As a Data Engineer with over 5 years working in the financial sector, I’ve seen first-hand how poor data quality can affect not only your business but, more importantly, customer outcomes.
We all know by now that all businesses involved in financial services (think banks, building societies, loan/credit providers and financial advisors), are sat on a mountain of customer data that has been gathered over months, years and decades.
It only takes a few seconds of scrolling on LinkedIn to come across a post that reads something like “UNLOCK THE POWER OF YOUR DATA GOLDMINE TO DRIVE BUSINESS CHANGE AND PROMOTE GROWTH!!!!11!!” [sic].
What if we changed that narrative to something along the lines of “UNLOCK BETTER CUSTOMER OUTCOMES WITH THE POWER OF YOUR DATA”?
In recent times, regulatory bodies such as the Financial Conduct Authority (FCA) have been pushing firms to nurture a corporate culture in which the fair treatment of customers is a central pillar. This attitude also needs to extend to the data that a business collects, holds and uses in its day-to-day activities.
With businesses having many different products and customers being onboarded through various channels, it’s very easy for data quality to get out of hand.
Eventually, this problem can become big enough that it starts to affect customer outcomes.
One common example is poor data quality impacting communication with customers. Sometimes this can go far enough that problems that start small, such as a missed payment, can often spiral out of control which leaves both the customer and the business potentially out of pocket.
Poor data quality could relate to incorrect data such as misspelt customer details; duplication of data, such as two (or more) records for the same customer or missing data, like an email address or a telephone number.
So, how do we tackle it?
There are some ways to tackle poor data quality but keep in mind, this is not a one size fits all approach and may differ depending on the scale and nature of the business.
Data strategy
What’s the point? Why are we collecting this data? How do we make sure it’s of sufficient quality to use and analyse? How can we be confident that we’re making the correct decisions from the data?
These are all questions that can be answered by a comprehensive data strategy.
Seriously, investing in a good data strategy now will set a business up for success in the future. It’s worth noting, a data strategy isn’t just about data and technical teams, it’s about everyone. From customer services and branch staff to legal and audit, everyone needs to be aware of the business’ data strategy and how it affects them.
Data governance
This one’s important. Businesses need to be thinking about what data they have and should know where it is, always. Data isn’t just your customer database, it’s everything, like those notes that a financial advisor jotted down whilst on a call; the details of a complaint from a disgruntled customer or credit application information, and everything in between.
All this data needs to be governed and looked after in a secure and confidential manner without losing value. Take for instance the notes made by the financial advisor, make sure those are typed up into the CRM before that paper is sent to the shredder. Recording details of those conversations is a great way to “Know Your Customer (KYC)”.
Depending on the scale of your organisation, this could be a full-time job so don’t underestimate the scale or importance of this task.
There are tools out there that can make this task more manageable such as Microsoft Purview or Collibra (other data governance tools are available).
Accountability
EVERYONE in the organisation is responsible for data quality. It’s not just down to automated systems and checks to ensure quality data (although this is important), first and foremost it’s down to the person entering the data to ensure it’s of sufficient quality to be used. Skipping fields on a form or typing “zzzzz” in front of a defunct customer record doesn’t cut it these days.
Training
If everyone is accountable for poor quality data, ensure they know how to avoid it. Provide examples of poor data quality and train employees on ways to overcome poor data, how to update it or who to report it to if they cannot.
Ensure that the importance of having good quality data is not lost on them as knowing WHY you’re doing something is just as important as knowing HOW to do it.
To conclude then, it’s very important to make sure that the data your organisation is collecting, processing, holding and using is accurate. This attitude needs to be instilled into every employee of the organisation from the very top, right to the bottom of the organisational chart, from day dot.
Everyone’s accountable, no excuses; something that seems as simple as being a bit lazy and not typing up notes from a phone call could be the difference between a customer having a great outcome and a customer befalling a terrible outcome and your organisation losing their business.
Not sure where to start?
Are you facing these problems? Aware of them but not sure where to start?
Find out how Hippo can help improve the quality of your data to ensure positive customer outcomes.
