Emerging fintech markets face few constraints in using cloud computing, big data, artificial intelligence, and the other technologies for up-to-date digital banking services.
Digital banking will have great ramifications in the coming years. The ongoing development of robotic process automation, big data, artificial intelligence, and other technologies in financial services is cause for concern in some quarters.
One indication of its impact: Wells Fargo, late last year, distributed a special 110-page report providing details on the impact of digitization on Wall Street. The bank predicted about 100,000 bank employees would be outright replaced by digital technologies by 2026.
The question then is not whether fintech must change. The question is, what exactly makes this happen? To understand this, it is crucial to grasp which digital innovations and organizational approaches let emerging markets leapfrog into digital banking.
Branches: addressing from another angle
Digital services seem to reduce the need for physical bank offices. The COVID pandemic made many people handle their financial issues via digital banking and ATM machines.
Banks must transform their physical offices into digital banking ecosystems since transactions via e-wallets can hardly cover the entire scope of operations that clients require from their banks.
Digital banking services appear to be a problem for many elderly customers who require in-office assistance provided by human specialists. In addition to the traditional in-office procedures that require face-to-face customer support, many “exotic” activities such as legal advice, insurance, brokerage, and real estate consulting are offered by bank branches today.
Banking transformation does not polarize physical offices and client-bank software, while human clerks are not juxtaposed to AI-powered chatbots. Service digital channels allow operation managers to turn to “superheroes” whose human capabilities are supplemented by digital developments.
Ultimately, bank branches have an opportunity to become a playground for augmented reality where physical, digital, human, and cyber can effectively intertwine to reinvigorate the striving banking industry.
Rethinking customer engagement: how banks behave in the digital new normal
In the increasing competition with innovative payment platforms such as Venmo, TransferWise, PayPal, Remitly, and the like, the task of banks comes to holding the existing clients with personalized approaches similar to what fintech disruptors offer. To fulfill the task, banks ought to follow some trends that Accenture has indicated in their global research Banking Technology Vision.
Trend 1: Using a group of DARQ techs where D is for Distributed Ledger Technologies (blockchain), A for Artificial Intelligence, R for extended (or augmented) reality, and Q for quantum computing. According to 47% of respondents, the most impactful technology for digital banking is AI.
Trend 2: Achieving a new level of “digital proximity” with clients. The ability to analyze and interpret customer behavior is critical to creating high-quality individual services in digital banking.
Trend 3: Improving the digital skills of banking staff. More than 75% of top managers are sure that their employees have a higher level of “digital maturity” than the banking organizations where they work.
Trend 4: Strengthening cybersecurity. Despite the global trend of Open Banking (when banks provide access to their information systems for third parties), only 51% of bank supervisors accept their partners as fully reliable regarding the cybersecurity of digital banking ecosystems.
Trend 5: Setting services to the non-stop operation. The “closed till 8 a.m.” excuse is hardly acceptable whichever banking service it may concern. About 87% of bank top managers agree that real-time services constitute the true competitive advantage of digital banking.
What digital technologies should banks use?
Hardly any sort of digital innovation has a certain value for emerging fintech markets. We have selected a few proven technologies worth using by banks right now.
Digital banking ecosystems with their multi-user platforms require computing capabilities above average. Banks should collect, securely store, and analyze data to develop new banking products. Bank staff should have access to their datasets from anywhere at any time. Even the richest on-premises IT infrastructure is at risk of becoming obsolete one day. In contrast to banks, cloud providers are the ones who make their living from keeping pace with all digital innovations offered to clients:
- They regularly upgrade their hardware without interrupting ongoing services.
- Cloud computing management is facilitated by the most up-to-date software solutions developed by the best software engineers.
- Clouds offer almost infinite storage space for any sort of data.
- Continuous backup of the entire in-cloud infrastructure lets clients forget about losing valuable info.
Cloud computing in banking has a convincing financial rationale allowing banks to spend fewer funds for digital transformation. The most expensive premium plans from cloud providers seem to be a drop in the ocean in comparison with what on-premises IT infrastructures require to spend.
