How AI Is Rewiring The Banking Process

Historically, financial service providers have been slow to adopt innovative digital solutions for efficiency. A McKinsey & Company study found that 40% of large banks and credit service providers were less productive compared to digital natives.

To stay ahead of a fast-changing digital ecosystem, boost market competitiveness, and ensure more tailored customer experiences, financial service providers have embraced digital transformation. This helps traditional financial service firms catch up to their innovative peers.

Despite AI sweeping across industries, one survey found that only 13% of banks currently leverage AI-powered tech in several facets of their business. This includes lending operations to help improve overall process efficiency.

Moving from “experimentation” to “implementation” requires banks to have a clear understanding of the forward-looking needs of their business. They also need to see how a changing customer and economic landscape can drive them to provide more digital solutions to remain competitive, boost efficiency, and increase performance and customer satisfaction.

Changing The Way Banks Work

Despite the slower approach to adopting new tech, leading financial service providers and multinational banks have indicated their ambitions to invest in more dynamic AI-enabled tech that could help to change the way employees work and customers bank.

Real-Time Decision Making

AI-enabled tech has made banking more convenient for customers and employees. Charged-up systems are enabled with rapid response automation that allows for real-time decision-making. This reduces the amount of time customers spend on application processing for loans, credit cards, and mortgage approvals. With AI, banking systems can generate responses based on available data, customer information, and desired inputs to provide real-time results.

Automated Credit Underwriting

The traditional credit underwriting process typically takes between two to seven days to complete. Banks and credit providers must also coordinate with credit unions to verify customer information as part of the decision-making process. However,  AI is transforming credit facilitation by enhancing analysis capabilities and streamlining decision-making.

This tech also enables financial service platforms to process applications more efficiently—automating approximately 50% to 60% of decisions while maintaining thorough assessments. With advanced AI integration, financial institutions can improve operational efficiency, while making more informed lending decisions, and creating better customer experiences, as seen with services such as CreditFresh.

Efficient Data Extraction

Financial service providers have control over massive silos of customer business-related information, economic data demographic information, and credit data. Extracting and analyzing these data sets are time-consuming. While important to assimilating banking performance, traditional methods have proven inefficient the more data is collected. By leveraging AI-powered systems, banks can extract sets of data more efficiently, remove discrepancies, and better control their data management practices.

Customer and Account Risk Management

AI risk management allows banks to understand and uncover underlying risks related to accounts and customer portfolios. Banks can assess, monitor, and mitigate potential risks more effectively with AI. In turn, they can deliver more appropriate, tailored solutions to the customer and their banking needs. Digital risk management protects client portfolios, data, and financial firms against potential losses.

Customer Financial Analysis

Analyzing customer behavior is a continuous process. It should not be set aside once the customer has been onboarded. Keeping track of customer financial behavior through continuous analysis ensures that banks have up-to-date information regarding customer financial indicators. This minimizes the time and resources needed to approve clients for loans or credit. With AI-enabled financial analyses, banks can generate detailed reports and financial transactions, and deliver comprehensive analysis relating to customer account performance.

Accurate Fraud Detection

Fraud and malicious activities on customer accounts remain a concern for most major banks. Around 29% of U.S. bank customers had experienced some fraud-related transaction on their account during 12 months, according to a JD Power study. Reaction to rising threats and digital fraud presents banking leaders with the ability to utilize AI to help boost fraud detection and mitigate the emergence of secondary risks and “false positives.” According to one report, accurately detecting fraud and suspicious account activity is the primary driver behind increased AI investment in the banking industry.

Financial Predictive Analytics

Market conditions can change at any moment. Political uncertainty can affect economic sentiment. Things such as inflation, interest rates, and credit lending impact banking performance, stability, and bottom-line delivery. AI-powered tools can be deployed to help create predictive models based on different scenarios and economic conditions. These actions help to provide customers with better insights into possible changes they might experience under various economic circumstances. In turn, this helps them adjust their financial and portfolio strategies accordingly.

The Future Of Banking Is AI-Automated

Banking has become increasingly automated. This lends itself to industry-leading digital natives that have revolutionized the way customers interact with major financial institutions and how they manage their accounts. AI is standing at the center of this change. It enables banks to deliver more accurate financial predictions, safeguard client information, mitigate fraud and risks, and improve the customer experience by introducing an automated banking system that’s tailored to their needs.

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