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Fintech

Why those in financial services must spring clean their customer databases

Republished By Plato
Republished By Plato

Date:

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With the cost of living crisis continuing and slow economic growth forecast for the remainder of the year, these are challenging times for financial institutions looking to drive growth.  

This makes it vital to ensure account holders continue to receive a standout experience, to prevent customer churn and drive profitability. Equally important is a focus on driving efficiencies to avoid wasting valuable revenue.

Why clean your database?

The answer to deliver a positive customer experience, and efficiencies, is to spring clean your data – though ideally not once a year, but on an ongoing basis.

It avoids wasting time and precious revenue on inaccurate communications, therefore driving efficiencies, while enabling the delivery of a standout, personalised service to aid revenue generation. Having accurate customer contact data also plays a role in
helping those in financial services meet stringent KYC and AML regulations, and therefore reduces the risk of fraud.    

In fact, best practice decision making is based on high quality, reliable customer data, because the insight that it helps to provide makes it possible to create informed decisions; for example, on the future of a product or service, or the creation of a
new one.

Data decay a constant issue

According to Gartner, data decays on average at three per cent a month and roughly 25 per cent a year, as people move home, divorce or pass away. With data continually degrading it’s essential to have data cleaning processes in place, not only at the onboarding
stage, but to clean held data in batch. All that’s required is simple, cost-effective changes to the data quality regime.

How to effectively clean databases:

Utilise an address lookup or autocomplete service

It’s essential to use an address lookup or autocomplete service to obtain accurate contact data at the customer onboarding stage. These tools deliver accurate address data in real-time by providing a properly formatted, correct address when the user starts
to input theirs. With the number of keystrokes required cut by up to 81 per cent when entering an address the onboarding process is speeded up, improving the whole experience, making it significantly more likely that the user will complete a purchase or application.

A service such as this is essential because about 20 per cent of addresses entered online contain errors; these include spelling mistakes, wrong house numbers, and incorrect postcodes, typically due to errors when typing contact information.

First point of contact verification can be extended to email, phone and name, so this valuable contact data can also be verified in real-time.

Deduplicate data

Data duplication is a common and significant issue with 10 – 30 per cent duplicate rates not uncommon for those organisations without data quality initiatives in place. It often occurs when two departments merge their data and errors in contact data collection
take place at different touchpoints. Data duplication adds cost in terms of time and money, particularly with printed communications and online outreach campaigns, and it can have a negative impact on the sender’s reputation. Using an advanced fuzzy matching
tool to merge and purge the most challenging records is the best solution to create a ‘single user record’ and source an optimum single customer view (SCV). The insight from which can be used to improve communications.

By deduplicating data in this way efficiency savings are also made, reducing costs, because multiple communication efforts will not be made to the same person. Additionally, the potential for fraud is reduced with a unified record established for each user.

Data cleansing and suppression

It is vital to undertake data cleansing or suppression activity to highlight people who have moved or are no longer at the address on file. As well as removing incorrect addresses, these services can include deceased flagging to stop the distribution of
mail and other communications to those who have passed away, which can cause distress to their friends and relatives. By employing suppression strategies financial institutions can save money by not distributing inaccurate messaging, protecting their reputations,
while boosting their targeting efforts to overall improve the customer experience.

Use a data cleaning platform

Delivering data quality in real-time to support wider organisational efficiencies and provide a better customer experience has never been easier. Today, cost-effective services are available, such as a scalable data cleaning software-as-a-service (SaaS)
platform that can be accessed in a matter of hours and doesn’t require coding, integration, or training. This technology can cleanse and correct names, addresses, email addresses, and telephone numbers worldwide. Records are matched, ensuring no duplication,
and data profiling is provided to help identify issues for further action. A single, intuitive interface offers the opportunity for data standardisation, validation, and enrichment, ensuring high-quality contact information across multiple databases. This
can be delivered with held data in batch and as new data is being gathered. As well as SaaS, such a platform can alternatively be deployed as a cloud-based API, via connector technology like Microsoft SQL Server, or on-premise.

In summary

In these challenging economic times having customer databases that are clean and accurate is essential. Making a concerted effort to spring clean databases, something that should be implemented on an ongoing basis, will deliver efficiency savings, help to
deliver a standout customer experience to support revenue generation, and reduce the opportunity for fraud.

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