Adding efficiencies, automating processes and strengthening cybersecurity efforts: data engineering can be crucial in support scaling fintechs, says Krzysztof Michalik, Head of Delivery – FinTech Stream at STX Next.
In short, data engineering is the practice of designing and building systems for collecting, storing, and analysing data at scale. For modern fintechs, banks and financial institutions, it can play a key role in supporting their attempts to handle and make sense of growing volumes of sensitive, unstructured data. Data engineering provides the support and infrastructure necessary for fintechs to digitise their workflows and optimise business processes.
Meeting the highest security standards, processing and protecting large amounts of confidential data and ensuring service availability are all ongoing efforts. As data engineering-powered tools and technologies have become more accessible, organisations will increasingly rely on the insights they can produce for decision-making as well as lean on their capability to enhance a business’ agility, dynamism and profitability.
Data processing for valuable insights
Banks and financial institutions will frequently 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 in the process cutting out any potential for human error. This can then 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.
Through processing large amounts of data, data engineering processes can support a business in identifying trends, making predictions and optimising 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.
Detecting irregular activity and financial crime
Data engineering can also power tools that support businesses in identifying and stopping financial crime. In many cases, businesses will implement systems with the ability to analyse, detect and highlight irregular activity, saving time and money whilst improving the accuracy of the process.
Preventing and detecting financial crime is one of the biggest challenges facing financial institutions globally. In response, businesses are increasingly looking to technology to keep pace with a growing list of regulations and protect sensitive customer data from new threats. As the fintech market evolves, so does the need for enhanced security and data protection.
To add to this, financial institutions are bearing the burden of processing more sensitive customer data than ever before and handling higher transaction volumes. All the while they are facing more sophisticated threats, while the fallout from attacks and data breaches in fines and reputational damage are arguably more significant.
Data engineering can also support regulation and compliance efforts. Implementing better security measures and protecting sensitive customer data through cloud-based data storage tools with built-in security and compliance features can be the difference when it comes to avoiding hefty fines. Simultaneously, data engineering can help improve data accessibility and reduce storage costs.
Data unification
Data unification tools can also be helpful in providing a business with digestible 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 support decision-making on wider business needs and highlighting new opportunities for growth.
Data unification can also support decision-makers by providing a comprehensive view of investment opportunities. For example, it can help organisations to streamline the process of identifying and recommending different lending products, which will reduce overall risk exposure.
What’s next?
For businesses looking to steal an edge over their competitors, data engineering can play a crucial role in automating processes and efficiencies, but also in their security, compliance and anti-fraud efforts. The modern fintech should harness data engineering’s potential and reap its rewards.
