The finance industry is continuously developing, having to adapt to the fast-paced technological dynamic. Online payment systems, mobile wallets, and banking have revolutionized the way people access products and services, such as borrowing and lending.
Technology has transformed transactions, made data management more efficient, and leveraged the benefits of automation, making finance more secure, fast, and productive. However, the never-ending evolution continues with innovative tools like artificial intelligence, machine learning, and blockchain. These technologies put the base for cutting-edge customer service, spotting fraudulent activity, and supporting digital assets like BNB, the native token on the BNB Chain ecosystem.
Meeting customer demand for resourceful technologies is necessary for companies to gain a competitive advantage, so let’s see how they adapt to current changes through technological advancements.
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Artificial Intelligence improves customer experience
Although AI is a relatively new trend, companies have approached it early to test its functionalities. Now, an increasing number of brands proudly utilize it for various features. Amazon uses it to provide users with personalized recommendations, Google offers an AI-powered virtual assistant, and IBM enables IBM Watson Analytics for companies to analyze customer data.
Among the many benefits AI can bring to a company, we list the following:
- Improved customer experience. AI algorithms analyze customer data and establish efficient interactions;
- Better decision-making. AI evaluates trends to provide forecasts in real-time;
- Enhanced risk management. AI helps automate risk identification, assessment, and management;
However, considering AI’s newness, companies face several challenges in adopting it. AI has been observed to have bias, depending on the data sets it is fed into. Therefore, its reports and responses can be unfair and lead to discriminatory outcomes. Businesses must use the highest-quality data for algorithms to benefit from useful reviews.
Moreover, trouble with data confidentiality might scare customers away, so organizations must tackle it by addressing ethical concerns and potential misuse of data. Transparency is the most important in combining AI with company products and services.
Digital trust frameworks support customer engagement
Digital trust is necessary for companies that want to develop or use digital technologies and services. Its goals include data security and reliability, accountability and oversight, and an inclusive and ethical use of organizational designs. Therefore, the framework aims to avoid manipulations of rules and standards and mitigate exclusionary practices.
Adopting technology requires a human-centric approach that prioritizes:
- Cybersecurity. Businesses must mitigate the risks of unauthorized access to their systems;
- Interoperability. Companies should be able to connect and exchange information safely;
- Privacy. Organizations must ensure customers the confidentiality of their personally identifiable information;
Building digital trust is essential for the future, but it’s also tricky. According to the World Economic Forum, experts predict that the cost of cybercrime will rise to $13.82 trillion by 2028, which will lead to vulnerabilities for companies.
At the same time, compliance with evolving regulations will compel businesses to keep pace with technological advancements and regulations, which may be challenging for those operating under multiple regulations and jurisdictions.
Quantum-safe cryptography prepares us for quantum computing
Quantum computers are supposed to become widely available in 2030, revolutionizing how technology offers solutions to modern problems. However, they might interfere with our current encryption methods, for which quantum-safe cryptography will be introduced. This technology will secure classical and quantum computers to interoperate with communication protocols and networks without threatening the security of transactions and customer data.
Quantum-safe cryptography will bring companies the following advantages:
- Future-proof security. Companies will be able to safeguard sensitive data in the midst of future threats;
- Regulatory compliance. Businesses can comply with emerging regulations during the adoption of quantum computers;
- Competitive advantage. Brands that adopt cutting-edge cybersecurity practices will prove their commitment to user data security;
Microsoft has already approached quantum computing by introducing the first chip in the world that can solve industrial-scale problems. While this is one of the most important moments in history, firms need to be cautious of emerging challenges.
Companies must navigate the lack of know-how and expertise to handle the technical complexity of quantum computers effectively. Professionals should prepare for the intricate technical landscape and prioritize regulations and data safety over competitive advantage.
Robotic Process Automation generates productivity
Robotic Process Automation (RPA) is software that automates repetitive tasks in high volumes. Manual tasks like data entry or claims processing can be operated by bots at unimaginable speed and scale. RPA is different from AI since it will do only what it is taught, so it might interact with generative AI and machine learning to be more efficient.
Regardless, it could enhance business finance by:
- Increasing productivity. Software products can work 24/7 and carry out numerous tasks;
- Enhanced accuracy. The robot cannot make human-error-like mistakes due to distractions;
- Innovative scalability. A business can handle an increase in demands with robots;
RPA has limitations, which make it difficult to implement at times. It cannot respond dynamically to changing parameters, so it’s only a data-informed process of business transformation. Therefore, companies leveraging it must be clear about their goals, prioritizing expectations and rationale for automation.
Integrating RPA with existing systems is another challenge companies will have to prepare for. Integration deployment might require additional technologies like AI or OCR (optical character recognition) to handle unstructured datasets. Moreover, RPA will still need long-term maintenance and monitoring to avoid errors from pre-programmed sequence deviations. RPA tools are prone to accumulating buds or reaching their full capacity.
What do you think about the future of finance?
As society changes, demands for products and services need advanced support from innovative technologies. So, the future of finance is shaped by AI algorithms that will improve customer engagement. Digital trust frameworks will enhance privacy and interoperability, while quantum-safe cryptography will offer companies the most significant competitive advantage. Finally, Robotic Process Automation will help automate mundane tasks to improve scalability, especially through a combination of AI and OCR. These features will make it possible for infrastructure to integrate tools that will make transactions faster, safer, and more efficient. At the same time, they’ll tackle risks of cybersecurity, scalability, and communication.
