A multidisciplinary approach to Data Management
Today, everyone relies on data. We use it to find our way on navigational maps, judge online products before purchase, and much more. Data is important, but even more vital is the quality of the data; You cannot find your way using unreliable map data or judge a product correctly based on fraudulent reviews. Most businesses today also rely heavily on data to reveal various inefficiencies, potential, and missed opportunities. For this, managing your data is essential - and here at Lunar, we recognize that good Data Management relies on people’s access to and understanding of data as much as the technologies we use to process it. We had a chat with Tine Marcher, Lunar’s Head of Data Quality to outline our unique approach.
Why is Data Management so important?
Data Management
Data Management is the practice of structuring, documenting, monitoring, and acting on poor/inconsistent Data Quality, in order to ensure that data can be the foundation of compliant, cost-effective, and efficient processes. In many aspects, a FinTech cannot operate without proper Data Management. It plays a crucial role in our ability to work efficiently and innovate the business, as well as for our ‘license to operate’.
The goal is to help people and the organization optimize the use of data within the bounds of policy and regulation. Moreover, it is about constantly maintaining and improving upon Data Quality, within a clearly defined threshold.
“Data Management allows us to standardize Lunar’s data disciplines and ways of working across the organization”
Managing data is essential for being able to scale a business and reduce inefficiencies. Good Data Management is likewise essential for proper reporting and avoiding regulatory issues.
Data Quality
Data has high quality when it is fit for purpose in decision making, development, operations, strategy, and planning. At Lunar, Data Quality is evaluated on five dimensions:
Created by Tine Marcher for internal documentation.
Quality data limits resources spent on improving, reprocessing, and fixing inaccurate data. Low-quality data likewise hide problems in operations and make regulatory compliance a challenge, says Marcher. Being regulated under the Danish FSA means a certain level of quality and transparency is required to even continue to operate.
At Lunar, however, we aim much higher than meeting the bare minimum for regulation and see Data Quality as key to our success. Being a mostly legacy-free organization, born of the digital age, gives us an advantage in this aspect - but it also amplifies the importance of the decisions we make today regarding Data Management if we want to avoid future troubles. Now is the time to get it right.
High-quality data is likewise vital for trust. If our employees do not trust the data made available, they will start working with their own data. This creates Data Silos - non-accessible isolated data, which creates a vicious cycle further decreasing Data Quality and trust.
“Without trust, Data Quality becomes poor or unknown, and our data foundation becomes worse”
Data Accessibility
Making data easily accessible is part of ensuring quality. In a larger organization, particularly one under heavy regulation, such as ours, there will always be a need for keeping certain data under lock and key. But within these constraints, we believe as much data should be accessible to our employees as possible.
Our employees (data users) are able to easily access managed data in a transparent way. This ensures that users do not work with their own data on local storage, unavailable to others. Data Silos introduces the risk of:
Storing data that should have been deleted.
Using data outside of purposes of legal basis.
Duplication of effort and reinventing the wheel, because more users have to understand, define, clean, and model the data.
Inconsistent data because of differing definitions or application approaches.
Lack of accountability to data - or unambiguous accountability: it becomes more different and costly to define data, reduce inconsistencies, and correctly protect it.
Ultimately, without access to the data we need, users will work with their own data, which creates Data Silos, which results in poor Data Quality, which then decreases trust in the data.
Without trust in the data, users tend to silo their own data - and the cycle continues…
This model exemplifies the importance of managed access to data.
Results of poor Data Quality & Management
Poor Data Quality will result in incorrect or inaccurate reporting, which can subsequently result in a financial loss for the organization or non-compliance with regulators. According to Marcher, without a foundation for good Data Quality, efficient integrations, innovations, and predicting outcomes become much harder.
“With good Data Management & Data Quality, we are much more likely to succeed”
Lunar’s approach to Data Management
Ubiquitous language and deep integration
Domain-Driven principles of the ubiquitous language play a key role in Data Management At Lunar. A ubiquitous language supports good Data Quality through precise communications. Data Management also introduces common ‘ways of working’ with our data, which in contrast to traditional Domain-Driven Design, slightly reduces autonomy in our Squads. But what we gain allows us to work in a way that results in less ‘reinventing of the wheel’ and easier employee onboarding. Data Management, however, is not traditionally approached in an agile way. This is because of the difficulty of refactoring data architectural deliveries and the complexity of legal requirements that need to be analyzed and documented initially to avoid risks of being non-compliant in an agile implementation cycle. Our approach is technology-driven: Through the implementation of data tools, we are allowed to highlight specific data issues quickly in order to find solutions and build our Data Management framework in parallel.
