With FinTech posing a challenge to the traditional banks and disrupting their core financial services, it has pushed the banks to innovate to remain relevant. There is an increased reliance on Artificial Intelligence (AI) by the banks to meet the competition posed by the FinTech players.
The impact of AI in retail banking can already be seen in retail banking, like customer service chatbots, credit scoring, and the use of data analytics in the segregation of customers and pitching of customized products. AI has also the potential to be leveraged in corporate banking and is being recognized now. Some of the application of AI in corporate banking is being discussed here.
Detect Money Laundering
AI can equip banks with technologically intelligent weapons to help detect money laundering. AI can be used to monitor and scan customer profiles and finding the origin of funds and identify high-risk individuals. Transactions can also be monitored to raise alerts in case of aberration from the regular transaction. Machine learning models can also be used to detect changes in customer behavior and the nature of their transactions. ML can also reduce the number of false alerts effectively compared to traditional anti money laundering devices.
Eliminate Discrimination in Lending
Apart from transaction data and data provided to the bank, AI can also analyze large amounts of external data related to customers like professional, institutional, political, and social like the information in media, social networks, and the public through natural language processing. Financial institutions can thus eliminate discrimination in lending, and to make credit decisions. Algorithms can assist in making the right credit decisions and improve customer relations.
Cross-Selling and Offering Tailored Services
AI-based solutions can equip Relationship Managers (RMs) to provide appropriate and timely advice to their clients by scanning their profiles and transaction history and generating the products best suited for them. This can help banks in cross-selling and offering tailored services By using predictive analytics and algorithms to analyze client behaviors, it can generate inputs in between the conversations and help close the deal.
Reducing Turnaround Time
Through Robotic process automation– using software robots — labor-intensive and repetitive tasks can be drastically reduced and turnaround time for various services and productivity of employees can be improved. It can play an important role in automatic report generation, account opening, customer onboarding, loan processing, and a wide range of back-office processes. Thus, by automating manual business procedures AI allows banks to stay competitive in an ever-evolving market.
Big Data for Predictive Analytics
Banks generate huge amounts of data through interactions and transactions. This can be analyzed by helping banks to comprehend all those client interactions and predict future behavior and providing them with valuable insights.
There are various solution is being deployed at various levels in the banking industry and having a positive impact on their functioning. To know the details and discuss more on this as well as other evolving solutions in multiple domains please write to us at open-innovator@quotients.com.
