The future of digital banking technology looks very promising. In the coming years, we can expect to see advanced technologies being integrated into digital banking platforms. These technologies will enable banks to offer more personalized and secure services to their customers, as well as to develop new products and services that better meet customer needs.
We can expect to see more collaboration between banks and FinTech startups, as both parties seek to leverage each other’s strengths to deliver better services to customers.
One trend that is expected to continue is the integration of Big Data into banking systems. This will allow banks to offer more personalized services and improve fraud detection.
The integration of Big Data into banking systems has the potential to transform the way banks operate and interact with their customers. By leveraging Big Data analytics, banks can gain deeper insights into customer behavior and preferences, and use this information to offer more personalized products and services. Big Data analytics can help banks identify and mitigate risks more effectively; develop and test new products and services more quickly and efficiently.
From what we can see, India and the world are embracing digital inclusion in increasing numbers, says Murali Brahmadesam, Razorpay’s CTO & Head of Engineering. The rapid emergence of neobanks is a testament to this fact, and according to reports, the digital banking space is poised to increase at a compound annual rate of 23.1% from 2022 to 2030. This indicates a paradigm shift that is characterised by innovation, especially in the mobile payments and digital wallet space.”
Murali goes on to note that keeping this growth trajectory in mind, it is important to note that Big Data plays a crucial role in gaining insights into customer behavior and managing risks in digital banking. Some of the key trends that we feel will shape the future of digital banking technology include increased personalisation, a seamless omnichannel experience, and extended reach to underbanked populations. Additionally, the integration of AI will be automating several tasks, thereby leading to improved customer service and the enablement of accurate financial predictions. Security measures, meanwhile, will focus on biometric authentication and encryption to address cybersecurity threats. Mobile functionality will continue to advance with features like mobile check deposits and voice-activated banking. Collaboration between banks and FinTech companies will be a step forward in revolutionising India’s financial landscape, expanding services to cater to diverse customer needs. The growing support from Indian regulatory bodies in creating a favourable environment and frameworks for banks and FinTech companies has also ensured the security, integrity, and stability of digital banking services in the country.
Managing compliance risks better with Big Data
Managing risks effectively in the banking, financial services, and insurance (BFSI) sector requires a comprehensive and integrated approach to risk management. In addition to identifying, assessing, mitigating, and monitoring risks, the organization should also cultivate a culture of risk management.
Dhiren Salian, Chief Financial Officer of ICICI Prudential Life Insurance, commented that data and predictive analytics have been extremely beneficial for the insurance sector. Such systems bring clarity and help make quick business decisions. By leveraging data analytics, we are better equipped to assess and mitigate compliance risks. It facilitates analysis of historical data, market trends and risk indicators thereby enabling us to detect patterns, anticipate risks and develop effective risk management strategies.
By leveraging Big Data, banks will be equipped with valuable insights, make real-time decisions, personalize marketing campaigns, assess risks, detect fraud, and optimize operations for improved efficiency and customer service.
Murali Brahmadesam states that the overarching BFSI space, like many other related industries, is incredibly complex and subject to regulatory developments and compliance. However, organizations can leverage Big Data to obtain insights and spot potential compliance risks and violations by analyzing vast amounts of data. It enables businesses to track and examine both structured and unstructured data, including financial transactions, regulatory filings, and market trends. Companies can, as a consequence, identify patterns and potential compliance violations through a comprehensive analysis. This helps them to reduce compliance issues before they escalate.
Heading Towards A Cashless Future
The world is increasingly moving towards a cashless future, with more and more people using digital payment methods such as credit cards, mobile payments, and online banking. There are several factors driving this trend, including the growing popularity of e-commerce, the increasing use of smartphones and other mobile devices, and the convenience and security of digital payment methods. Some of the benefits of a cashless future include:
- Improved security: Digital payment methods are generally more secure than cash, as they are less susceptible to theft and fraud.
- Increased convenience: Digital payment methods are often more convenient than cash, as they can be used to make payments from anywhere, at any time.
- Better record-keeping: Digital payment methods provide better record-keeping and tracking capabilities, making it easier to monitor and manage finances.
- Increased financial inclusion: Digital payment methods can help to increase financial inclusion by making it easier for people who are unbanked or underbanked to access financial services.
However, there are also some potential drawbacks to a cashless future, including concerns about data privacy and security, as well as the potential for increased economic inequality if certain groups are excluded from the digital economy. While a cashless future has the potential to deliver significant benefits, it is important to carefully consider the potential risks and challenges associated with this trend.
Murali adds that the shift towards a cashless future is becoming more evident as digital payments gain momentum. Mobile payments and digital wallets are options that are increasingly favoured, especially in developed economies. The Covid pandemic accelerated this trend, driving online shopping and contactless payments even further.
Banks are increasingly recognising the importance of Big Data analytics in understanding and serving their customers effectively. By leveraging Big Data, banks will be equipped with valuable insights, make real-time decisions, personalize marketing campaigns, assess risks, detect fraud, and optimize operations for improved efficiency and customer service.
Analyzing transaction data, for instance, enables banks to identify and address bottlenecks, enhancing efficiency and customer experience. With the increase in digital transactions, banks can gather data on consumer behavior and preferences to develop insights into customer needs and tailor their products and services accordingly, which can fuel product innovation and open up newer market segments. Big Data analytics empowers banks to make data-driven decisions swiftly, detect and prevent suspicious transactions, target personalized marketing efforts, assess risk accurately, and gain insights into market trends and customer sentiment. By optimizing operations through Big Data analytics, banks can streamline processes, reduce costs, and maintain a competitive edge in a rapid and consistently evolving ecosystem.
Building personalised solutions for customers
Providing personalized solutions to customers has become a key strategy for banks seeking to remain competitive and meet their evolving needs.
To build personalized solutions for customers, banks need to collect and analyze customer data, develop advanced analytics capabilities, and invest in technology infrastructure to support personalized product development and delivery.
According to Dhiren Salian, “We have been leveraging data science and technology to ensure that our customers are on course to achieve their long-term financial goals. A variety of ML models have been deployed to enable us to analyse multiple factors such as customer demographics, behaviour, preferences, risk profiles and household data. These insights allow us to develop insurance products, pricing models and marketing strategies. For instance, the deployment of advanced ML models has enabled the company to improve persistency across all cohorts.
Data analytics is aiding us in understanding customer challenges and has enabled us to offer a virtually paperless and hassle-free onboarding experience for certain pre-selected segments of customers.”
Future innovations in BFSI
Innovation in the BFSI sector is being driven by a combination of regulatory changes, technological advances, and changing customer preferences. To stay competitive, financial services firms need to invest in technology, talent, and partnerships to develop new products and services that meet the evolving needs of their customers.
Dhiren Comments, “We believe data science and analytics will continue to play a vital role in underwriting. Advanced predictive modelling techniques using deep learning and natural language processing combined with extensive data sources, such as electronic health records, wearables, and genetic information, will enable more accurate risk assessment and personalised and faster underwriting decisions.
Insurers will leverage customer data, including past interactions, preferences and feedback to provide customised recommendations, streamlined application processes, and faster claims settlement. Chatbots and virtual assistants powered by data analytics will play a significant role in delivering personalised customer support and guidance.”