AI, Real-Time Analytics Among Banks’ Top Tech Investment Focuses In 2022

5G, artificial intelligence (AI), microservices and real-time analytics are amongst banks’ top investment focuses this year, priority areas which suggest that incumbents are currently concentrating on improving customer experience, delivering a true digital banking journey and reaching greater business agility, a study by global market research company Forrester found.

The Top Emerging Technologies in Banking in 2022 report, released earlier this year, draws on a survey of and interviews with more than 30 banking business and technology decision-makers and solution partners to understand their current interests and planned investments for the year to come.

Results from the study revealed close to 30 different technologies emphasized by business leaders. These technologies were categorized in three different groups: the “hot” technologies, which are high priorities for incumbents and which will see resources being allocated to them in the next 12 months; the “on the radar” technologies, which recorded legitimate near-term interest but with no immediate commitment; and the “hype” technologies, or trends that have generated a lot of buzz but which lack real interest or budgets committed for the coming year.

The study identified six “hot” technologies banks are currently heavily focus on. In particular, machine learning (ML) and real-time/predictive analytics stand out from the pack for the “high” investment levels incumbents are committed to them.

Respondents praised ML for its potential to help improve process automation across use cases including loan origination and fraud detection, and help deliver a more personalized customer experience.

Real-time/predictive analytics, meanwhile, are sought after for their potential to allow banks to make better-informed decisions, serve customers in a more seamless and personalized way.

Computer vision (CV) and natural language processing (NLP)/natural language understanding (NLU) are two other key technologies banks are actively implementing. CV, which enables systems to derive information from digital images and videos, has compelling applications in areas including identity verification and authentication. And NLP and NLU, which focus on processing text in a literal sense and understanding a text’s meaning, allow banks to leverage insights from structured and unstructured data, streamline business processes, and improve experiences.

5G, another “hot” technology, is expected to become a general-purpose technology for financial services firms moving forward as it enables “superfast mobile broadband, massive machine-type communications, and reliable and low-latency communications,” the report says.

Finally, microservices architectures are perceived by incumbents as a key architectural building block that promises increased agility and which allows them to future proof their organization.

Besides these six “hot” technologies, ten technologies were identified as being on banks’ “radar.” These are not center stage of the implementation roadmap this year but have sparked banking executives’ interest for their potential to improve banking operations, customer experience and the flexibility of a bank’s applications, the report says.

Three of the ten technologies are related to AI: deep learning (DL)/neural networks, natural language generation (NLG), and AI-powered robotic process automation (RPA).

DL and neural networks allow for the development of tools that are able to predict outcomes, classify unstructured data, and identify patterns. Interesting use cases include fraud detection, customer churn analysis, and purchase propensity modeling.

NLG is a software process that produce written or spoken narratives from a data set. It can be used to create regulatory reports and summarize long reports and huge data sets for executives.

And RPA, which refers to the use of advanced business process automation tools to complete mundane and repetitive tasks, allows employees to focus on more value-adding and customer-centric activities and reduce manual oversight.

Other technologies “on the radar” include distributed ledger technology (DLT)/blockchain, which promises efficiency gains; data mesh, which allows for data to be more widely accessible; event-driven architecture, which allows banks to build nicely designed, highly coherent and highly decoupled banking applications; and low-code/no-code development platforms, which offer higher business flexibility and quicker delivery of applications.

Finally, in the “hype” technology category, ten technologies were identified, namely advanced gamification, confidential computing, edge computing, green technologies, the Internet-of-Things (IoT), the metaverse, quantum computing, sophisticated chatbots, spatial computing and virtual reality.

Advanced gamification involves the use of technology and the application of game elements to engage and motivate users better. It promises increased revenue and customer loyalty but remains an unchartered territory for most banks.

Confidential computing, which focuses on increasing security by creating secure and isolated environments, is used by just a few banks.

Edge computing, which aims to process data closer to the source, promises to increase network performance but despite the opportunities, multiple barriers such as time required to move data and the cost of data edge are still hampering the widespread adoption of the technology.

Green technologies, which aim to minimize short- and long-term environmental impact of technology products, are an emerging trend but still lack common standards on what can qualified as “green.”

And the metaverse, which refers to an immersive virtual environment that replicates the physical world, promises a rich mixed-reality experience. Some banks have started exploring what it may mean for them, but realistically, it will take the industry several decades before a truly immersive, virtual environment comes to fruition.