120 FEATURE efficiency, whilst collaborating better and delivering deeper and more meaningful customer engagements,” says Philippe Brissaud, product operations lead for Microsoft Cloud for Financial Services and industry AI. “For AI to play a role in these decisions, it’s essential that organisations use the technology responsibly and plan for unintended consequences. This is important for ensuring compliance as legislation evolves and maintaining trust with consumers.” With a whole variety of financial service providers to choose from – including big technology-based e-wallet services, fintech and insurtech companies, and neo-banks and traditional institutions – businesses need to invest in solutions to onboard and retain customers. “Azure AI-powered analytics and machine learning models are built into Microsoft Cloud for Financial Services,” says Brissaud. “This allows financial services organisations to proactively avoid and mitigate potential negative experiences that impact customer retention, and create intelligent, lower-effort ways of attracting new customers.” With AI, ML and analytics applied throughout the customer life cycle, businesses can identify trends, protect identities and assets, and provide personalised customer experiences. For example, large language models can recognise, summarise, translate, predict and generate text and other content based on knowledge gained from massive datasets. These help to build effective chatbots and virtual assistants like Chat GPT that can improve customer service. “Ironically, the use of AI-powered insights in this manner can also create more human-focused and personal service experiences,” says Karassik. “AI allows employees to devote time to other activities, with less attention needed to solve customer problems.” AI can also be used to provide personalised, real-time offers. The Royal Bank of Canada is doing precisely this through a piloted Virtual Clean Room – a privacy-preserving, multi-party, data-sharing platform built on Microsoft Azure Confidential Computing. What’s more, AI technology can prevent attempts of fraud, money laundering and cyberattacks through its predictive qualities. “AI optimises market and operational risk management to deliver risk insights, comply with regulatory requirements, secure identities and manage sensitive data against threats,” says Karassik. “Scalable computers and analytics can power modelling, insight and regulatory reporting as a result of this.” Other AI-powered tools can help to secure user identities and control access, identify and protect sensitive data and govern critical data and communications channels, as well as protect against external cybersecurity threats and insider risks. It comes as no surprise then, that analysts including IDC FutureScape, predict that 10 per cent of attempted identity fraud will be reduced thanks to more sophisticated AI and ML technologies in open banking sources. A future in data “We are already seeing financial institutions realise significant gains by deriving more insights from their data than ever before,” says Brissaud. “Fintechs have demonstrated the power of data by incorporating insights and improved analytics from social media platforms and other alternative sources. Commercial banks are quickly closing this gap and using AI to innovate well beyond them.” For example, HDFC Bank partnered with Microsoft in January 2023 to leverage Azure, Power Platform and Microsoft 365 to enhance its data-sharing capabilities, modernise and migrate is application portfolio, and provide a secure digital workplace for its employees. HDFC Bank will use AI and ML capabilities to process data from multiple sources and encourage employee collaboration. “Banks must seize the opportunity to make their way through the mountains of data that is largely underutilised,” says Brissaud. Data in the privileged relationship between banks and their clients must be managed carefully, but within that context there are incredible insights and value waiting to be derived and applied.” “ Banks must seize the opportunity to make their way through the mountains of data that is largely underutilised” PHILIPPE BRISSAUD, MICROSOFT
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