Four Key Data Trends in Financial Services

Increasing transparency and automation

Technology has revolutionized the financial services industry. Neobanks and fintechs have transformed the expectations of customers through intuitive response and personalized engagement while demonstrating to the wider industry what is possible when you apply automated, cloud-native intelligence to data. Traditional financial service providers are striving to respond through their own digital transformations, yet data generation, storage, analysis and transfer present significant challenges.

In one of the most regulated industries, data security, transparency, accuracy and authenticity must be uncompromised. Not only to avoid hefty fines, or exposure to fraud; but also to ensure the most accurate insights are derived, to drive innovation and maximize organizational success. The result is the development of four key data trends in financial services, as organizations strive to stay ahead of the curve: data transparency, elimination of data silos, real-time financial data and automation of manual tasks.   

1. Data transparency in financial services

Data transparency is about two things: the ability to access and work with data no matter where it is located or what application it is created from. Secondly, it's an assurance that data is accurate and from an official source.  In financial services, the latter is controlled and regulated by various bodies like the FCA (Financial Conduct Authority) to protect customers and maintain stability in the industry. It’s also demanded by external and internal stakeholders including the executive board, departmental management and business analysts who require access to business critical data that must be readily available and high quality. Without it, they risk losing information and making uninformed decisions. 

Being able to access and work with accurate data wherever it is located or created presents a further challenge in financial services. There is an enormous amount of numerical data to be analyzed, often stored on various excel sheets or databases, and the extraction and unification of this data is highly technical and time intensive. As a result, we’re seeing a trend in financial services moving towards complete data transparency: so they can work with their data no matter where it is located or what application it comes from, with complete assurance that the data maintains accuracy to its original official source. Of course, this can be highly challenging to achieve.

2. Focus on user experience and eliminating data silos

Today, customers are at the heart of organizations, around which data insights, operations, technology, and systems revolve. Financial services are investing in new technologies, such as AI, to understand client needs and to anticipate future behaviors and further personalize the engagement experience. Chatbots are a great example of this. These digital assistants communicate with customers via text messages or voice commands to create automated, personalized experiences. 

However, the outcome of this is an increased mass of data from these new data sources for organizations to manage, and ultimately data silos that need to be eliminated. Organizations in the financial services increasingly understand the importance of eliminating data silos, but to bring this data into one unified source is often time-consuming, expensive and complicated. 

3. More real-time financial data available

Real-time data empowers prompt activity, permitting organizations to be proactive by taking advantage of opportunities or forestalling issues before they occur. With real-time data, organizations are able to visualize data that reflects changes within the business as they happen, improving accuracy and  driving better decision-making. Rather than spending resources, time and money gathering unimportant data, software can be positioned to deliver just the information you want, when you want it. 

The act of using data algorithms to track down enormous amounts of data, is empowering organizations to pursue exact forecasts and human-like decisions when evaluating data and executing trades rapidly. 

4. Automated Financial Reporting 

The ever-increasing mass of data in financial services has led to a huge increase in manual administration, in order to gain real value from the data. Data management solutions allow organizations in the financial services industry to fully automate financial reporting. 

Automated financial reporting will give you the data you need, where you need it and when you want it. Full automation of reporting gives you data you can trust, instantly updated without any manual labor required. 

One solution for managing data in financial services 

The Kleene vision is to make business insights a commodity, not a privilege. We combine all data sources in one place, translate them into one language and organize everything to make it easier for your teams to work with. We do the heavy lifting for you with end-to-end data automation, at a fraction of the cost of doing this with in-house engineers.  

Kleene’s data management platform provides data transparency in every sense: translating and cleaning your data so you can access it wherever it is located or where it came from.  While assuring the integrity of the original data. It delivers insights quicker so you can focus on improving user experience. It eliminates data silos so your organization has one unified, complete truth. It delivers your financial data in real time: so you get the information you need, now. And our intelligent automation is the key to making all this happen without any additional time resource to you. 

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