Data Management Strategy

Data Management Challenges for financial firms and solutions to overcome it

Data is a critical resource for firms who are concerned about customer operations and relationships. After all, it provides valuable information about companies’ interactions with their customers. Specifically, financial services companies have a huge amount of customer data that can lead to increased sales as well as provide insight to operational improvements. Despite potential new revenue and cost reduction opportunities, many financial firms still struggle to gain insight from their data.

Solutions to overcome data management challenges for financial firms:

Data Integration

The exponential rise in data volume over recent years has left financial services firms with a challenge to aggregate, manage and derive value from it.  As more data accumulates, it’s quite common for any firm to become unaware of what data it has, where the data is, and how to use it.

Data integration can help financial services companies manage customer interactions and obtain a “single customer view,” leading to cross-selling and upselling marketing opportunities, as well as new product development insight.  It can also ease complexity and increase the accuracy of satisfying regulatory requirements, adding regularity and repeatability to compliance data programs.

Enterprise data solutions, whether cloud-based data lakes, marts, or warehouse, can centralize and auto-aggregate data across enterprise and social applications, external partners, and the IoT, assuring data privacy and security in their design.  Further, 24×7 monitoring and operations, complete with archival and destruction procedure can manage data to the appropriate scale and relevancy.

With integrated data, financial services firms can 

  • Reduce their manual effort to aggregate and resolve data discrepancies and human errors, decrease the time it takes to prepare data for analysis from months to weeks or days.
  • Build a shorter path to valuable revenue insights.
  • Mitigate risk from outside intrusions and breeches.

Further, with the use of modern data integration technologies, financial companies can onboard their customers and streamline digital payments and transactions without expensive manual processes

Data Analytics

With the use of data analytics, the financial industry can effectively manage credit risks and minimize their exposure to such risks.  AI-powered analytics and consumer personas provide deep insights about customers’ behaviors, enabling banks and financial services companies to continuously evaluate customers’ performance and reduce their risk exposure on a continual basis as credit risk profiles change. 

Aside from credit risks, another leading risk for financial services companies is fraud detection. AI, Big Data, Machine Learning enable financial firms to analyze transactions based on behavioral analytics, predictive analytics and machine learning models, helping financial firms detect frauds effectively and proactively. 

Chartering an analytics program demands the early definition of business goals, revealing which insights are needed and in which priority order, at which point the implementation of analytics and visualization platforms and tools, and data science solutions can actualize the vision.

Nallas helps financial firms convert data into strategic assets.  We facilitate significant cost savings for your organization by eliminating expensive manual processes. By enabling informed and accurate data insights, our services will lead you to overall better decision-making (less rework) and “Flight Control” for key strategic initiatives.

At Nallas, we care about what you care about and at the end of the day, what is most important – the business outcomes you are driving towards. This is your metric of success – and so it is ours.  

Check more about our Data Engineering services here