Introduction
Semantic AI is a set of techniques, processes, and technologies that automate the generation of digital business applications and services by harnessing the power of machine learning. It allows businesses to focus on delivering end-to-end solutions that are more efficient and effective than traditional methods.
Semantic automation is a subset of artificial intelligence that uses machine learning techniques to analyze unstructured or semi-structured data to make predictions. It’s often used in conjunction with other types of AI, such as deep learning, reinforcement learning, and neural networks. The word “semantic” means language and can help FinTech organizations design more accurate customer fidelity models and personas based on the relevant intent levels.
According to blueprism.com, financial services companies that have invested in intelligent automation have witnessed significant increases in their productivity rates, an improvement in their agility and resilience, higher accuracy and speed in areas like compliance, and better customer service. In fact, 87% of the respondents from the research have experienced digital acceleration in some way.
The benefits of semantic automation are manifold: it helps companies gain insight into their customer base; it reduces costs by automating repetitive tasks; it increases productivity as humans can automate repetitive tasks so that the ones that are more critical in nature can be offered more attention.
So, let’s unravel how semantic AI benefits FinTech companies:
1. Cost Optimization
Semantic automation can help you to reduce costs and increase efficiency. For example, it helps you to reduce the cost of compliance.
Approximately 75-80% of transactional operations, such as general accounting and payment processing, and up to 40% of strategic operations, such as financial controlling and reporting, financial planning and analysis, and treasury, are expected to be automated over the next ten years, depicts research by McKinsey & Company. AI can also increase the global banking sector’s annual valuation by $1 trillion, primarily by reducing costs.
Semantic automation also helps in reducing fraud, customer service, and other operations by automating them through data analysis and machine learning algorithms that are powered by AI machines such as IBM Watson, Google Assistant, etc.
2. Transfers Extensive Analog Processes to Digital
Semantic automation facilitates the process of converting analog data into digital data.
Semantic automation allows us to transfer our existing processes into a new software system by using artificial intelligence (AI) and machine learning technologies like deep learning and neural networks, etc., to automate manual tasks.
Digital transformation is changing the way business is done. Businesses that have adopted digital transformation have seen significant improvements in performance, efficiency, and cost savings.
These benefits are typically achieved with the help of automation.
Semantic automation transfers extensive analog processes to digital platforms by using existing manual systems to create new digital solutions. It has many benefits, including:
- Reducing errors or risk
- Improving efficiency
- Improving quality & security
3. Semantic Automation Powers RegTech & InsurTech
Semantic automation is a process that uses artificial intelligence (AI) to understand the meaning of data. This understanding allows for the automation of tasks that would otherwise require human input. In the world of RegTech and InsurTech, semantic automation is used to power a number of different processes.
One of the ways semantic automation is used in these industries is to help with regulatory compliance. Semantic automation can help identify and track important information that needs to be reported to regulators. The data comprehension abilities can save companies time and money as they no longer must spend resources manually gathering and tracking this data.
Semantic automation is also used in risk management. By understanding the risks associated with certain activities, semantic automation can help companies make better decisions about protecting themselves from potential losses. Additionally, semantic automation can be used in underwriting to help identify risk factors and calculate premiums accordingly.
Finally, semantic automation is often used in customer service applications. By understanding the meaning of customer inquiries, semantic automation can provide better customer support by automatically routing inquiries to the right person or department. Additionally, semantic automation can be used to create knowledge bases that contain information about commonly asked questions and their answers. These knowledge bases can help customer service representatives provide better support by giving them access to relevant information to the customer’s inquiry.
4. Semantic AI is Revamping the Banking Sector
Semantic AI is revamping banking and helping banks provide more personalized services. It’s transforming how banks do business by making it easier for them to understand their customers and make better decisions based on that knowledge.
Some of the benefits of Semantic AI include:
- Improved customer service due to more personalized recommendations and offers.
- Increased efficiency as a result of automating previously manual tasks.
- Enhanced security as systems become better equipped to identify and prevent fraud; and
- Greater insights into customer behavior can help banks improve their products and services.
