The banking industry is one of the most important in modern society. Given the way finance and trading evolve, it is understandable that banking needs to grow and develop with it. However, as the world handles more and more information, banking data quality issues can grow more problematic.
What can we do to ensure that data quality in banking is of an optimum standard? What challenges are banks and financial institutions facing regularly?
There is an urgent need to identify these key issues so that services like WinPure can help cleanse and clarify these numbers for years to come.
Why is Data Quality Important in Banking?
Immediately, data quality is essential in banking due to its sensitivity. People rely on banks to take special care of their money. Their lives, as well as work, literally depend on these safeguards. Therefore, it stands to reason banks should handle data that is simple to understand and always secure.
However, this is not always the case. And Moody’s Analytics advises that significant problems such as the 2008 financial crisis may be avoidable through more accurate risk analysis. Moody’s further suggests that effective risk assessment in banking revolves around three principles. These are data, analytics, and infrastructure.
Therefore, data must be of optimum quality for confident assessment. Money is an asset that is perhaps more at risk than any other.
UK government risk assessors state estimates point to $1.6 trillion worth of money laundering in 2009 alone. Worryingly, with technology advancing in the decade since this problem may be exacerbating.
Protecting money is complex and challenging, even for multinational corporations and banks. Therefore, the need for clear, concise, and consistent data quality is crucial. Not only to benefit everyday livelihoods but also global economies.
Instead of understating data quality in banking, we need to keep vigilant for quality problems in global finance. Therefore, it is a key mission of WinPure to help improve risk assessments and security standards for banking bodies worldwide.
Related Reading: The Shocking Cost Of Dirty Data In Banking
3 Data Quality Issues Banks Face
It may be simple to assume that all banks handle data to impeccable quality standards. While all banks should ensure their data is clean and easy to understand, it is not always a simple process. Data quality challenges in financial industry brands may be simple to spot, but does the ‘cure’ follow suit?
Here are the three most common data issues in banking and how WinPure can help manage and overcome them.
Risk Assessment Challenges
As explored above through the Moody’s model, data is a huge proponent in the risk assessment system. If banks do not have faith in the information they use and analyze, they cannot be confident in approaching unknown risks. Banks without confidence are, of course, hardly likely to inspire confidence in account holders.
Failure to assess risk properly in the banking industry could lead to severe reputational damage. It could lead to a financial loss on a large scale. These factors could also lead to national economic failures, as well as an outcry from banking customers.
Data in banking must be clean and concise to offer confident solutions. WinPure, for example, can help banking professionals by linking multiple records together. A common issue some banks may face is that the disparate data they need to make risk assessments is difficult to piece together.
WinPure’s cleansing model brings together multiple data banks and sources. This enables users to work from a single platform and a single screen to build safer, more confident assessments.
Related: Top 5 Data Hygiene Tips
Changes in Expectations and Demand
Financial expectations are always changing. Global shifts and crises in 2020, for example, indicate that more and more people adopted digital banking. A trend that many analysts believe will continue. However, without the best quality data available, how can banks be sure they are ready to meet these changes?
Our overview of the banking industry demonstrates that only 8% of industry bodies are up to date with their data hardware. This data emerges from 2019, meaning the pivotal year of 2020 may change some statistics. In any case, it is still a worrying sign that some banks are not taking efficient steps to take care of their data.
Data quality in banking, therefore, needs a scalable, fluid, and responsive administrative model. As mentioned, WinPure’s record linking and merge purge features can help to drain data lakes of duplicate information. Not only that, but data matching and cleansing strategies can help to set a new precedent.
Banks can use WinPure to continue growing their databases with confidence. Big data in banking will continue to grow. Therefore, instead of letting it compound, WinPure can refine and carefully store such numbers with greater clarity.
Privacy and Security
Banks are under immense pressure to assure users their money is safe. This is no longer as simple as a friendly, local manager giving a customer their word. Billions of people place their trust in global banking, whether online, via phone, or in person.
Therefore, banks must ensure data security is not only in place but that it is provable. Duplication of data and records can lead to inaccuracies and potential breaches. It is another effect of the data lake which may not always be evident on the surface. The worrying statistic that only 8% of banks are up to date on software and hardware does not bode well in this instance.
WinPure can assist banks their users in refining and re-establishing records. Data cleaning revolves around making it easier to understand and digest. While security measures must be the responsibility of banks themselves, software in WinPure can help simplify the information involved.
Conclusion
Banking is a critical service billions of people rely on. We can safely assume big data in this industry is likely to be ever-growing and unfathomable to process without software support. Data quality and consistency in banking are also under constant public scrutiny.
However, data quality issues in banking are not impossible to overcome. With the support of WinPure, banking services and systems can help measure risk, assure client confidence, and drain data lakes. With worldwide banking evolving evermore, data quality in banking is a legitimate and pressing concern.
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