Financial services are an important part of the economy and play a wider role in providing liquidity and capital around the world. But ongoing political uncertainty and the consequences from the COVID-19 crisis have deep implications for that UK's financial services sector.
In a post-Brexit world, the industry is facing regulatory uncertainty in a entirely unique scale, with banking executives having to understand the implications of various scenarios, including no-deal. To reduce the risk of significant disruption, financial services firms require the right technology infrastructure to be agile and responsive to potential changes.
The role of open source
Historically, banks have been hesitant to adopt open source. But over the course of recent years, that thinking has started to change. Organisations like the Open Bank Project and Fintech Open Source Foundation have happen with the aim of pioneering open source adoption by highlighting the benefits of collaboration inside the sector. Recent acquisitions of free companies by large and established corporate technology vendors signal the technologies are maturing into mainstream enterprise play. Banking leaders are adopting open innovation strategies to lower costs and reduce time-to-market for products and services.
Banks must prepare to rapidly implement changes to IT systems in order to comply with new regulations, which can be a costly task if firms are solely counting on traditional commercial applications. Changes to proprietary software and application platforms at short notice usually have hidden costs for existing contractual arrangements due to complex licensing. Open source technology and platforms could play a crucial role in helping financial institutions manage the effects of Brexit and also the COVID-19 crisis for their IT and digital functions.
Open source software gives customers the ability to spin up instances far more quickly and respond to rapidly changing scenarios effectively. Container technologies have brought about a step-change in virtualisation technology, providing almost equivalent amounts of resource isolation as a traditional hypervisor. This in turn offers considerable opportunities to improve agility, efficiency, speed, and manageability within IT environments. In a survey conducted by 451 Research, almost another of monetary services firms see containers and container management like a priority they intend to begin using over the following year.
Containerisation also enables rapid deployment and updating of applications. Kubernetes, or K8s for short, is an open-source container-orchestration system for deploying, monitoring and managing apps and services across clouds. It was originally designed by Google and it is now maintained through the Cloud Native Computing Foundation . Kubernetes is a shining example of free, developed by a major tech company, however maintained through the community for those, including banking institutions, to adopt.
The data dilemma
The use cases for data and analytics in financial services are endless and offer tangible solutions to the consequences of uncertainty. Massive data assets imply that banking institutions can better gauge the chance of offering a loan to a customer. Banks already are using data analytics to enhance efficiency and increase productivity, on and on forward, will be able to use their data to train machine learning algorithms that may automate a lot of their processes.
For data analytics initiatives, banks now have the option of leveraging the very best of free technologies. Databases today can deliver insights and handle any new sources of data. With models flexible enough for rich modern data, a distributed architecture designed for cloud scale, along with a robust ecosystem of tools, open source platforms can help banks break free from data silos and enable these to scale their innovation.
Open source databases can be deployed and integrated in the environment of preference, whether private or public cloud, on-premise or containers, based on business requirements. These database platforms can be cost effective; projects can begin as prototypes and develop quickly into production deployments. As a result of political uncertainty, financial firms will need to be much more agile. And with no vendor lock-in, they will be in a position to pick the provider that's perfect for them at any point over time, enabling this agility while avoiding expensive licensing.
As with any application running at scale, production databases and analytics applications require constant monitoring and maintenance. Engaging enterprise support for free production databases minimises risk for business and can optimise internal efficiency.
Additionally, AI solutions have the possibility to change how banks deal with regulatory compliance issues, financial fraud and cybercrime. However, banks want to get better at using customer data for greater personalisation, enabling them to offer products and services tailored to individual consumers instantly. As yet, most banking institutions are unsure whether a post-Brexit world will focus on gaining more overseas or UK-based customers. Having a data-driven approach, banks can see where the opportunities lie and how best to harness them. The opportunities are vast and, on the journey to provide cognitive banking, banking institutions only have just scratched the surface of data analytics. But because the consequences of COVID-19 continue and Brexit uncertainty once again moves up the agenda, moving to data-first will end up less of a choice and much more of a necessity.
The quantity of data sets and also the diversity of information is growing across financial services, making data integration tasks more and more complex. The cloud offers a huge chance to synchronise the enterprise, wearing down operational and knowledge silos across risk, finance, regulatory, customer support and more. Once massive data sets are combined in one location, the organisation can apply advanced analytics for integrated insights.
Uncertainty on the highway ahead
Open source technology today is definitely an agile and responsive option to traditional technology systems that provides financial institutions with the ability to cope with uncertainty and adapt to a variety of potential outcomes.