How AI is changing the future of the financial industry
Artificial intelligence (AI) is perhaps the biggest bet in the financial world today. Adopting smart solutions can give financial institutions and banks a sharp advantage over their competitors by helping them optimise their offerings in this ever-changing, unpredictable world.
Today, AI has gone beyond its experimental stage and is being implemented in real-world use cases. Banks are using AI bots to onboard clients and perform automated risk analyses of borrowers. They are using computer vision, pattern matching, and deep learning to identify process inefficiencies. AI-based anti-money laundering solutions are helping them prevent fraud, among several other use cases.
Banks and financial institutions are combining AI with other emerging technologies to drive game-changing transformation. For instance, Infosys helped an Australian-based bank leverage data analytics, blockchain, Internet of Things, and AI models to help predict highly accurate demand, consumption, and price for trading companies that were presented through an intuitive easy-to-read dashboard to streamline their business trading and procurement process.
Addressing the limitations of AI
However, AI is not without its limitations. An AI, no matter how powerful and efficient, is ultimately the reflection of its creator. It inherits our biases that hobble it and prevent it from performing to its full capability. Even the most advanced AI may incorrectly reject an application if a borrower belongs to a particular race, community, or an immigrant family.
It is thus crucial to build a trust factor within AI models by ensuring that the data used is humongous, diverse, and updated frequently. Using additional data from non-traditional sources such as social media or creating algorithms that are blind to characteristics such as gender while also checking bias against those same characteristics is necessary yet challenging. Using techniques such as Explainable AI and Ethical AI brings transparency regarding how AI takes a decision and allows AI models to be updated to eliminate such biases, making it reliable, safe, and empathetic.
AI trends in BFSI
As digital transactions, app usage, payment modes, and transaction volumes are on the rise, AI will play a critical role in enhancing customer service and increasing the safety and security of customers’ wealth. A good example is UBS’ Daniel chatbot, which answers queries on market trends for investors.
Similarly, risk mitigation is a space where AI should thrive. For instance, a large European bank has successfully implemented AML and KYC analysis for client onboarding processes. They achieved nearly 50% automation as their AI models help segment entities, form cluster groups, and apply rules for Suspicious Activity Report (SAR).
At a time, when personalisation is key to customer engagement and driving revenue, AI can augment data usage to create hyper-personalised services. DBS, for example, has updated its mobile app offering with more than 100 automatic personalised insights for their end customers, powered by AI models.
To drive revenue, RoboAdvisors can be deployed across various banking functions: recommending investment products, providing nudges to users, sending out investment alerts, and tracking and projecting spending versus earning, among others.
As with every other industry, BFSI was also severely impacted due to the pandemic. Only those banks with a strong digital presence and robust customer care centres could continue business with minimal disruption. Business leaders are now acting swiftly to adopt AI technologies to augment business decisions. The Bank of England survey reflects this sentiment as it predicts an increase in AI usage to meet future operational demands in the new normal of a Covid-19 word. However, this intent is constrained by the risk management and governance frameworks that have not evolved as swiftly as AI has.
Nations and governments are waking up to the fact that AI is fast becoming indispensable to the way we live and conduct business and they are drawing guidelines around it. The EU, for instance, has already published the Artificial Intelligence (AI) Act and is expected to finalise the rules by 2023-24. It needs to be seen whether these rules would accelerate AI innovation or put brakes on it.
In any case, as Deloitte observes, banks and other organisations in the EU should not wait and watch. Instead, they must assess their AI strategy and the effort needed for its implementation because there’s no doubt that AI is changing our future even as we speak. And the growth and competitiveness of the financial services industry will depend on how fast they adopt AI to enhance customer delight and provide the edge over their competitors.