Rupa Ramamurthy, Executive Vice President of Banking Operations at Teleperformance India, discusses how embracing data and analytics has turned into a business priority for the banking industry.
Over recent times, the financial services industry makes huge strides in adopting technology, like artificial intelligence (AI) and knowledge analytics, into its workflow. Actually, the IHS Markit's 'Artificial Intelligence in Banking' report estimates the worldwide AI market will reach $300 billion by 2030. This wide adoption of AI-driven automated solutions has been largely driven by the link between the strategic adoption of these solutions in the banking sector and also the results – strategic cost-savings, enhanced operational efficiency, and better engagement rates with customers and prospects.
Leveraging AI for the Front-Office
Industries across the board are undergoing an AI-enabled digital transformation, to provide a more seamless customer experience, fit for that new generation of hyper-connected consumers. A transfer of customer behaviour has redirected interest towards challenger companies, rendering legacy organisations less relevant in the current radically different, post-pandemic landscape. Many of the true in the case of financial services, where consumers have come to rely upon banks that allow smooth authentication, provide swift and easy transactions with 24/7 access to their funds, and drive personalised services. Banking is ahead of other industries, in respect of the deployment of AI to lift and automate the customer experience model, with 1 in 5 UK consumers now using challenger banks.
Certain customer-facing applying AI are on a staggering growth curve across banking operations, accelerated by the need for instant, online responses. For instance, chatbots – being used to support front office operatives and instantly manage and react to inbound customer queries – are now set to account for 85 per cent of all customer service interactions for financial institutions by 2021. Assisted intelligence solutions, for example click-to-chat technologies, make it possible for banks to streamline the end-to-end customer journey, inside a more cost-effective and consistent manner than can be done by a customer service agent.
By implementing analytical technologies, banking institutions can gain a deeper understanding of customer needs to devise customised interactions while offering. As data sources mount, banks can continuously improve resolution times without the need for staff intervention, and achieve 30 per cent higher sales conversion rates as a result.
Reduction in costs
In the back-office, AI-powered tools are used to complement the work of human agents by completing the tasks typically prone to human error – thereby minimising operating costs. Actually, it is expected that by 2023, $447 billion will be saved in costs, through the increased adoption of AI by banking institutions.
The automation of processes for example mortgage applications, account openings, and remittances services is becoming commonplace, as banks seek to drive down costs and increase productivity by limiting customer agent mistakes. Even in 2021, human error remains one of the leading causes of data breaches for financial institutions. As AI is adept at handling unstructured data, error rates could be significantly reduced, as well as the significant cost of resolving them.
The banking industry is extremely vulnerable to threats posed by fraudsters. Therefore, fraud detection and mitigation have grown to be a top priority for all banking institutions. AI now plays a number one role in decreasing rates of false positives, by reducing the number of missed alerts signalled by transaction monitoring systems – preventing fraudulent attempts and reducing payments fraud.
Through machine learning, AI has the capacity to interpret trend based-insights, making it possible to determine whether a transaction is fraudulent or not – in fact 63 per cent of monetary institutions say AI is capable of preventing fraud before it happens. Automated programmes are capable of carrying out security checks accurately, helping to keep customers' accounts and also the financial ecosystem safe. As digital identities become increasingly important, the function of banks is expanding to assist customers safely verify their identities with Multi-Factor Authentication (MFA).
Using Data for Good
Whilst personalised user experiences can make the customer feel their providers understand their needs, financial organisations should use data insights to create responsible recommendations. By tracking customer's spending and purchase history, AI can help customers make more informed and appropriate decisions, and also to not encourage people to take on debts they cannot repay.
The post-pandemic marketplace will continue to see AI flourish as a business differentiator. As a multi-faceted technology, AI has transformed traditional banking models and given way to a new breed of challenger banks, setting new standards for customer experience. Financial organisations are leaning on the technology to strengthen their algorithms, reduce the chances of fraud, and premeditate and address customer needs – using the ultimate business objective to cement their reputation like a reliable and resilient partner.