Eight technology trends that will disrupt the banking industry

Technology is rapidly transforming the way how banks operate and how they serve their customers, and becoming a key enabler of competitive edge. According to a new report by Deloitte’s Middle East Financial Services practice, eight emerging technologies are set to disrupt the banking industry in the coming years. An outline of the technologies and some of the key benefits they have to offer to the banking industry.

Cloud computing

Cloud is an essential tool of today’s service delivery model, and enables banks to penetrate new business opportunities and access new delivery channels. By leveraging cloud-based services, banks are able to decrease data storage costs through saving on capital expenditure (CAPEX) and operating expenditure (OPEX), while ensuring customer data is protected. 

There are three types of cloud services:

• Infrastructure as a Service (IaaS) A third party hosts elements of infrastructure, such as hardware, software, servers, and storage.
• Software as a Service (SaaS) Using the cloud software such as an internet browser or application is able to become a usable tool.
• Platform as a Service (PaaS) The branch of cloud computing that allows users to develop, run, and manage applications, without having to get caught up in code, storage, infrastructure and so on. 

 

 

Some of the key benefits of cloud-based working for banks include:

• On-demand scaling and agility: Cloud-based services are agile and able to provide additional technology resources whenever required, adhering to organizational computing needs and dealing with sudden spikes in demand. This level of agility can give banks a real cost advantage over competitors who operate their own data centers.
• Security and availability: Cloud vendors provide the banking sector with restraints on data manipulation in a cloud ecosystem. These security and audit restrictions, combined with organizational authentication programs, offer the facility to audit and reduce penetrative attacks, which would otherwise require significant investments to execute in an on-premise environment.
• Shift in IT spending: Cloud provides a shift from capital expenditure to operating expenditure. Switching from asset ownership to service consumption leads to flexible pricing, (you only pay for what you use), and requires no upfront infrastructure investment, enabling organizations to pursue other investments for growth or innovation. With the purchase of infrastructure, there is always the risk of aging and obsolescence; this can be avoided by consuming resources as a cloud service.
• Stimulates innovation: Cloud services free banks to redirect IT roles away from operations and towards developing capabilities in such areas as the Internet of things (IoT), machine learning and artificial intelligence (AI). This cannot happen without at-scale computing and storage. 

Big Data analytics

Big data refers to large and complex datasets that create significant challenges for traditional data management and analysis tools in practical timeframes. Using advanced analytics, banks can apply technology to efficiently extract valuable insights from data, and use those to improve the (strategic) decision-making process. 

Benefits of Big Data analytics for the banking sector include:

• Increased customer retention: With in-depth customer profiles, it’s easier to build stronger customer relationships, by developing products, services, and other offerings tailored to their specific needs. Banks can use big data to sort through feedback and respond promptly to customer questions and concerns
• Real time stock market insights: Instead of simply analyzing stock prices, big data takes into account political and social trends that may affect the stock market. Monitoring trends in real-time allows analysts to compile and evaluate the appropriate data and make smart decisions.
• Risk management optimization: Monitoring customer spending patterns and identifying unusual behaviour is one way in which banks can leverage big data to prevent fraud. Big data, when plugged into business intelligence tools with automated analysis features, can trigger red flags on customer profiles that are higher risk than others
• Innovation Big data covers a broad spectrum of use cases and is a key enabler of many technologies of today and the future, especially in advanced analytics, AI, machine learning, and robotic process automation (RPA).

AI and cognitive technologies

Artificial Intelligence (AI) is now becoming a part of the business environment and is reinventing the entire ecosystem of the banking sector. By increasing the level of automation and using dynamic systems, AI supports decision-making, enhances the customer experience, and improves operational efficiency. AI also provides a strategic oversight for getting value out of data, which is now needed more than ever due to the data influx from a wide range of sources. 

Benefits of artificial Intelligence in the banking sector include:

• Fraud detection: Fraud detection has been the hotspot for the application of AI in banking. AI’s increased potential for real-time sensing and improved ability to spot anomalies make it highly valuable in this regard. Automated fraud detection systems use machine learning to identify behavior patterns that could indicate fraudulent payment activity
• Customer recommendation: AI can enable banks to provide quality advice to customers by removing “human error”. AI-powered personalized finance management tools hold great potential in the market.
• AI-driven virtual assistant: A virtual assistant can anticipate and answer thousands of customer questions and also help customers perform banking transactions in real-time
• Productivity gains: Almost the top 20% of back-office work accounts for 85% of the cost. Labor-intensive work like compliance reporting, new customer on-boarding communications, and documentation can become highly accurate and efficient with the adoption of AI tools and technologies 

Deloitte foresees a growing appetite for AI investment across the Middle East. In fact, in one scenario, spending could reach over US$100 million in 2021. 

The Internet of Things (IoT)

Internet of Things is a technology which connects devices/sensors in a network with the aim of providing better data-driven insights. The banking sector started utilizing IoT relatively late compared to sectors such as energy and automotive. However, IoT has been gaining importance in financial services lately, especially in retail banks, which are showing large investments in IoT to be used in their internal infrastructure and consumer-facing capabilities. 

The use of IoT devices will allow banks to collect massive stockpiles of customer data, ranging from their demographic details to their income and spending patterns, to their preferences. The access to this amount of data has the potential to drive fundamental change in the industry including increasing operational efficiency, preventing fraud, reducing nonperforming assets (NPAs), improving employee and customer efficiency, and facilitating easier verification, loan tracking, and customer retention.

