Financial services are the backbone of the global economy. Technology has been greatly shaping the way the financial services industry works and has enhanced value services. Let us explore how AI (Artificial Intelligence) has been increasingly adopted in the financial services sector, transforming, and transducing it.
Lending Patterns and Risk Management
Credit Scores: AI algorithms analyse a wide range of data to assess the creditworthiness of individuals and businesses more accurately. They determine if an individual is creditworthy, what are the pitfalls, whom to lend to, and the threshold of lending.
Credit Underwriting: AI incorporates non-traditional data sources (social media, online behavior) to assess the credit risk of individuals without a conventional credit history. This is called alternative data analysis. There are many loan apps (Cashe etc) using this to analyse the creditworthiness and repaying capacity of individuals.
Anti-Money Laundering (AML) and Know Your Customer (KYC): AI enhances compliance processes by automating the identification of suspicious activities and ensuring regulatory compliance. This has enabled many companies (Like Signzy) to capitalise on digital KYC growth.
Cybersecurity: Tools are enabled to detect and prevent cyber threats, offering an additional layer of security.
Fraud Detection: Machine learning models can identify unusual patterns and detect potentially fraudulent activities in real time.
Voice and Image Recognition and Biometric Authentication: AI-powered systems use voice and image recognition for secure authentication and access control. This enables better security and fraud detection.
Customer Service and Insights
Chatbots and Virtual Assistants – AI-powered chatbots handle routine customer queries, improving efficiency in customer service. This helps with better TAT for queries and has helped in cases of cybercrimes.
Personalized Recommendations – The most important usage of AI is in analysing customer data to offer personalized product and service recommendations.
Behavioral Analytics – AI helps in understanding customer behaviour and preferences, enabling financial institutions to tailor their products and services. Those special offers in your online banking account are based on algorithms that predict what you want.
Predictive Analytics -AI algorithms predict future trends based on historical data and assist in strategic decision-making.
Automation and Operational Efficiency
Robotic Process Automation (RPA)– Mundane and repetitive tasks are automated, reducing errors and improving efficiency. This has also led to many functions being outsourced.
Back-Office Operations – AI streamlines various back-office functions such as data entry, reconciliation, and report generation, facilitating compliance and governance.
Investment and Trading
Quantitative Analysis – AI algorithms analyze large datasets at high speeds, identify trading opportunities, and execute orders based on predefined criteria – the root of Algorithmic Trading.
Market Analysis-Natural Language Processing (NLP) is used to analyze news and social media sentiment for predicting market movements.
Wealth Management
Robo-Advisors: Automated investment platforms use AI algorithms to provide personalized investment advice based on individual financial goals and risk tolerance.
Insurtech
Claims Processing – Claims processing is expedited by automating tasks like document verification and damage assessment.
Claims Underwriting -The accuracy of risk assessment in insurance underwriting processes is enhanced, leading to better claim management.
The application of AI in financial services is vast and continually evolving, providing opportunities for improved efficiency, better decision-making, and enhanced customer experiences. However, it also raises considerations regarding data privacy, ethics, and regulatory compliance that need to be carefully addressed.
