Financial institutions, from global conglomerates to local credit unions, are increasingly harnessing the power of automated data-driven processes and artificial intelligence (AI) to create groundbreaking products and services that redefine customer experiences and reshape their industry.
The growth of data and digitization has given financial institutions new opportunities to utilize information. From transaction records to customer profiles, financial services have always been built upon data. Now data analytics combined with AI and machine learning algorithms are allowing firms to extract meaningful insights from vast datasets, providing a deeper understanding of customer behavior, market trends and risk management.
With market size projected to reach $698.48 billion by 2030 globally, fintech technologies hold the key to business growth and will strengthen the entire financial value chain. To stay competitive, every future-facing firm must become a technology-driven entity and forecast a new digital finance architecture to move toward more strategic, real-time financial activities.
Traditional banks providing core banking solutions are striving to reposition themselves as technology platform firms with a banking license. HCLTech is investing in FinTechs, APIs, application modernization and cognitive computing to facilitate this transition.
In the banking sector, 72% of customers believe personalization is “highly important” in today’s financial landscape. BCG estimates that banks can achieve as much as $300 million in revenue growth by personalizing their customer interactions for every $100 billion they have in assets.
HCLTech’s Senior Vice President of Digital Process Operations, Sugata Gupta spoke about AI in BFSI in a blog, saying: “In a very limited time, AI has become an integral part of the business processes for the Financial Service industry, innovating and evolving with time with minimal manual intervention. AI financial institutions are expected to be able to optimally leverage both machine and human capabilities, driving cost and operational efficiencies and delivering tailored solutions.”
Financial institutions are integrating sources of data to innovate the services and products they deliver to their clients. HCLTech’s Fintech and Co-innovation lab in London has over 150 experts collaborating on cutting-edge technologies to drive future innovations in banking. The financial services sector is undergoing a seismic shift, propelled by data-driven processes and the integration of AI and emerging technologies with focus on cybersecurity, hyper-personalization and other future-forward approaches like composable banking.
Cybersecurity in Banking: According to IBM and the Ponemon Institute, the average cost of a 2021 data breach in the financial sector is $5.72 million. Modern financial firms need an all-encompassing, dynamic, and resilient security solution. Automated data-driven processes are helping financial institutions stay one step ahead of fraudsters. Machine learning algorithms can identify unusual patterns of behavior and transactions, enabling banks to detect and prevent fraudulent activities in real-time.
HCLTech offers a portfolio of dynamic cybersecurity services that applies AI and predictive analytics to provide a proactive and integrated response to threats and improve security stature significantly.
“We’re now seeing these approaches like decision trees, neural networks and GBM models being applied in anti-money laundering to predict “productive events.” Some of the advancements in linguistic analysis and contextual text analytics are proving helpful to automate tasks,” said David Stewart, Banking Industry Director for SAS Fraud and Security Intelligence.
Hyper-personalization: Much like ATMs in the 1960s and mobile banking in the 2010s, AI and hyper-personalization are redefining the 2020s, ushering in the next era in banking and separating the haves from the have-nots. With AI, organizations can access huge data sources to build customer profiles to aid in implementing hyper-personalization.
According to a HCLTech’s Whitepaper on AI in Financial Services, hyper-personalization will revolutionize call centers by effortlessly routing calls to the right agent and providing access to the relevant customer data in real-time. Not only does AI provide customers with a seamless experience, but it significantly reduces operating costs while uncovering new revenue opportunities.
In addition to customer-facing processes, AI supports backend banking processes by safeguarding, storing and de-identifying PII, as well as improving regulatory compliance. Some other roles that AI plays in improving the customer experience include quality assurance, response time, identity protection and up-selling and cross-selling.,/p>
Composable banking: Composable banking is emerging as a new approach that aligns speed, agility and innovation to stay ahead in the competitive financial market. Composable architecture aims to treat change as a constant by continuously innovating technology platforms with the latest advancements and building new products while delivering hyper-personalized customer journeys.
There are no one-size-fits-all vendor lock-ins, risk of replacing monolithic core banking systems, or expensive engagements. “Composable banking allows customers freedom of choice,” says Sriraman Ganesan, Executive Vice President, Product Engineering, Temenos.
HCLTech and Temenos have collaborated to help clients deliver the most open and secure cloud-native platform for composing, extending or deploying banking capabilities at scale. This partnership will enable banks and other financial institutions to progressively modernize at scale, accelerate digital transformation, support transition to the cloud and deliver omnichannel customer experience.
Emerging trends in banking
Open banking: Regulatory changes like the European Union's Payment Services Directive 2 (PSD2) are driving the adoption of open banking practices. This encourages financial institutions to share customer data with authorized third-party providers, fostering collaboration and innovation.
Chatbots and virtual assistants: AI-driven chatbots are transforming customer service in banking. These virtual assistants can handle routine inquiries, assist with account management, and even provide financial advice. Bank of America's "Erica" and Capital One's "Eno" are AI-powered examples that simplify customer interactions.
ChatGPT: Recently, the impact of ChatGPT technology on banking, financial services and insurance (BFSI) has been significant with its expertise in handling complex financial questions and providing reliable and accurate responses. Unlike traditional chatbots, which use rules to respond to questions and requests, ChatGPT uses a deep neural network and natural language processing (NLP) to generate responses based on its learning from conversations it’s had with humans.
Blockchain and cryptocurrency: Blockchain technology has the potential to revolutionize various aspects of financial services, including secure and transparent transactions. Cryptocurrencies like Bitcoin are also challenging traditional notions of currency and payment systems.
Personalized financial services: Banks are utilizing AI algorithms to analyze individual spending patterns and financial habits. This allows them to offer tailor-made financial advice and solutions that address customers' unique needs. JPMorgan Chase's "You Invest" platform, which offers personalized investment recommendations based on customer behavior, is a prime example of this trend.
The strategic use of data analytics, machine learning and AI is allowing financial institutions to not only streamline operations but also offer innovative products and services that cater to customer needs. As these trends continue to evolve, the financial services landscape is bound to witness further disruption, ultimately benefiting both the industry and its customers.