Financial institutions that invested in advanced data management systems witnessed improvements in various factors such as quality of the performance, customer experience, and ultimately increase in profits. To know more about the significance of AI and data analytics in the NBFC space, Rashi Aditi Ghosh of Elets News Network (ENN) had a conversation with Samir Mohanty, Chief Operating Officer & Chief Technology Officer, Avanse Financial Services.
How are NBFCs redefining themselves with the help of technology in recent times?
In the last couple of years, the entire world witnessed rapid digitalisation across sectors to cope with various never-seen-before situations. This has brought about a massive change in the fundamentals of how businesses operate in recent times. In order to stay competent and relevant, many financial institutions including NBFCs, have embraced technology and introduced innovative digital capabilities to further strengthen the processes.
As a new-age and digitally-agile NBFC, Avanse Financial Services has also embraced digitalisation and automation to make efficient credit and operational decisions and to provide hyper-personalised services to our young aspirants. We offer a seamless omnichannel experience to customers. Our presence across offline and online platforms ensures deeper market visibility by connecting with primary, secondary, and tertiary audiences.
Technologies such as Artificial Intelligence (AI), Advanced Analytics, Application Programming Interface (API), Robotic Process Automation (RPA), Big Data, Chatbots, and Natural Language Processing (NLP) have transformed NBFCs to a great extent. Increased technological capabilities have enabled the sector to operate in a more cost-efficient manner. Furthermore, it has also helped smoothen multiple internal processes, thereby reducing the TAT, ultimately benefiting the customers.
How beneficial is Advanced Analytics in BFSI institutions today?
Advanced Analytics is an emerging technique to discover insights using data and preparing recommendations. These analytical tools provide business intelligence and a deep dive into the data. Advanced analytics use classification algorithms and forecasting tools to enable effective decision-making. Through the structural and targeted use of advanced analytics, financial institutions can achieve important results in defining risk, identifying new growth opportunities, and even developing personalised ways to interact with their customers.
Financial institutions that invested in advanced data management systems witnessed improvements in various factors such as quality of the performance, customer experience, and ultimately increase in profits. We, at Avanse Financial Services, believe that adopting technology across business processes is the most crucial step for an essential service provider. Leveraging advanced analytics has enabled us to adopt insight-driven lending, paving the way for building a sustained profitable enterprise by adopting cost-efficient digital tools.
The world of banking has encountered unprecedented change over the past few years. Do you agree that data and its management have now become a significant part of financial institutions?
The banking and financial services industry heavily relies on data and data analytics in multifarious ways. This has been further proved by the widespread adoption of big data in the BFSI sector, along with AI across the operational spectrum. By enabling access to analytics in real-time for organisations, authorising swifter action on derived insights via intelligence, gives the NBFCs a competitive edge in the industry. The biggest driver of change in the financial space is data management, as analytics and related solutions automatically enable superior data management, helping organisations structure, streamline, and leverage data for gaining insights.
This increasing dependence on technology and automation also brings with it the responsibility of protecting sensitive data. Hence, we believe that NBFCs must invest in adopting robust data security measures. Notably, many financial institutions employ data loss prevention (DLP) technologies, the latest firewalls and other multi-layered security to prevent data breaches. Investing resources in these tools will not only secure the sensitive data but also help streamline and manage it efficiently as well as effectively.
At Avanse, we have deployed robust data security strategies to protect the company’s information assets against cybercriminal activities. They are also guarded against insider threats and human error, which remains among the leading causes of data breaches today. The organisation has deployed tools and technologies that enhance its visibility wherever critical data resides and how it is used, apply protections like encryption, data masking, and redaction of sensitive files, and automated reporting to streamline audits adhering to regulatory requirements.
How is Artificial Intelligence helping NBFCs in handling their dynamically changing customer base?
The financial industry has witnessed a paradigm shift in the business model due to digitalisation, which has led organisations to focus on creating customised solutions for their customer base. NBFCs strive to offer tailor-made solutions right from customer acquisition to the collections stage using Artificial Intelligence (AI) and Machine Learning (ML). Digital tools such as Data Analytics, Data Mining, Robotic Process Automation (RPA), Virtual Assistants, and Natural Language Processing (NLP) are employed by new-age and customer-centric financial organisations to provide an enhanced user experience.
The predictive analysis provides insights into customers’ buying patterns, social behaviour, financial profiles, and historical data. This leads to drawing accurate inferences to provide suitable solutions. Furthermore, contactless processes such as video KYC allow customers to complete the necessary procedure from the comfort of their homes, offering them a smooth and hassle-free journey right from the start of the engagement.
Avanse Financial Services has adopted a hybrid model of doing business, which comprises best practices of traditional lenders and new-age Fintech players across the value chain with a focus on risk management and asset quality. We call it the PHYGITAL Operating Model. As a part of this model, we have incorporated and excelled in the process of amalgamation of alternate data and traditional information to create hyper- personalised offerings and to onboard the right credit. We, at Avanse, take a segment- led approach that evaluates a student’s future employability potential rather than depending on the co-borrower’s financial background. We analyse their academics, entrance test scores, the pedigree of the college/university, the course selection and more. We also evaluate alternate data on social chatter and verify third-party research material. This analytical approach involves complex AI and ML tools, which further help us underwrite the right risk for the organisation.
We have also implemented an AI-ML based platform that uses data to build perspective models that provide early warnings on customers who are most likely to default in terms of EMI payments. This AI & ML based collection platform is an initiative towards a bounce prediction model under risk analytics. It has been created to analyse and identify the accounts that might enter the Over Due (OD) stage. This analysis is conducted with the help of artificial intelligence and machine learning analytics. After the vulnerable accounts are identified, they are transferred to the next level. At this level, we reach out to them for reminders at regular intervals.
What major changes in terms of analytics, data, and automation do you see in the next few years?
A 2022 survey by PWC and FICCI revealed that India’s banking sector is leading in implementing and adopting all emerging AI use cases. Technological integration is a crucial prospect for financial institutions to be future- ready and stay relevant to customers as hyper- personalisation has become the new standard. It can revolutionise the financial space by increasing productivity while enhancing customer value and business economics.
In the future, AI-based anomaly detection engines will not only be more intelligent and inclusive but will also be independent of manual training on conventional data models. With this development, significant opportunities are also presented by AI in fields like payments, onboarding, and fraud detection and prevention.
AI and Application Programming Interface (API) for integrated services will be imperative to foster co-innovation and build ecosystems for the further growth of the sector. Moreover, with the aid of data science, data management, and batch processing, strategically integrated cloud computing services will enable financial institutions to employ resources in a very flexible and effective manner.
In India, the market for AI is burgeoning. While most financial players are removing data silos, more effort is required to make data processing and the functional side of gaining insights scalable and useful from a business viewpoint.
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