I see new technologies as catalysts for unlocking our human potential further: Sikhin Tanu Shaw, CIO, Can Fin Homes Ltd

In this exclusive interview with Express Computer, Sikhin Tanu Shaw, Chief Information Officer of Can Fin Homes, explores various aspects of technology trends and their impact on the industry. The interview delves into recent digital and tech trends reshaping the landscape, particularly focusing on the rise of generative AI and its application in streamlining processes within the housing finance sector. He also discusses the traction of AI in the BFSI industry, emphasising its role in enhancing customer interactions, automating document processing, and facilitating personalised financial services.

Can you share some of the recent important digital or tech trends that you see in the industry and their impact?

Recent tech trends in the industry are reshaping the landscape at a rapid pace, impacting organisations across sectors and departments. One of the most significant developments in tech is the rise of generative AI and artificial intelligence, which are revolutionising various industries. Companies are now focused on understanding how to leverage these advancements to drive better value for their customers and streamline repetitive tasks.

In the housing finance industry, there are numerous repetitive tasks involved in loan processing, including document collection, underwriting and risk assessment. Predictive models powered by AI can play a crucial role in automating these tasks, thereby improving efficiency and accuracy.

From a security standpoint, the landscape has evolved, with attacks becoming increasingly sophisticated. Companies must remain vigilant and proactive in implementing solutions like Security Operations Center (SOC), Security Information and Event Management (SIEM), Security Orchestration, Automation and response (SOAR), User and Entity Behavior Analytics (UEBA) to gain comprehensive visibility into their systems and networks. Vulnerability Assessment and Penetration Testing (VAPT) has also become a necessity and hygiene practice, with regulatory bodies like the Reserve Bank of India (RBI) mandating its frequency based on application criticality.

Overall, companies are navigating these tech challenges by embracing innovative solutions and adhering to regulatory requirements to ensure robust cybersecurity measures are in place.

What is the traction of AI in your industry, including housing finance and BFSI as a whole?

AI traction is a significant phenomenon across various industries, including BFSI and housing finance sector. I’ll give you a couple of examples. First off, we have chatbots, which are leveraging AI to engage with users on websites, particularly in addressing loan inquiries. These chatbots, powered by large language models, interact with users, understanding their loan requirements, and offering tailored solutions in real-time. It’s a remarkable application of AI in enhancing customer interactions.

Another noteworthy area is automated document processing. In today’s lending landscape, acquiring loans necessitates gathering extensive data and documents. AI-driven virtual assistants or models streamline this process by autonomously collecting and parsing through documents, providing key insights to branch managers or loan processors swiftly and efficiently. It’s a game-changer in simplifying document management and processing.

Then there’s personalised financial services, a realm where AI excels. Just as we experience personalised product recommendations on platforms like Amazon or Flipkart, AI models in the finance industry leverage customer behaviour analytics to offer tailored recommendations and services. Whether it’s suggesting relevant loan products or providing personalised financial advice, AI is at the forefront of enhancing customer experiences and satisfaction.

Lastly, let’s touch upon prediction and risk assessment, a critical domain where AI’s analytical prowess shines. By analysing vast datasets from diverse sources and past customer behaviours, AI empowers housing finance companies and stakeholders to assess risk more accurately. Whether it’s predicting default probabilities or evaluating creditworthiness, AI models offer invaluable insights derived from analysing data from various platforms, including social media and online banking activities. This comprehensive approach, coupled with AI’s ability to analyse bank statements and other relevant datasets, provides a holistic view of a customer’s risk profile, aiding in more informed decision-making processes.

Isn’t analysing every spending transaction potentially an encroachment on privacy, particularly if it involves monitoring where individuals are spending their money?

When any company analyses data, the first step is to obtain customer consent. For instance, when applying for a loan, your credit score is typically checked with your permission. Similarly, when accessing bank statements or ITR certificates, customers are asked to provide these documents themselves. This emphasis on consent underscores the importance of privacy. When the customer provides required data, it becomes the responsibility of the company to ensure its privacy and security. This is where regulations like the Digital Personal Data Protection (DPDP) Act, 2023, come into play. According to these regulations, all digital data collected by companies must remain within India’s borders and strict privacy measures must be upheld. Data should only be used for its intended purpose and once it’s no longer needed, it should be securely destroyed. It’s imperative for companies to uphold these standards to maintain customer trust and data integrity.

How accurate do you believe AI is in using risk assessment, considering its integration with data?

Indeed, AI models undergo frequent updates, leading to fluctuations in their accuracy over time. The reliability of these models hinges heavily on the quality of the underlying dataset, emphasising the critical role of data management and data quality. Proper data management practices, including change management and data governance, serve as foundational elements for AI implementation. The efficacy of AI in delivering results or making decisions is intricately tied to the quality and training of the underlying data.

As these models mature, I remain optimistic about the trajectory of this technology. With each passing day, AI continues to evolve, and I anticipate further advancements in the days ahead. A robust dataset is instrumental in this maturation process, facilitating iterative improvements and enhancing the accuracy of AI outcomes.

Also, it’s essential to address potential biases within AI models. Conducting AI model audits can shed light on the extent of bias present in the model. By regularly assessing and auditing AI models, organisations can mitigate biases that may arise from repeated exposure to certain types of data. While there may not be regulatory mandates dictating the frequency of these audits, adopting a self-regulatory approach can prove beneficial. Regular audits enable organisations to identify inaccuracies and biases, empowering them to refine and optimise their AI models for improved performance and fairness.

