Transforming Finance: The Impact and Value of AI in Financial Services
From Experimentation to Implementation: How AI is Proving Its Worth in Financial Services
For financial institutions, the path to recovery from the pandemic signifies a shift from tentative experiments with artificial intelligence (AI) and machine learning (ML) to their extensive adoption. This crisis has pushed financial organizations to address customer needs round-the-clock. As a result, many of these organizations are evolving at an accelerated pace while ensuring their core operations run seamlessly. This urgency has ignited interest in AI and ML solutions, which minimize manual intervention, bolster security, and allocate more time for innovation. By shortening the duration between idea generation and value delivery, AI and ML promise long-term strategic benefits for organizations.
Today’s banks are being transformed into digitally-driven enterprises similar to tech giants, prioritizing customer-centric capabilities. So, how can banks and financial institutions leverage AI effectively, and what are the key use cases in practice?
Benefits Across the Business
Many financial services firms had already begun implementing AI and ML prior to the pandemic. However, challenges in pinpointing which key functions could benefit most from AI often hindered expected returns from the technology. This is likely to change in the near future, as the increased deployment of AI and ML becomes central to the economic recovery from COVID-19, highlighting areas where AI can effectively contribute—such as credit decision-making, fraud prevention, and enhancing customer experiences with seamless, 24/7 interactions.
Specific Financial Services Processes Enhanced by AI
- Document Processing through Intelligent Automation: Intelligent and robotic process automation refine various functions, enhancing overall efficiency while speeding up core financial processes, ultimately leading to significant cost savings. A noteworthy area gaining traction is e-KYC (electronic know-your-customer), a remote, paperless process that diminishes bureaucratic costs associated with crucial client verification protocols.
- Efficient and Thorough Customer Support: Virtual assistants address customer needs with minimal human input. This straightforward approach boosts productivity by reducing time spent on routine customer inquiries, allowing teams to concentrate on long-term projects that foster innovation. Chatbots, commonly seen in e-commerce, are increasingly finding their place in the financial sector, as seen with JP Morgan’s use of these bots to streamline back-office tasks and enhance customer support.
- Risk Management Analytics: Evaluating creditworthiness essentially relies on assessing the likelihood that an individual or business will repay a loan. Understanding default probabilities is crucial to the risk management processes at lending firms.
Assessing financial data accurately presents challenges, as some individuals and organizations may misrepresent their ability to repay loans. To address this issue, companies like Lenddo and ZestFinance are leveraging AI for risk assessment and to evaluate creditworthiness. Credit bureaus, such as Equifax, are also employing AI and machine learning alongside advanced data analytics to analyze alternative sources in risk evaluation, thus gaining valuable customer insights.
Previously, lenders relied on a limited set of data, primarily annual salaries and credit scores, to gauge creditworthiness. However, with the advancements in AI, organizations can now analyze an individual’s entire digital financial profile, enhancing their capability to predict the likelihood of default. This comprehensive analysis of both traditional and alternative data is particularly beneficial for individuals who lack standard loan or credit histories.
The Time to Adopt is Now
The interaction dynamics between businesses and clients have shifted permanently this year, and the finance industry is no exception. Prior to the urgency imposed by the pandemic, financial institutions were experimenting with AI and machine learning on a small scale, often treating it as a mere compliance measure. This year, however, has seen an urgent shift towards genuine innovation and resilience within the sector.
Financial organizations are now recognizing the significant benefits of AI, including enhanced efficiency in back-office operations and noticeable improvements in customer engagement. The transformation that was just beginning before Covid-19 has since accelerated and is rapidly becoming the new standard. Moreover, financial entities that embrace AI now and focus on its complete implementation will likely be in the best position to enjoy its future benefits.
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