It is legitimate to claim that no sustainable digital banking is possible without cloud computing financial services nowadays. Migom Bank, for example, provides cloud-based banking of the Swiss-grade standards for emerging markets with dynamic currency exchange, QR-code payments, and custody of digital assets.
Big data is the resource for algorithms of machine learning enabling many efficient banking approaches (KYC or know-your-customer, for example). Correctly processed big data contributes to predictive analytics as little else does.
Big data in banking requires corresponding software solutions for analytics and visualization. They should be graspable for banking staff having no deep data-science expertise. Both ready-to-use software products for big data processing and bespoke solutions are available on the market. The second approach is preferable since big data applications in finance have special goal settings and implementations. Financial organizations from emerging markets can hardly bypass big data analytics in banking since processing customers’ data is a must-have for fintech.
Artificial intelligence is built upon neural networks, which, in turn, are fueled by big data. Technologies for digital banking compose a sort of multi-level pyramid capped by AI.
How would the banking industry use artificial intelligence? The scope of AI applications is multifaceted in banking:
- AI algorithms can analyze customer behavior to deliver valuable recommendations for better customer satisfaction.
- AI facilitates the automation of banking routines, especially in risk management. It helps detect suspicious transactions to block them in time.
- AI can improve data analytics in the Bank-as-a-Service paradigm. The Commonwealth Bank of Australia, for example, proposes personalized financial plans for customers via an AI-powered mobile app.
- AI-enabled chatbots reduce operating costs by answering typical questions of customers around the clock.
- AI can enhance regulatory compliance through error-less fraud detection.
- AI-powered facial recognition facilitates client identification in mobile banking.
The majority of banking experts believe that artificial intelligence in banking and finance is the most value-adding digital technology.
Robotic Process Automation
Since the majority of in-bank operations still remain manually processed, robotic process automation (RPA) in financial services requires a wider adoption. Manual banking routines grab the most precious asset – time. Additionally, the risk of possible errors fails to be curtailed.
Fortune Business Insights predicts the RPA market capitalization is to reach $6.81 billion by 2026.
RPA use cases in banking include such a decent robotic process automation example as AML (anti-money laundering) analytics. AML investigation implies repetitive procedures based on highly regulated rules. Hence, MLA procedures can be easily fulfilled by robotics in banking.
Another example of RPA in financial services implies account closure processing. AI-enabled RPA bots can completely replace bank officers to let human staff focus on what really needs creative human intelligence. RPA is critical for the always-available banking ecosystems that mitigate poverty in emerging markets via mobile payments. Alvarez & Marsal, for example, are developing mobile payment banking infrastructures for African banks to deliver monetary benefits to the poorest population.
Cyberattacks on banks seem to be inevitable consequences of digitization. Hackers will always be attempting to grab hold of customer databases to sell them to marketers and advertisers via the black market.
In addition to technical means of hacking, fraudsters are using social engineering while making calls to potential victims under the guise of their banks.
The following digital technologies can mitigate cyber threats for financial institutions:
- AI-powered anti-fraud analytics can instantly check multiple data sources to detect discrepancies in documents and transactions.
- Digital identification technologies such as 2-factor authentication and cross-platform verification make banking systems less vulnerable to unauthorized access.
- Cryptographically encrypted emails facilitate the security of private communication between banks and clients.
Privacy is becoming a cornerstone in digital banking these days. Fortunately, there is no lack of digital technologies to provide sufficient cybersecurity in the financial sector. One of the Mexican “neobanks” Klar offers highly-secure banking solutions to ordinary customers who are deprived of State-owned custodial services.
A final word
Both developed markets and emerging ones have surprisingly equal opportunities for digital transformation. Moreover, emerging markets are better equipped to leapfrog into digital banking.
Software outsourcing vendors from Eastern Europe, Asia-Pacific, Latin America, Russia, and India offer advanced digital banking solutions cheaper than similar systems created in the USA and Western Europe.
Emerging fintech markets face few constraints in using cloud computing, big data, artificial intelligence, and the other techs for up-to-date digital banking services. The next step is to gain a deeper understanding of how these innovations work.