AI and Fintech Trends in 2021
AI is changing every industry, and Fintech is the pioneer industry in terms of the adoption of AI. This article goes over the Fintech Trends and how AI impacts the Fintech industry.
Since consumers are increasingly becoming digitalized, payment services providers have to focus on the speed and convenience of paying. Mobile and online banking services have grown from 20% to 50% across countries during the COVID-19 pandemic. Companies of different sizes scale up the provision of digital services, given the constant lockdown, and aspire to maintain that high level in a post-pandemic time.
AI and ML help facilitate many traditional processes, saving time and resources. McKinsey estimates that AI might bring $1 trillion of incremental value for banks by automating different areas of work, helping control risks, and facilitating decision-making.
Financial institutions that seek to be AI-first consider adopting AI-based solutions as a matter of urgency. They wish to access powerful data processing, profound personalization options, and value-adding predictive analytics in the short term.
What are the core application fields where AI and ML solutions could be extremely beneficial?
- Modernization of your back-office processes
- Reduction of costs spent on repetitive operations and support
- Provision of amazing customer experience
- Assitance to your clients in making informed financial decisions
- The highest level of financial security for your solutions and services
These are just a handful of examples of AI and ML capabilities that might help you step up your business.
Robotic process automation and robo-advisors
Robotic process automation (RPA) for a range of processes is vital to save on operational costs and resources, reduce human errors, and promote informed decision-making. Additionally, AI and ML enable the two trending solutions: personalized portfolio management and product recommendations. Robo-advisers can handle mundane and time-consuming tasks, including data analysis for personalization, gathering in-depth insights, or recommending money-management and investment solutions without human intervention and often with much higher precision than human specialists.
Another way RPA helps financial organizations become more competitive is by managing compliance and industry regulation issues. Working with regulators could involve many repetitive tasks that robots can complete, thus lowering expenses and improving efficiency. That makes RPA a relatively low-cost approach to improving back-office operations and assisting clients with making the best financial and investment decisions.
Credit scoring and churn prediction
Some current credit scoring systems can often take into account stereotypes, such as race, age, or gender, and refuse to provide credit as a result. AI and ML may help companies focus on customer profiles and a particular person, and such a case-by-case approach can promote more positive decisions on crediting.
Along with that, AI-powered solutions can take the customer experience one step further by enabling a better digital experience, automated transactions, and analyses of massive amounts of data that describe consumer behavior, sentiments, and weaknesses of service provision. Companies would be able to prevent customer churn by addressing anticipated and potential pitfalls.
Financial institutions deploy AI-enabled chatbots to provide a high-level customer experience and meet the demand for instant responding and issue solving. Chatbots allow a practically real-time conversational experience by processing high volumes of incoming information. For example, Bank of America, Capital One, and Wells Fargo have used chatbots already for several years, which help them address customer queries and offer financial advice effectively.
Using chatbots, financial institutions can deliver five-star conversational servicing to their clients. However, brands need to carefully select and identify chatbot technology and acquire robust chatbot solutions to ripe the benefits. The technology is evolving and could soon allow users even more personalization, so they would be able to communicate with providers on their terms.
Fraud prevention and cybersecurity
Security and fraud mitigation are essential for organizations dealing with financial information and clients' sensitive data. Over 55% of businesses across the globe reported fraud in 2020 and admitted the increase of fraudulent activities in that year.
Financial institutions, including fully digital neobanks, need to timely detect and address security breaches to minimize the damage of possible cyberattacks that are practically impossible to prevent. AI and ML-based solutions can help ensure the highest security level, protecting businesses and clients. Therefore, investing in cybersecurity is a must, especially considering that banking and financial services are massively going digital these days.
Facial recognition payments
Imagine - your clients don't have to carry a smartphone, credit or debit card, or any other identification source to pay for goods or services. That sounds like an enticing feature to boost their loyalty.
Facial recognition technology offers all those opportunities. The technology has already become extremely popular in China - in 2019, more than 1,000 convenience stores implemented the facial payment option powered by Alipay, and over 100 million users registered to use the innovative payment method. Biometric payment cards have also become popular in California and Spain, with networks of facial recognition-powered ATMs installed in Barcelona, Valencia, and other major cities. The biometric-based payment method is highly secure and could one day become a digital payment type number one.
The current influx of demand for digital services and remote communication requires new approaches from financial institutions to gain and retain clients and stay competitive. They have to keep up with the technology development and offer cutting-edge and convenient servicing. Many financial organizations opt for AI and ML-driven solutions to solve current challenges and gain an edge over competitors.
We should expect more AI-driven assistants and fraud prevention solutions, enhancing financial and payment services for clients worldwide and providing a higher level of security in transactions, user-friendly navigation, and processes automation. It is the right time for your organization to join the lines of AI and ML adopters.