How is technology helping financial companies?

AI in the fintech market

Artificial intelligence has become a promising technology for companies in various sectors of the economy. Financial companies are pioneers and leaders in this field. Autonomous Research has calculated that by 2030, AI will save industry up to 22% of funds. Forrester estimates that about half of the world’s banks and insurance agencies use smart algorithms in their transactions, and the demand for FinTech Development Services continue to grow. Consider the value of artificial intelligence in FinTech.

AI statistics in the financial sector in 2022

When financial companies implement AI, their main goal is to reduce transaction costs. Other significant benefits include improved data management and increased employee productivity.

In 2021, most financial institutions have partially implemented smart algorithms in their transactions. Only a third of participants in the Statista survey claim to have fully kissed technology.

By 2026, the share of artificial intelligence in FinTech will almost triple. It will be to reach $26.67 billion. Organizations are interested in this innovation and are investing in AI-based projects to automate operations and grow their business.

The value of AI for financial companies

Artificial intelligence in finance supports many traditional procedures, from front to back offices.

Artificial intelligence is used in many sectors:

  • banking;
  • insurance services;
  • loans/credits;
  • personal finance;
  • digital payments;
  • capital risk;
  • wealth management.

FinTech companies benefit from AI. Technology helps to work with data, which is a rich competitive resource. Companies use only 0.5% out of 44 zettabytes of data generated annually. There is a lot of information in the financial industry: browser specifications, transaction history, images, confidential information, etc.

An intelligent algorithm optimizes the work with data to achieve maximum benefits for your business. It will help you:

1. Accurately access credit risks

Lending is the biggest niche in the financial industry. In 2020, America alone had around $4.17 trillion in outstanding consumer credit, or $62.4 billion more than a year earlier. Negligent payers are becoming a problem for banks.

Banks scrupulously check the creditworthiness of applicants to avoid a financial disaster. It is difficult to perform this task manually: bank employees must analyze the credit score, familiarize themselves with loan applications, calculate payments and approve or reject the customer’s application.

Artificial intelligence automates underwriting. An intelligent algorithm analyzes the candidate’s fingerprint: profile on social networks, browsing history on web resources, geolocation. The technology evaluates the collected information and provides bank employees with conclusions about credit risks.

AI-based subscription is paid. With this technology, companies increase loan approval percentage and extend payment terms. They trust borrowers, offer more money for longer term without risk to their business.

2. Save resources.

By adopting AI-powered applications, banks save $447 billion by 2023. Emerging Technologies calculated that smart algorithm followers increase their annual revenue by 58%.

To increase profits, banks do not need to raise the price. They deliver better deals to customers through improved processes. Users do not turn to competitors because it is convenient for them to work with the bank. Conversion is growing, as is revenue.

Savings become possible through AI automation. Previously, the procedures were done manually and took more time. Artificial intelligence takes over responsibilities such as data analysis, application underwriting and approval. Employees accomplish more tasks during the same period.

3. Customize services.

In pre-technological times, bankers needed to know their customers personally to help them manage their money rationally. Today, with each bank having ten hundred million customers and most transactions taking place through banking apps, it is more difficult to “please” individual consumers. More than 50% of financial services users believe this personalization makes them trust their banks. Only 35% of financial institutions can meet these demands.

Artificial intelligence allows organizations to quickly analyze large amounts of consumer information. Based on the results, the algorithm selects relevant products that meet individual demands. As a result, users get what they like and continue to cooperate with the financial company. Increase customer retention by just 5% increases 25% profit.

4. Detect fraudsters.

The industry has always been concerned about protecting customer privacy. The pandemic has forced financial institutions to adapt their business models to the new rules. For example, they switched to remote lending. Consumers are more likely to pay for products online, use digital wallets and use P2P payments. As a result, additional loopholes have appeared for attackers.

PwC found that in 2020, a company was attacked six times on average, costing $42 billion. FinTech data breach costs are among the highest at $5.72 million.

An intelligent algorithm monitors the behavior of users of a banking or insurance application, automatically detects fraud threats and flags suspicious activity. For example, if a borrower tries to apply for ten identical loans in 5 minutes, the artificial intelligence detects this behavior as an anomaly and alerts cybersecurity specialists.

5. Make accurate predictions.

Good analytics in FinTech affect sales growth, business development and competitiveness. It may depend on the forecast whether a loan will be granted to a reliable person or to an insolvent person; which financial products will be useful to customers in the future, etc. To find a pattern in the processes and draw reasonable conclusions, it is necessary to study a huge amount of data, learn how to store and protect it. It is quite difficult to do it manually. Smart tools are needed to turn data into valuable insights. One of them is AI.

Artificial intelligence examines stored customer data and “tells” managers how to use the information profitably. A person can predict demand based on sales data from previous years without using machines. But only artificial intelligence can reveal complex and unexpected variables.

How to Implement Artificial Intelligence in FinTech

While many financial institution owners view AI as experimental or utopian, early adopters of the technology are already seeing practical results. Therefore, some business processes should be developed to pave the way for artificial intelligence.

Deloitte has identified six steps to harness the power of AI:

  1. Develop an AI strategy.

It is necessary to establish which processes the company wants to improve with the help of AI, whether it plans to use the technology partially or everywhere. He must become familiar with the technology, add it to the culture of the organization and adapt the AI ​​to the business objectives of the company. Employees must decide what needs to be done and how to make the technology useful.

2. Define use cases for AI.

This is the most difficult step in introducing AI into an organization. Some companies are rushing to adopt the technology simply because it’s popular. They don’t realize its value and its long-term prospects. A smart algorithm provides many opportunities that we mentioned above. It is worth choosing priority use cases and evaluating their advantages and possible disadvantages. Thus, the company will understand how to start AI software development.

3. Create a prototype.

To determine if it is technically possible to implement an AI use case in an organization, if it is worth investing money in a solution, it is necessary to create a prototype. It is important to check how this solution will work alongside the existing ones. Make sure your employees are ready for a radical change in their work. Estimate whether the investment in the AI ​​application will pay off.

4. Consider privacy.

Typically, technology testing, risk assessment, legal and ethical issues come into play in the later stages of AI software development. They should be discussed before the start of the project. Thus, you will build an application taking into account the requirements of privacy and legislation.

5. Create a reliable team.

To make the idea of ​​adopting AI a reality, you need to appoint a team to help you introduce the technology into a business process. You will need a data scientist, UX designer, developers, tester, and other staff to work on the project. When a company does not have such personnel, it is impractical to hire temporary employees. Consider outsourcing IT services.

6. Maintain technology after deployment.

AI support and training continues after the software is implemented. It is necessary to analyze how AI models react to different input data and improve the algorithm. If you skip this step, the model will drift and start producing inaccurate results.

Conclusion

Artificial intelligence in FinTech creates a better financial environment for banks and their customers. You must be mentally and technically prepared for change to implement the technology. It is worth enlisting the support of a FinTech development company who will create an AI application, deploy the software in your organization and update the product if necessary.

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