Do you believe AI and GenAI, including chatbots, have had a positive or negative impact on the workforce?

When new technologies and applications like ChatGPT emerge, there’s often a concern about their impact on the workforce. However, I view it differently. I see new technologies as catalysts for unlocking our human potential further. They provide us with greater efficiency and time to excel in what we do best. Rather than viewing them as a threat, I see them as collaborators, augmenting our abilities and enabling us to unleash our potential to its fullest extent. This isn’t a negative impact; it’s an empowering opportunity for employees and users to leverage technology to enhance their capabilities.

Human beings possess unique cognitive abilities that no AI can replicate. We excel in strategic decision-making, leadership and analytical analysis, areas where our cognitive strengths shine. While AI models are indeed trained by humans and data, the proliferation of AI is largely due to advancements in computing power, cloud technology and the availability of vast datasets. These advancements have enabled us to train models more effectively, allowing AI to generate outputs that benefit both customers and employees alike. Therefore, rather than fearing AI, we should embrace it as a tool that complements and enhances our human capabilities.

How do you view the need for continuous skill enhancement and adaptation to new technologies, particularly in the context of the evolution of AI and other future advancements?

When we look back at our own educational journey, we realise that the subjects we studied twenty years ago aren’t necessarily the same as what we’re studying now. Similarly, what we learn today isn’t necessarily what we’ll apply tomorrow. This constant evolution underscores the need for ongoing learning and upskilling to remain relevant, both as individuals and within our respective industries.

New technologies emerge constantly, and they’re not here to replace jobs but to augment them. It’s all about adapting, upskilling, and reskilling to stay ahead of the curve.

How do you perceive the balance between AI’s role in preventing and causing risks, especially as AI matures over time?

The positive applications of AI models across various industries are undeniable. However, it’s crucial to acknowledge that cybercriminals and organised crime groups are also leveraging these AI models for nefarious activities, creating a significantly larger and more powerful industry. Finding a balance becomes imperative, and this is where organisational cyber defence strategies come into play.

I often emphasise this point to my colleagues and industry peers during discussions: “You’re secure until you get hacked.” Indeed, there seems to be no end to the need for investment in security. We must assess our organisation’s risk appetite and determine how deeply we can invest in security measures. However, it’s crucial to understand that there’s no definitive end point in the pursuit of security; it’s an ongoing effort and concern for all of us.

If you ask any CIO, CTO or CISO, they will express genuine concern about the negative applications of AI which is being used by threat vectors and attackers. This is where government regulations can play a significant role in curbing the misuse of AI and help addressing cybercrimes. However, it is essential to follow a structured approach to security, starting with Vulnerability Assessment and Penetration Testing (VAPT), diligent patching of applications and infrastructure, implementing Endpoint Detection and Response (EDR) solutions etc. Establishing an AI powered Security Operations Center (SOC) equipped with a robust Network Operations Center (NOC), Security Information and Event Management (SIEM) solution, Security Orchestration Automation and Response (SOAR) tools, User and Entity Behaviour Analytics (UEBA) and Data Loss Prevention (DLP) measures can help detect anomalies in the system and user behaviour.

As an industry veteran, what technological innovations do you believe will shape the future and contribute to advancements in innovation and security within the industry?

Absolutely, the landscape of industries and businesses is swiftly gearing up for the future with emerging technologies. This forward momentum isn’t limited to any specific sector but encompasses all industries. So, if you’re wondering how to prepare for the future, my advice is to embrace upcoming technologies as swiftly as possible as long as it is beneficial for your business, ideally through a proof of concept (POC) approach. It’s crucial to evaluate how a technology aligns with your business objectives and how it can benefit your operations before diving in. Once you’ve conducted a POC and observed tangible positive results, it’s a green light to proceed and fully adopt the technology. However, if the outcomes aren’t as promising, it’s wise to adopt a “fail fast” approach and pivot accordingly.

Looking ahead, several technologies are poised to reshape the future. Artificial Intelligence (AI) and quantum computing stand out as game-changers, with significant developments underway in the Western world as well as in India. The advancement of GPUs and chipset giants like NVIDIA and Sony etc. signals a forthcoming transformation. Additionally, cloud computing has already become ubiquitous, offering unparalleled scalability, adaptability, and rapid deployment capabilities. However, prudent management of cloud spending is essential to prevent costs from spiralling out of control.

On the infrastructure front, cloud technologies continue to lead the way, providing organisations with swift provisioning and deployment capabilities. Unlike traditional on-premises setups, which can take weeks to set up and configure, cloud environments allow for near-instantaneous virtual machine provisioning, significantly expediting deployment processes.

In terms of applications, newer technologies like AI-generated content are on the rise, promising enhanced efficiency and innovation. Moreover, cybersecurity remains paramount, with organisations continually adapting to evolving threats and bolstering their defences with advanced techniques like AI-driven security solutions.

Across industries, organisations are swiftly embracing these technological advancements, with the financial services sector often leading the charge due to its criticality and stringent regulations. As we move forward, this trend of rapid adoption and adaptation to emerging technologies is expected to persist across all sectors, ensuring continued growth and innovation.

AI-Driven AutomationBFSICybersecurityGenerative AI
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