Bahaa Abdul Hussein is a Fintech expert and shares his experiences with his audience through his blogs.
The economy and competition in the financial industry have created a global context that is nudging banks to create a new data frame that is in tune with new needs. Financial institutions must refurbish their reporting mechanisms, while balancing cost, quality and production.
Every business owner has opportunities to create data that is valuable. This data can be used by optimizing your operations and defining strategies that will take your business to new heights.
What Must be Done by Businesses?
To achieve operational excellence without a burden on the production team, ease of data handling is paramount. It could become cost banks dearly when they use old techniques to handle data.
Since risk management is an extensive, complex process, we’ll talk about the multitude of problems during this journey and look at how new technology can make it easier.
Going Step-by-Step
● Stock-take and Productivity
The first challenging step in data manipulation is in extraction of data bundles from data pools or legacy systems. Large data volumes may be collected, and storing it in absence of a proper strategy to manage data can be costly.
● Transformation
After acquisition of data, aggregation of data is required. It’s important to note that here we need to rectify or purify all the faulty datasets. At the same time, we need to enrich the granularity of the data. Other adjustments which are not automated are a daily concern for reporting teams and consume most of their production time.
● Calculate
This stage of data analysis usually relies heavily on analysis and testing. It involves calculating key metrics. These calculations can interfere with the process of production, leaving users with metrics that might not be sufficient for investigation of data.
● Certify and Analyse
After performing multiple analyses and investigating them, the next step is to verify the accuracy of the metrics that are calculated. Using Artificial Intelligence for this step will significantly increase efficiency and reduce the time required in getting this step of the process done.
● Display and Sharing
And finally, we exhibit all the dashboards to different stakeholders. The teams that produce this content need to be supported by an automated data visualization layer. However, this automation must be flexible for the analyst to focus on other tasks with more value. Easily displaying information through a single dashboard is essential for information-sharing and support.
Final Words:
Financial institutions are showing a increased awareness of the need for modern data solutions. It’s clear that evolution is happening. And those who adopt it early will be more successful as compared to those who wait. Thank you for your interest in Bahaa Abdul Hussein blogs. For more stories, please stay tuned to www.bahaaabdulhussein.com