For example, using a technology called the knowledge graph, which is employed by tech behemoths like Amazon, Google, and Apple, it’s possible to connect several databases into one cohesive whole where information can be searched across those sources to deliver personalized experiences for each individual user—and all without requiring any human intervention.
5. Augments Your Digital Workforce to Empathize, Collaborate, Network & Create
Of course, the most apparent benefit of semantic automation is that it can help you to augment your digital workforce. For example, software and systems are programmed to take on multiple business functions and perform them without human intervention. For example, one program could be responsible for managing customer relationship management (CRM), while another could handle sales lead generation through social media campaigns or email marketing campaigns.
Semantic automation also allows companies to scale their workforce as needed by using AI-powered bots instead of hiring new workers every time there’s an increase in demand for labor within their business model.
6. Systematically Integrating & Automating End-to-End FinTech Operations
Semantic automation leverages machine learning and AI to automate tasks that humans can do. It’s a great way to streamline your end-to-end FinTech operations, including:
- Helping you increase customer satisfaction with your services
- Improving the quality of your data
- Making it easier for you to scale up without having to hire more people
7. Data-Driven Approach to Improve Customer Experience
A data-driven strategy is unavertable to improve the quality of services.
Semantic AI is a technology that uses machine learning models to analyze data. Semantic AI can help businesses improve customer experience by decrypting diverse data points. For example, Semantic AI can identify customer sentiment from social media data and use this information to improve customer service.
Semantic AI can also use data to create personalized recommendations for customers. By understanding a customer’s preferences and past interactions, Semantic AI can recommend products or services that interest the customers more. This approach can improve customer satisfaction and loyalty.
Overall, Semantic AI can use data to understand customers and their needs better. This understanding leads to improved customer experiences and ultimately increased profits for businesses.
8. Securing Services with Better Fraud Management
Security is a top priority for financial services. Consequently, the rise of new regulations and data protection regulations such as GDPR has become the norm, which facilitates companies to protect customer data and avoid its misuse for purposes other than those stated in their privacy policies.
Semantic AI secures FinTech services with better fraud management by understanding the meaning and context of data, calling for more accurate identification of fraudulent patterns and potential threats. Additionally, Semantic AI can help to automate the process of fraud detection and prevention. By analyzing data as it comes in, Semantic AI can identify suspicious activity and alert FinTech employees to take appropriate action. As a result, Semantic AI can help to keep FinTech services safe and secure from fraudsters.
Not only semantic automation improves security, but it also improves customer experience. A semantic technology system will help you build a better and more secure model using external data sources such as social media posts or emails sent through multiple channels. It also allows you to scale your business quickly across omnichannel, as it does not require any changes in existing systems but instead works alongside them so that they become more intelligent over time.
Wrap up
Semantic AI is a big deal, and it will only get bigger. It’s already being used by companies like Amazon, Google, and Facebook to power their services. But what should a FinTech company do to leverage semantic AI?
The answer lies in building an intelligent system that can understand your customers’ or users’ needs better than you do—and then delivering them with the right product or service at the right time. If you’re not doing this now, start looking at how your competitors are doing it; if they have figured out how to do it (well enough for their own benefit), there’s already evidence and a pragmatic roadmap for you to get started.
Semantic automation can help you scale your FinTech services by automating the process of understanding and extracting meaningful insights from data. The technique allows you to keep up with the ever-growing demand for data-driven services and to stay competitive in a digital-first world.
The future of semantic AI looks very promising. With the rise of big data and the internet of things, there is an increasing demand for services that can make sense of all this data. Semantic AI is well-equipped to handle this challenge, and we expect to see many more innovative FinTech applications utilizing semantic automation in the future.At MSys Technologies, we have over 320+ FinTech engineers with 8+ years of experience delivering cutting-edge FinTech services. Best practices and time-tested methodologies drive our DevOps teams so that you can be assured of end-to-end, high-quality FinTech services. Supercharge your FinTech ecosystem with AI; contact MSys for full-stack FinTech services.