Robotic Process Automation (RPA)

The banking industry is mandating the use of intelligent automation to drive efficiency, eliminate repetition, and improve customer satisfaction by providing fast and efficient services. The technology behind this automation is called robotic process automation (RPA). 

RPA is transforming how banks operate. Some key benefits of RPA in the banking industry:

• Cost reduction: The cost of robot software represents one-ninth of a full-time employee in an onshore location. Potential cost-saving opportunities such as those associated with employing and housing a person are therefore eliminated when hiring a robot.
• Accuracy: By nature, robots are programmed to follow rules, thus providing higher productivity and less error rates compared to their human counterparts. When hiring robots, quality of data goes up typically to 99.5% accuracy. In rare cases of RPA errors, slips are systematic.
• Operational efficiency: Robots are faster than humans at performing tasks, and thus standard tasks such as customer onboarding processes, account opening, and loan processing to a certain extent can be automated using RPA.
• Compliance: RPA can enhance several aspects of compliance such as monitoring and testing. RPA’s capability to pull and aggregate data from multiple sources could also enhance the efficiency of regulatory, non-financial, and risk reporting as it can help eliminate or reduce the time-consuming processes of collecting and compiling large amounts of information. 

Blockchain and Distributed Ledger Technology (DLT)

Blockchain technology and its associated distributed ledgers were devised as a simple yet smart solution to keep track of the Bitcoin cryptocurrency in circulation. The solution leveraged a ‘distributed ledger’ architecture under which all users who participated as ‘nodes’ in the network had a copy of the entire ledger.

Benefits of Blockchain technology in the banking sector include:

• Time sensitivity: Blockchain enables the near real-time settlement of recorded transactions, reducing risk and providing an enhanced customer experience.
• Authentication: Smart contracts allow business validations and automated reconciliation for straight through processing.
• Trust: Smart contracts allow codification of business rules, validations and reconciliation, thereby reducing manual processing.
• Manual processing: Blockchain maintains automated audit trail of transactions, thereby reducing manual processing for data validations and reconciliations.
• Transparency: The hash/pointers of the records written on the Blockchain are immutable and irreversible, not allowing modifications and eliminating risk of fraud.
• Intermediary: Blockchain’s distributed ledger technology facilitates disintermediation, thereby reducing costs and lowering latency.
• Golden source: Blockchain’s distributed ledger and consensus mechanism allows data consistency across multiple participants.

Quantum Computing

A quantum computer is a new type of computer that harnesses the power of quantum mechanics to solve problems that were previously believed to be intractable on regular computers. In the banking sector, the authors predict four major use cases.

• Portfolio optimization: Determining the attractiveness of a portfolio by processing thousands of assets with interconnected dependencies, thus helping in minimizing risk and maximizing gains from dynamic portfolios of instruments.
• Financial modelling: Today’s markets deal with a basketful of risky and uncertain situations that require faster and more secure processing solutions. Quantum computing will offer a big help in isolating key global risk factors and finding new ways to handle complex financial data by carrying out an incomprehensible number of calculations all at once.
• Enhanced security: Quantum computing can be used to create better encryption, resulting in stronger data security and less fraud and compliance violation.
• Machine learning optimization: Quantum computing can enhance current cognitive technologies that have seen widespread applications across industries. Because they have the ability to scan a massive amount of data in milliseconds, quantum computers can provide feedback much more efficiently compared to classic computers, which results in shortening the learning curve for AI.

There still is some way to go however before quantum computing becomes a reality. According to Deloitte, the 2020s will likely be a time of progress in quantum computing, but the 2030s are the most likely decade for a larger market to develop.

Open Banking

Open Banking refers to the movement that banks work together in an ecosystem of (technology) partners. Banks broadly have four broad strategic options: full-service provider; utility; supplier; and marketplace interface. 

These four options are not mutually exclusive. Two of these – utility and supplier – involve losing control of the customer interface as products and distribution become unbundled. However, organizations pursuing more than one option are likely to need to sharpen their own proposition for each option they pursue to remain competitive.

Open banking is poised to introduce a number of opportunities both for incumbents and new entrants:

• Service offering enhancement By opening up their APIs, banks can connect other APIs in the market in order to enlarge their service offerings by introducing FinTech solutions in a plug-and-play manner. By embracing the open banking API economy, banks are able to further improve and transform current offerings, increasing their attractiveness to existing and prospective customers alike.
• Customer engagement improvement Open banking APIs improve the attraction rate of a bank and enable them to cope with the changing demands of existing customers and lure prospective customers. These APIs can also serve as a unique way to improve customer engagement and provide for customer needs in an agile, secure, and future-proof method.
• Profitability increase Increased access to individual transactional data will allow lenders to better understand customers’ risk profiles at a more granular level. Lenders will be able to augment credit scores with empirical cash flow data to better understand individual customers who do not currently hold relationships with them. Furthermore, lenders will be able to price risks for each individual transaction to reflect its context, from purchase type to total borrowed amount.

In related news, according to another recent report by Deloitte’s Middle East Financial Services practice, the firm found that one fifth of Middle East bank holders now use FinTech solutions to bolster their experience and financial management.