Three Ways Data Engineering Can Empower Financial Institutions

Posted on 23rd August 2023

Streamlining operations, garnering valuable insights and securing your business: data engineering has a major role to play in the fintech industry.

In today’s rapidly changing business landscape, meeting the highest security standards, processing large amounts of confidential data and ensuring service availability is more crucial than ever. According to Krzysztof Michalik, Head of Delivery – FinTech Stream at STX Next, data engineering can play a key role in supporting the modern business with meeting these requirements, especially fintechs, banks and financial institutions that are handling growing volumes of sensitive, unstructured data.

Michalik said: “As data engineering tools and technologies have become more accessible, organisations are increasingly relying on the insights they can produce for decision-making as well as leaning on their capability to enhance a business’s agility, dynamism and profitability. For fintech companies, data engineering provides the tools and infrastructure necessary for managing and analysing the enormous amounts of unstructured data generated in the industry.”

Below, Krzysztof Michalik discusses the crucial role that data engineering can play in supporting fintech businesses in their ongoing growth:

1. Processing vast amounts of data

Michalik: “Financial institutions and banks looking to stay ahead in the industry and gain a competitive edge rely on innovative, high-end solutions that process and analyse financial data.

“Many fintech businesses act on this by accessing data platforms or services that can automate tedious processes, doing so quickly and cutting out the potential for human error. This can be applied to tasks like approvals or services like credit risk indicators, and can assist in identifying fraud patterns in real time to optimise lending operations.

“By processing large amounts of data efficiently, a business can identify trends, make predictions and optimise operations to deliver better financial services to its customers. Consolidating data in real time to provide actionable insights for better decision-making can support the provision of high-end services.”

2. Automating security

Michalik: “As the fintech market evolves, so does the need for enhanced security and data protection. More so than ever, financial institutions are processing sensitive customer data that is at risk of theft from bad actors. Data loss of this kind can lead to huge fines and reputational damage.

“Businesses are increasingly looking to technology to keep pace with a growing list of regulations and protect sensitive customer data from new threats. Implementing better security measures and protecting sensitive customer data through cloud-based data storage solutions with built-in security and compliance features can help to meet these regulatory requirements while simultaneously improving data accessibility and reducing storage costs.”

3. Data unification for valuable insights

Michalik: “Data unification tools can provide a business with digestible and comprehensive insights through collection and analysis of data from multiple different sources. This data is then presented via easy-to-understand dashboards that can help business leaders to identify new opportunities for growth and make better-informed decisions.

“Companies can also use data unification to ensure accurate claims processing and fraud detection by visualising claim trends, fraud patterns, and other key metrics in real time.

“Unification of data from various sources can also support decision-makers by providing a comprehensive view of investment opportunities. For example, this can help organisations streamline the process of identifying and recommending different lending products, which reduces risk exposure while increasing efficiency.”