How to improve your business with efficient financial data management
N-iX
2022-06-15T19:55:17+00:00

Effective data management is critical for organizing data streams that come from different sources. Large quantities of data are difficult to manage, and inconsistencies pertaining to data management in financial services may cause business intelligence bottlenecks. As the business generates more an...

How to improve your business with efficient financial data management

Effective data management is critical for organizing data streams that come from different sources. Large quantities of data are difficult to manage, and inconsistencies pertaining to data management in financial services may cause business intelligence bottlenecks. As the business generates more and more data, finance teams gain new opportunities to generate valuable insights, but it is not that simple.

To manage the data, businesses need a simple, secure, and practical way to collect, process, and utilize the information. Let’s see how most of the current challenges of financial data management can be resolved with the right set of instruments that allow for process automation, data visualization, and analytics. 

What is Financial data management?

Financial data management is a set of processes and measures that help the enterprise in managing, analyzing, and optimizing financial information while staying in line with all the rules and regulations pertaining to accounting. Effective data management is possible with the use of the right data analytics software and algorithms for reporting and data visualization.

Data management is directly related to such areas of expertise as data analytics, cloud-based enterprise resource planning (ERP), Big Data, Data Science, and more. The company dealing with large quantities of financial data must have confidence in its digital tools and processes that track and organize it. Financial data management, driven by a set of data processing, analytics, visualization, and automation tools, vastly improves the quality of reports. The decision-makers can, thus, make the whole enterprise more agile and efficient. 

data management flow

How inefficient financial data management hinders your business

More data sources mean more problems for the CFO, but it is often impossible to reduce the number of data sources and streams in a growing business. In most cases, a CFO would be cooperating with numerous departments within the company. All of them would be bringing new data streams to the table.

Of course, the obvious solution here is to delegate data governance to a team of designated experts. They would analyze all the data streams, bring you the spreadsheets, compile statistics, and give presentations. This, however, is a monotonous and painstaking job, and even though you might hire the best financial data analysts, the inherent flaws of such an approach would remain:

  • Human error renders the accuracy of the reports questionable.
  • Monotonous and time-consuming tasks impede the teams’ potential for analysis and innovation.
  • The data sent by one of the departments might not be complete without input from another department. In some cases, different departments might present conflicting data.
  • It would be impossible to get real-time financial information if it depends on human performance.
  • Any change in the financial data from a single department would require a change in the entire data entity, which leads to significant overheads.
  • By the time the team generates the data, it might already be weeks or months old.

Naturally, none of those is good for the business, and collectively, these problems can cause inefficiencies and data governance bottlenecks. Making decisions based on outdated, incomplete, or inaccurate information is not acceptable as it might have a negative impact on the business, its employees, and stakeholders negatively. Such errors and poor decisions may snowball into real disasters over time. 

How you can benefit from financial data management

So, what kind of measures should you employ and what financial data management solutions can help you achieve maximum efficiency and real-time reporting? Combining all the data sources into a single infrastructure is a good place to start. Using a single consolidated reporting infrastructure, rather than pulling the information from disjointed data streams allows you to: 

  • Improve the trustworthiness and relevance of the data, allowing for real-time decision-making and extraordinary agility.
  • Combine the data sent by different departments by creating a single standard for data governance.
  • Free your teams to handle other important tasks and have more time for generating valuable business insights.
  • Access all the available data from a single source.
  • Study all the available data sets and historical changes in real-time.

Centralized control over data requires a centralized data repository such as a data lake, data warehouse, and databases. Storing data in a secure repository is critical for data management in financial services, and thus, you will need a robust and secure data architecture to make it work right. 

Improve your business intelligence and make the right decisions

By embracing financial data management solutions and aggregating multiple data sources into one stream, you will improve your business intelligence maturity. This will give you the opportunity to react to the changes in your data both before and after it occurs. 

Making the right decisions in response to certain changes in the data is good but making preemptive decisions beforehand is even better. As you go up on the business intelligence maturity curve, you can make prescriptive decisions to better define your strategic plans and improve the accuracy of predictions. 

 correlation between analytics and business intelligence

Here at N-iX, we apply data mining and statistical models to help businesses across industries to identify patterns in their data streams, predict outcomes, prevent failures, and make the right decisions. Methods like machine learning also allow you to extract valuable insights from unstructured data streams such as videos, texts, photos, documents, and more. 

