AI as Risk Management Game-Changer in Banking

Updated On : September 2021

The banking, financial services, and insurance (BFSI) industry landscape is been reshaped by Artificial Intelligence (AI) in different functions like risk and compliance management. AI is creating new opportunities for financial institutions to have a large amount of data. AI is saving time, is helping banks to identify risks, fraud, boosting revenue, and improving the customer experience, thus it is one of the key banking industries transforming drivers.

To identify risks in a timely and effective manner and to make informed decisions the risk managers use machine learning models as they can analyse large amounts of data which helps to improve the analytical capabilities in risk management and compliance.

The AI applications in the financial services ecosystem help to identify the patterns and connections that humans can’t, this gives the chances for improving and augmenting the financial business processes. Hence the banks are now investing in AI, machine learning, blockchain, and digital identity systems.

Before the digital revolution in the banking and financial sector, customer intelligence was based on learning via trial and error methods, like the customer data was collected by focused groups and conducting surveys on consumer behaviour.

But today these new technologies are giving businesses access to a tremendous amount of data about consumer’s behaviour and their needs.

According to Capgemini insights the non-traditional lenders use technology-based algorithms and software integrations to assess credit profiles of customers and alternative data like social media photos, check-ins, GPS information, online shopping, and bill payments.

Risk management in the financial sector is using cognitive technologies to gain a competitive advantage. Risk management and AI work perfectly together when there is a need for handling and evaluating unstructured data. It is estimated that the risk managers will focus more on analytics rather than spending time to manage risks inherent in the operational process.

Key drives of digital transformation in Banks:

• Increasing competition between traditional banks, fintech, and digital-only banks
• To meet digital and tech-savvy customers’ expectations
• To optimize operations and reduce costs

Advantages of AI in Compliance automation and risk in Banks

• Fast and improved risk assessments
• Improved efficiency in combating compliance violations
• Reduced Costs
• Faster and better customer service
• Helps the bank to make informed decisions because of predictive forecast
• Improved auditing
• Mitigates cybercrime

AI is making the banking process not only intelligent to the banks as well as for the employees but also in mitigating cyber risks, money laundering, and frauds.
Banks with the help of AI-driven automation are going to leverage machine capabilities for enhancing operations, reducing manual errors, and become cost-efficient. With help of AI, banks can deliver personalised services to the customer and thus will help to increase revenue and growth.