Artificial Intelligence (AI) has become the catalyst for digital transformation within the FinTech industry, reshaping the dynamics of the banking, financial services, and insurance sectors. A study by Moody’s Analytics reveals that nearly one in five FinTech professionals (18%) actively embrace AI, underlining its increasing adoption in the industry.
AI is no longer just a buzzword but a driving force behind the evolution of how customers manage, invest, and interact with financial systems. In this blog, we will take a closer look at the profound impact of AI on FinTech, especially in areas like investment, customer support, fraud detection, and regulatory compliance.
Advantages of AI in FinTech
Leveraging the capabilities of AI in FinTech can have many strategic advantages. AI and machine learning can improve overall efficiency, boost cybersecurity, and sweeten the consumer experience in multifaced ways, especially in the following four critical areas:
- Investment: Predictive AI transforms investment strategies, leveraging real-time data for informed decisions.
- Fraud Detection: AI-powered algorithms act as vigilant guardians, identifying and preventing fraudulent activities.
- Customer Service: Virtual assistants and chatbots, fuelled by AI, provide instant and personalised customer support.
- Regulatory Compliance: AI ensures adherence to ever-evolving regulatory standards, minimising compliance challenges.
AI in Action: Exploring Key Applications in FinTech
Predictive AI in Investment and Risk Management
Predictive AI is like a magical crystal ball, except that it is not actual magic but based on a concept – machine learning (ML). Machine learning algorithms analyse past and current data sets to make predictions and recommendations for the future. The predictive machine learning models also minimise risks by identifying pitfalls before they manifest.
FinTech players leverage Predictive AI’s capabilities to make better investment decisions at significantly lower risk. AI technology facilitates the seamless integration of structured and unstructured data from various sources into investment risk systems. It encompasses a wide range of data, such as financial data, market information, news articles, social media feeds, and other pertinent sources.
AI in Cybersecurity and Fraud Detection
Although there are traditional methods of rule-based detection of fraudulent patterns or detection of anomalies (from the expected patterns in a dataset), these methods are inflexible, static, and have high false positive rates (due to challenges in identifying genuine abnormalities from acceptable variation in user behaviour).
Enters AI! By harnessing machine learning algorithms, FinTech organizations can scrutinise extensive datasets, identifying patterns and anomalies indicative of fraudulent activities with high precision. AI-powered systems continually learn from new data, uncovering subtle patterns to proactively establish defences against fraudulent activities.
AI in Customer Support and Engagement
AI chatbots and virtual assistants are cost-efficient, precise, and personalised tools for customer support and seamless user engagement. They provide help to customers based on patterns from the learning data. Moreover, these AI-based tools can continuously learn and update themselves from new data and interactions.
AI can also help users navigate through the vast knowledge bases in the help pages of the FinTech website/application. It can surface generated answers from knowledge bases directly into the search page, making the journey easy and pain-free for the user. AI is transforming customer support and engagement by providing personalized and proactive interactions, enhancing the quality of responses, and improving customer satisfaction.
AI in Regulatory Compliance
Harnessing AI technology in regulatory compliance can result in cost reduction and achieving high efficiency and accuracy in this area. With AI/ML development of specific software, organisations can automate and streamline tedious compliance processes. This will help FinTech companies identify and mitigate compliance risks proactively.
AI’s adoption in Fintech can make regulatory compliance activities more efficient, including risk detection, regulatory change management, horizon scanning, obligation libraries, policy management, control management, third-party risk management, anti-money laundering (AML), and know-your-customer (KYC) obligations. The unmatched data processing and pattern recognition capabilities of AI enable businesses to navigate the intricate maze of global regulations more precisely and with greater speed, reducing the risk of non-compliance and potential fines.
The Future of AI in FinTech
The potential of AI is enormous, and it is going to influence every industry, and FinTech is no exception. According to Finextra, two-thirds of FinTech companies already leverage AI, and its influence is set to grow.
In conclusion, the era of AI-powered FinTech marks the dawn of a new era in the entire BFSI (banking, financial services, and insurance sector). AI/ML development will help reduce human intervention in tedious tasks, enabling businesses to utilize human time and intelligence in innovation and expansion activities.
Choose Advantal for AI/ML Development Services
At Advantal Technologies, we’ve successfully developed machine learning algorithms for custom-made AI-powered tools that provide an impressive 90% accuracy in their predictions and recommendations. We can tailor cutting-edge AI capabilities to meet the unique demands of your FinTech project.
Call us at +91-9926054677 or write to us at sales@advantal.net to book your FREE project consultation session.