We can also build business intelligence solutions that optimize the performance of your teams and develop data warehousing solutions using a vast tech stack. This will help you get more vivid reports and a comprehensive view of your business operations. 

Make things easier for your people with data automation

Data automation is one of the biggest data management trends in financial services that allows you to lift some weight off your employees and increase their efficiency. Instead of handling the data manually, they will learn new skills and expand their roles enriching your enterprise with an innovative and forward-looking perspective. Basically, by automating data flows, you can redirect the efforts of your employees towards other important tasks, helping them expand their expertise and promoting the efficiency of your business operations.

It is possible to automate most of the repetitive tasks – from invoices to bank statements and expenses. With the right set of technologies, processes that used to take hours to finish would now take mere minutes. It will also reduce the number of human errors and cut the time spent on correcting them. 

Real-time visibility and synchronization

You can better examine the opportunities you have, when all the processes are properly organized and all the resources are allocated to the right places. Using enterprise resource planning (ERP) for financial data management, you can access in-depth information to see what’s best for your organization at that exact moment and in the future. 

Having a full picture of your enterprise's resources and needs allows you to better plan your resources and make better decisions. ERP software can also help you synchronize the data and improve its quality across different departments. When generating large quantities of data, you need to consolidate and synchronize it on a company-wide scale. This process becomes simple and easy thanks to the ERP software.

How a reliable partner can help you turn financial data into value

Transitioning to more efficient data governance techniques is not that simple. It requires a vast pool of expertise including data analytics, business intelligence, data science and more. Naturally, an experienced and reliable software development partner can provide you with a dedicated development team of experts who can set up data management solutions for you. N-iX offers the right selection of services that will help you resolve a number of challenges:

Visualize your data

Visualization is one of the data management trends in financial services that allows you to gain clear actionable insights. The N-iX team can help your finance team visualize the data in a form of user-friendly reports. We can also provide your team with the training they would need to make the most out of the insights and feel confident when acting upon them. We can also set up notifications for users so that they stay aware of all the important changes in the data.

Migrate to the cloud

Cloud migration is among the most widespread data management trends in financial services, and we can help you migrate large quantities of data from on-premise storage to the cloud (Google Cloud, Azure, AWS). This allows for more scalability and reduces the cost of storing the data. N-iX will help you design your cloud infrastructure and migrate to the cloud safely. 

Build and integrate the Big Data Analytics ecosystem

You can build scalable Big Data ecosystems and integrate them into your existing IT infrastructure easily with the help of a reliable software development partner. We leverage the capabilities of Cloudera, Hadoop, Apache Spark, and other tools to create effective systems to extract, transform and load (ETL) large quantities of data. 

Create data lakes

Data lakes are helpful for storing unstructured or semi-structured data in large volumes. This is especially useful for data that comes from different sources and at high speeds. Thanks to such tools as Amazon S3 and Hadoop, you can store data cheaply and efficiently. 

Extract insights effectively

Data analytics can help in not just extracting and analyzing data but also in identifying patterns and making predictions. You can apply online analytical processing (OLAP), data mining, machine learning, and other techniques for making predictions and informed business decisions. 

Of course, each set of financial data management solutions needs to be tailored to the specific needs of a business. You will need to formulate KPIs and estimate realistic goals, and we will help you choose the best solutions that match your goals and needs. 

Final thoughts

Financial data management is essential for effective work with vast amounts of data coming from different sources at high rates of speed. Such problems as human error, data entry delays, lack of real-time updates, etc. can stall the growth of your business and result in major setbacks. That is why it is essential to apply the latest data analytics tools to improve the efficiency of data management in financial services. 

Data visualization, automation, migration to cloud storage, ERP solutions, and other techniques can improve your data governance practices and improve the overall efficiency of your business. A reliable software development partner can help overcome the current challenges and develop efficient financial data management solutions for you.


 

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By Vladyslav Kitsela, Oleksandr Shynkovych June 15, 2022

About N-iX

N-iX is an Eastern European software development service company that helps businesses across the globe expand their engineering capabilities and develop successful software products. Founded in 2002, N-iX has formed strategic partnerships with a variety of global industry leaders and Fortune 500 companies, including OpenText, Fluke Corporation, AVL, Lebara, Currencycloud, TuneIn, and many others. With more than 1,800 professionals, N-iX offers expert solutions in software engineering, cloud-native services, data analytics, embedded software, IoT, machine learning, and other tech domains covering a wide variety of sectors, including finance, manufacturing, telecom, supply chain, to name a few.

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