Why data-driven solutions are critical for banks’ survival
Why data-driven solutions are critical for banks’ survival
Thursday February 10 2022 By FAUSTINE NGILA
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- By deploying Natural Language Processing (NLP), a subset of AI, banks could reach every customer in the language they best understand, even if it is vernacular.
- AI-driven analytics can give a reasonably clear picture of future expectations and help banks stay prepared, especially by analysing data from external global factors.
The application of Artificial Intelligence (AI) in the provision of financial services matters now more than ever, and banks of the future will have to keep improving their systems if they are to adapt to the emerging dynamics of customer preferences in the future.
This, according to fintech experts who spoke during the inaugural Leap 2022 global tech summit in Riyadh, Saudi Arabia, could make the difference in profitability in the global banking sector.
“The combination of intelligent propositions and personalised experiences will set an AI bank apart from traditional incumbents,” said Rana Gujral, chief executive officer of Behavioral Signals, an enterprise software company that unravels behavioural signals from speech data.
Noting that banks across the world are struggling to connect with their customers in the current era of the Fourth Industrial Revolution, Mr Gujral stressed the need for personalising banking experience using AI.
An AI-based loan and credit system can look into the behaviour and patterns of customers with limited credit history to determine their creditworthiness. Also, the system sends warnings to banks about specific behaviours that may increase the chances of default.
With a major industry shift occurring and the existing practices such as optimising for the first available customer care agent based on routing becoming increasingly ineffective, banks were urged to focus not only on what customers say but also how they say it and “the tonal variations” in their speeches.
“Banks need to use AI to understand human emotions, deduce speaking styles, assess human behaviours and predict interval signals generated from the tone of voices,” Mr Gujrat said
By deploying Natural Language Processing (NLP), a subset of AI, banks could reach every customer in the language they best understand, even if it is vernacular, further boosting financial inclusion in countries with huge unbanked or underbanked populations.
Petr Stransky, founder and chief executive of British dispute recovery platform iCEIBA, told financial institutions to do more in leading the way in implementing innovations towards the future of digital finance.
“We are entering an era where everything can be priced and traded in real-time. This will change how we think and act about finance,” he said.
Banks, according to him, will need to use frontier technologies to segregate most functions and gatekeepers for different types of assets and transactions, as customers now jump into Decentralised Finance (DeFi) products such as Non-Fungible Tokens (NFTs).
To achieve this, banks were asked to use modern software in analysing real-time data on every single detail in their banking operations while observing market trends and the changing customer preferences occasioned by the Covid-19 pandemic.
AI-driven analytics can give a reasonably clear picture of future expectations and help banks stay prepared, especially by analysing data from external global factors such as currency fluctuations, natural disasters or political unrest which have serious impacts on banking and financial industries.
Chief executive of fintech research company Burnmark, Devie Mohan underscored the need for insurance companies to make data-driven predictions to remain in profitable business and rethink their business models.
“Insurers will need to deliver a better digital experience for both panic buyers and long-term customers,” she said.
If banks fail to adapt fast to AI and mobile banking, Ms Mohan warned, bigtech companies could soon take control of the global banking sector, with Google Pay, Apple Pay, Facebook Pay, WhatsApp Pay, Amazon Pay and Alipay all unleashing the power of Big Data analytics to create successful payment across their social networks.
“Big technology companies may become quasi banks,” she said.
IBM’s global head of strategy in banking and finance Anthony Lipp says financial services are now so digital that it’s easy to embed them in other offers, and it’s easy to enhance those offers in markets outside of banking.
“So the model that banks need to build to be competitive is one of hyper-efficiency — very low cost, extreme scale. That means financial institutions have to come up with alternatives to expensive existing processes.”
AI-based systems can help banks reduce costs by increasing productivity and making decisions based on information unfathomable to a human agent. Also, intelligent algorithms are able to spot anomalies and fraudulent information in a matter of seconds.
Banks were also urged to deploy robotic process automation algorithms to increase operational efficiency and accuracy whilst boosting transaction speed.
A report by Business Insider suggests that nearly 80 percent of banks are aware of the potential benefits that AI presents to their sector.
Another report suggests that by 2023, banks are projected to save Sh45 trillion by using AI apps, an indicator that the banking and finance sector is majorly relying on AI to improve efficiency, service, productivity and digital Return on Investment.
The Leap 2022 event has brought together tech leaders from across the world, making it a tech information-sharing ecosystem by global players in 5G, fintech, AI, blockchain, Virtual Reality, robotics, green energy, cloud management, edtech, medtech, autonomous mobility and 4D printing.