Part of our approach also lies in the ambition of going beyond what is required for compliance and regulatory reporting, as alluded to previously. Traditionally, In the banking industry Data Management oftentimes becomes a paper tiger and is never truly an integral part of doing business. Our growth mindset in combination with our fortunate position of being free from decades of legacy and paperwork, allows us to constantly optimize where needed. We acknowledge specific issues of our business when they appear and act on them accordingly; Starting over if we have to.
Regulation may be a driver for Data Management but going beyond being compliant results in increased efficiency and the ability to leverage data to innovate and improve products.
“At Lunar there exists a willingness to change; to completely refactor in order to improve our data, if need be”
Data Deletion
Proper Data Management also involves the ability to delete data that we no longer have a purpose for keeping. In order to stay compliant with GDPR, there are vast requirements in the context of deleting personal data, which makes it an important task in order to operate a bank successfully. While important, deletion is also an example of a vast, error-prone challenge. Deletion requires a clear definition of personal, identifiable data as well as set rules for deletion. In a close collaboration between Compliance, Legal, and Tech at Lunar, we ensure that we have consistent and compliant deletion rules, so that we can identify personally identifiable data and so that we - to a large extent - can automate the deletion process. Automating these processes decreases the risk of human error and increases the possibility of being compliant in a way that also gives us full control over the deletion process, full audibility, and the possibility to adjust rules when regulations change.
Moving towards Hyperautomation
It is still early days for Data Management as an independent discipline here at Lunar, but because Lunar is born in the digital age and is without a paper trail legacy, we can move rapidly towards automation of Data Management activities. We want to take advantage of new data technologies to auto-classify and auto-tag our data. This saves time and helps ensure consistency. When creating and processing data, people see more nuances but are at the same time a bottleneck for both time and consistency. There is a balance between quality, trust, and being in touch with the data that is important to uphold. Therefore we work with a combination of automation by technology and supporting colleagues through data stewardship. Data stewards facilitate, bring awareness and train our employees, enabling better handling of data in our daily work. The technology enables our data stewards to have an overview of quality, prioritize the right effort and reduce the amount of manual work for our employees.
The Complete Dataset
When it comes down to it, good Data Management is just as much about making people aware of the data and the impact of handling correctly as it is about using the right technologies. Working in unison and speaking the same language is important to ensure consistency, correctness, timeliness, and completeness of our data. Granting managed access to data also plays a big part in keeping data high quality and fit for purpose. Making use of data supports accurate decision-making, but only works as long as trust in the data exists. Trust comes from upholding high Data Quality levels and standardizing ‘data ways of working’ and this also avoids people working in isolated Data Silos. Automating processes helps avoid certain risks and human error, which can have a negative impact on Data Quality as well as being cumbersome and feel irrelevant to our employees. Data is integral to the way we want to run our business - and as a fintech operation, we are more than just a bank: Built on a foundation of data and a culture with the right mindset helps us take advantage of powerful new tools and acknowledge our mistakes. Fixing these mistakes in a swift manner and balancing our Domain-Driven principles of autonomy with Data Management, allow for our future success.
About Lunar
Lunar is a FinTech company founded in Aarhus, Denmark 2015 motivated by rethinking the banking experience. Unlike many other FinTechs Lunar operates as its own bank, with a license provided by the Danish Financial Supervisory Authority in August 2019. Lunar is a 100% digital bank, with a mission of giving you back control over your money by making managing your finances understandable, accessible, and easy for anyone. We now serve more than 500.000 customers across Denmark, Norway, and Sweden - and not just private banking customers, but businesses as well!
For more information visit our main website here.
Want to work for Lunar?
Lunar is full of talented people working on incredible things all the time. With more than 550 people across the Nordics - Aarhus, Copenhagen, Stockholm, and Oslo we are constantly evolving. This site is about just that: The technologies we utilize and create, our ways of working, our learnings, and company culture. If you are interested in joining us, check out our careers page!
