed elsewhere that covers their insurance details, all information is provided in a single view and accessed by everyone: who they are, what products/services they have, their financial history, their communications with the company, the marketing they receive. 

Of course, just having this single view won’t guarantee that your data is telling you the truth about your customers. To get your hands not only on one view, but a single version of the truth – or ‘Golden Record’ as it’s known – you need: 

  • the platform to host it (e.g., customer MDM)
  • Data Quality to define what that ‘single customer view’ should look like
  • Data Governance to make sure that everyone who handles customer data is maintaining that Data Quality over time. 

Once you have a single version of the truth on every customer, you can explore your Customer DNA in detail and introduce more robust data driven customer due diligence, with high-quality data enabling faster decision-making and even automation

Do you need customer Master Data Management? Here are five questions to ask yourself. 

If you can answer yes to each of the following questions, chances are your customer data is reliable and ready to use. 

If you can’t answer with confidence – or it’s an outright no – it’s time to explore customer MDM and ascertain a single version of the truth on your customers. 

  1. You have one data record of every customer, that’s accessed by every department. 
  2. No department, team or individual is keeping their own customer data records separate (if they do exist, these ‘silos’ could include a rogue spreadsheet or a CRM)
  3. You have a robust and well-communicated Data Governance process in place to maintain Data Quality 
  4. You’ve carried out a Data Quality initiative recently to make sure all data aligns with your data definitions and objectives
  5. You have a customer MDM platform that houses all customer data across the organization.

With customer MDM, you could have confidence in reliable customer data, improve your customer experience, increase efficiency (for instance, with automated customer due diligence) and ultimately monetize customer data without damaging customer trust. 

If you want to be able to bank on your customer data, download our guide to customer MDM and discover your next steps to getting that golden record: Know your Customer: An Agile Solutions Guide to Customer Master Data Management.