Fintech’s success relies on technological progress and innovation and will continue to bring about new, disruptive business models in financial services. According to McKinsey analysis, three key technologies will lead fintech development and shape the finance landscape over the next ten years:
Banks will begin to rely more on AI to keep up with technology companies gradually encroaching on their territory. For example, automatic factor discovery will become increasingly common in the financial world, allowing for better financial modeling overall. In addition, knowledge graphs and graph computing, which rely on artificial intelligence semantic representation to create associations and identify patterns among complex financial networks, will play an even more significant role in the coming years. By using a variety of data sources, they can revolutionize finance.
Analytics that consider enhanced privacy will help ensure minimal data usage or use only the relevant, necessary information that has been properly sanitized. This includes federated learning, a type of decentralized machine learning that prevents the risk to privacy associated with centralizing datasets. With federated learning, the computational power goes to the data rather than vice versa. Data analysis tools that protect consumer privacy, like advanced encryption and secure multi-party computing, will create a new landscape of customer protection.
AI has the potential to change every financial industry operation, from customer service robots to automated transactions and Robo-advisors. For example, AI could give users a tailored product experience, market tracking, analytics services, and facial recognition authentication. Although many financial intuitions use AI scattershot, often only utilizing the technology for specific verticals or cases, Middle-and-back office applications include intelligent processes, enhanced knowledge representation tools, and natural language processing for fraud detection. Bank industry leaders are reforming their operations by methodically deploying AI throughout their digital dealings. It is essential to understand that algorithms’ efficacy depends on data. The focus is shifting to gaining a competitive edge from customer behavior data collected through regular operations but was utilized less before. Ecosystem-based financing can revolutionize how banks, insurers, and other financial service firms do business. This type of financing allows for partnerships with non-financial players to provide seamless customer experiences in areas outside the traditional economic realm.
For banks, the “AI-first” institution will yield greater operational efficiency via the automation of manual tasks (a “zero-ops” mindset) and the replacement or augmentation of human decisions by advanced diagnostics. The improved operating performance will flow from the broad application of traditional and cutting-edge AI technologies, such as machine learning and facial recognition, too (near) real-time analysis of customer data sets. In addition, banks will operate like “digital native” companies in the future by being nimble and quickly releasing new features. Banks will also partner with other non-bank organizations to offer new services that are cohesive and work well together.
- Cloud computing
Financial institutions should be aware of three significant forms of cloud services: public, hybrid, and private. Public means that the Infrastructure is owned by providers who sell computing services to various organizations or individuals. Hybrid Infrastructure consists of two types of clouds that are maintained differently but connected through unique technology. A private cloud means the Infrastructure is built for a single customer’s exclusive use, either in their own data centers or another hosting facility. Here are some relevant trends in cloud computing that we have identified:
- Edge computing
- Cloud containers
- AI-cloud integration
Cloud computing benefits financial companies, such as freeing up non-core businesses, like IT infrastructure and data centers. With the cloud, these companies can access flexible storage and computing services at a lower cost. Additionally, the cloud is causing new formats – like open banking and banking-as-a-service – to form, changing how customers interact with financial service providers.
To remain afloat, financial institutions will need to rely on the cloud as they take on new businesses requiring a high level of responsiveness. Also, using big data analytics will become more popular, increasing demand for elastic computing, which allows people to adjust resources as needed.
After many long years of waiting, IoT is finally starting to mature and significantly impacts financial systems. These changes happen because of three essential layers – perception and intelligent sensor systems, wireless communication networks, and application and operations support. For example, RFID labeling still has lots of potentials to automate item identification and logistics management at the sensor level. However, IoT is expanding, and solutions are adapting to devices that communicate across channels, near-field communication solutions, low-power wide area networks, narrow-band IOT, connected end-point devices, and centralized control management. Additionally, embedded system technologies are developing rapidly, enabling more intelligent communication with objects.
Carbon emissions and energy efficiency are critical for many investment strategies and regulatory policies. Achieving goals like peak carbon emissions and carbon neutrality will require the broad use of renewable energy and effective monitoring and management of industrial power consumption. This creates opportunities for IoT applications. For example, carbon trading will be increasingly linked to IoT measurements, giving insightful players chances to succeed. Also, insurers are using IoT more correctly calculate risk while at the same time making insurance both more accessible and faster for customers. In the past, car insurance companies have based premiums on drivers’ indirect characteristics such as age, location, and gender. But with the advent of telematics, which uses sensors and tracking devices to collect data, insurers can get a much more direct measure of risk. Thanks to the IoT, data once unavailable to insurers is now trackable, including driver behavior and vehicle use. This allows insurers to interact with customers more frequently and offer new services based on customer data. And because customers often only contact their insurer for policy renewal or claims handling, there is potential for increased efficiency gains throughout the sector. For example, IoT can refine risk management in the banking sector by producing more accurate records that match physical transactions and establishing a new trust system. In customer relations, it allows insurers to connect with customers more frequently and specifically.
The key technologies and trends driving fintech and financial industry innovation are becoming increasingly intertwined and integrated. Niche economic sub-sectors primarily utilize technological innovations to launch applications, generate value, and shape the competitive landscape. To stay ahead of the competition, traditional financial institutions will need to use their considerable resources in the future.