Ram Devanarayanan, Head of Business Consulting for Infosys Finacle Europe
Introduction
In recent years, the banking industry has faced numerous challenges, including rising consumer expectations, digital competition, technological advancements, and regulatory pressures. To stay relevant, banks have embraced digital transformation, with 57% of bank leaders agreeing that it is among their top strategic priorities. However, the current economic downturn and the need for cost-cutting measures have further emphasised the importance of customer engagement and resource optimisation. In this article, we will take a look at how artificial intelligence (AI) can revolutionise the banking sector, enable personalised experiences, improve customer engagement, and drive financial well-being. While the benefits are substantial, we also need to understand the challenges associated with implementing AI solutions effectively.
Enhancing Customer Engagement with AI
The use of data and AI technologies empowers banks to gain valuable customer insights and deliver personalised experiences. Machine learning (ML) can analyse vast amounts of data, providing banks with actionable insights that drive contextual interactions and enable human-like conversations. A prime example of this is NatWest’s virtual assistant, Cora, which can, among other things, assist customers by helping them reschedule loan and credit card payments.
The acquisition of comprehensive data is also vital for effective customer engagement. Banks need to consolidate information from various customer relationships and locations, enabling a holistic understanding of preferences and anticipating future needs. By analysing income, expenditure patterns, age, and financial assets and liabilities, banks can offer advice on managing spending habits. This data-driven approach ensures banks deliver the right services at the right time, minimising the risk of customers seeking alternatives elsewhere.
Risk Management and Fraud Detection
Banks can leverage AI in risk management and fraud detection. By analysing vast amounts of data, including transactional patterns, market trends, and historical risk data, AI algorithms can identify potential risks and fraudulent activities with greater accuracy and efficiency. This enables banks to proactively mitigate risks, protect customer assets, and ensure compliance with regulatory requirements. A study by Nvidia has shown that this is the top area of investment for financial services professionals, with 31% highlighting it as a use case for their company.
AI also enhances operational efficiency in areas like anti-money laundering (AML) compliance. By automating the process of detecting suspicious transactions and patterns, AI can significantly reduce the time and effort required for AML investigations. This all allows banks to enhance their compliance measures, streamline operations, and allocate resources more effectively.
Overcoming Challenges and Maximising Benefits
While the potential benefits of AI in banking are significant, implementation challenges must be acknowledged. Costs associated with data collection and the installation of the infrastructure can be substantial. Banks need to carefully consider their business goals, customer base, and technology readiness to make informed choices. On top of this, banks must prioritise robust security measures and adhere to strict data protection regulations to safeguard customer information. This is particularly pertinent with the Bank of England’s recent finding that cyberattacks are the biggest risk to the UK financial system. Building transparency and clear communication around data usage and customer consent is essential to maintain trust in AI-driven banking services.
Conclusion
AI has the power to revolutionise the banking industry by transforming customer engagement, personalisation, and improve risk management. By leveraging data analytics and AI technologies, banks can deliver highly tailored experiences, proactive recommendations, and improved financial management tools. However, successful implementation requires a long-term strategic approach, careful consideration of costs, and a commitment to data security and privacy. As the banking landscape evolves, embracing AI can empower banks to stay competitive, drive customer satisfaction, and navigate the ever-changing demands of the digital era.
