Artificial intelligence has modified the physics of financial services (AI). It has altered elements like centers of gravity and weak bonds that are crucial for building a successful business. Data-driven process and talent optimization, product performance, and personalized interactions are now considered to be crucial for increasing value and efficiency.
How AI transforms banking & fintech
Customers in the Millennial and Gen Z generations favor modern, fast technology over antiquated ones. FIs can now meet the demands of customers who are living in the digital age thanks to AI-based goods and services. They are able to improve the user experience by offering specialized goods and services.
Artificial intelligence (AI) technologies improve the entire customer experience by providing individualized recommendations, insights, and suggestions. To put it briefly, AI enables banks, insurers, asset managers, and fintech to outperform competitors, increase customer lifetime value, and gain market share.
Top 6 use cases of AI in fintech and banking
For AI applications, high-performance computing (HPC), machine learning, and deep learning are used by more than 75% of businesses. Fintech companies use machine learning for the use cases below, whereas deep learning is advantageous for retail banking and capital markets.
Transaction fraud detection
Financial institutions use AI and machine learning to efficiently detect, investigate, and mitigate transaction fraud, money laundering, and KYC discrepancies. AI can decode risk factors and help reduce chargebacks, fake accounts, spam, account takeovers, and other CNP frauds in real-time by analyzing large datasets and user behavior. To name a few, the fraud detection use case is critical in banking, card transactions, insurance, and lending platforms.
Conversational chatbots
Conversational AI applications include chatbots and virtual agents. They are not the same as traditional chatbots. They can understand customer intent, troubleshoot issues, and make small talk based on context by leveraging Natural Language Processing (NLP) and Machine Learning (ML) processes. They can be used in financial institutions to collect customer information, provide support, resolve queries, and redirect escalations to customer service representatives. These chatbots can provide support via audio, video, and text and can be used across multiple channels.
Regulatory intelligence
To remain in compliance with governments and regulators, the banking and fintech industries must update their operations on a regular basis. AI streamlines, automates, and simplifies compliance requirements. Role-based, personalized dashboards provide cost-effective regulatory intelligence for data-driven decisions. The most recent regulations can be kept up to date, and financial institutions can monitor their compliance status.
Credit decisioning engine
AI-based credit scoring can help speed up creditworthiness and lending decisions. In addition to credit history, transaction patterns, work experience, and online behavior, AI-powered credit scoring models examine real-time indicators such as current income, employment opportunities, and potential earning ability. This allows for a more sensitive and personalized credit score assessment, as well as more inclusive lending decisions.
Algorithmic trading
Making profitable transaction decisions is the foundation of trading. AI-driven algorithmic trading makes profitable trades and develops skilled traders by using pre-trade analytics and trading strategies. AI-based algorithmic trading produces real-time forecasts based on the analysis of price change patterns, currency values, global indices, raw materials, and other macro/micro indicators by assimilating its own data using machine learning techniques. It assists in lowering operational and trading risks and is incredibly accurate at spotting market anomalies.
These, however, are not all. In addition to the use cases mentioned above, AI can speed up and automate customer acquisition, underwriting, and marketing optimization.
More Stories
Various benefits and examples of Regulatory Technology
Regulatory technology, also known as RegTech, is a term used to describe a category of technology solutions that help businesses...
BNPL apps that can help consumers who do not own credit cards
Buy Now Pay Later (BNPL) is a payment service that allows consumers to make purchases and pay for them in...
10 ways AI is quickly invading marketing platforms
Artificial Intelligence (AI) is rapidly changing the way we live and work, and the marketing industry is no exception. In...
10 tools everyone needs to make Content marketing easier
Content marketing has become an increasingly important aspect of modern digital marketing strategies. But what exactly is content marketing? Simply...
Experience the new digitalization of the Insurance sector with InsurTech
Insurtech is a term used to describe the use of technology to revolutionize the insurance industry. Insurtech companies use digital...
Top 10 Marketing automation tools helping marketers
Marketing automation is a crucial part of any successful digital marketing strategy. It helps businesses streamline their marketing efforts and...