True essence of digital transformation lies in leveraging AI and ML models with the right datasets: Jyothirlatha B, CTO, Godrej Capital
Express Computer recently had an insightful conversation with Jyothirlatha B, CTO, Godrej Capital. This interview delves into the progress made by Godrej Capital in its transformative journey, particularly in the technology domain. She shares the company’s strategic focus on digital lending, the impact of the COVID-19 pandemic on their operations, and the three-year plan aimed at innovation and differentiation in the market. The discussion also covers key elements of digital transformation in the financial sector, success metrics for digital initiatives, and the challenges and roadblocks faced during their technology-driven evolution.
As the tech business leader, what progress have you made on your goals that were set 3 years ago, when the company was launched?
I appreciate your insightful question. In 2019, our cohesive team, including the Management Committee (MC), embarked on a transformative journey. Comprising five members initially, our strategic focus centred on the launch of Godrej Housing Finance, primarily emphasising the Home Loan (HL) product. During our deliberations, the primary consideration was whether to adopt existing strategies or chart our distinctive course. Our discussions revolved around the core themes of innovation and creating differentiators in the market. We were keen on exploring ways to stand out and offer unique value propositions rather than simply following established norms.
Our journey began with a firm belief in adopting a unique approach. However, the landscape shifted significantly during our strategic discussions due to the unforeseen onset of the COVID-19 pandemic. The events of 2020, marked by a complete lockdown and associated challenges, prompted a reevaluation of our operations beyond traditional business norms. This shift led us toward a more digital lending approach, conceptualising innovative products such as designed EMIs and touch-free loans—essentially zero-touch loans.
Our primary objective was to deliver the Home Loan (HL) product in a manner distinct from conventional practices, especially considering the prevalent paper-oriented processes in other organisations. We aspired to transform the entire home loan process into a fully digitalised experience with minimal customer interaction.
To address environmental demands and leverage our diverse background encompassing lending, business, technology, and processes, we formulated a comprehensive three-year plan. The initial year focused on launching HL, establishing a robust foundation for housing finance. In the second year, our goal was to expand offerings to different products, adopting a platform approach to avoid complex multi-system scenarios. The second year also emphasised data, while the third year involved a deeper exploration of AI and ML technologies.
Reflecting on the three-year plan, we have largely achieved our goals, making strategic adjustments based on market trends. Importantly, our technology stack strategy remained consistent. Moving forward, our focus is on driving further innovations, enhancing product adoption, streamlining internal processes, boosting employee productivity, and aligning with new regulatory guidelines, particularly those emphasising security as outlined in recent RBI circulars.
What should be the key elements of a financial sector organisation’s digital transformation story?
When we talk about banks, the focus often centres around the money withdrawal process, highlighting the anytime banking concept, where physical money is no longer a necessity. UPI has made financial transactions incredibly easy, and this convenience should extend to lending processes for consumers. Digital transformation, in my view, involves making the lending process easily accessible to consumers. The readily available digital data, facilitated by initiatives like India Stack, PSO, CAN, and Aadhar, enhances the underwriting process, ensuring a better understanding of the customer.
The evolving landscape of digital data availability, when harnessed effectively, can simplify the lending process. Although it might take some time, constraints such as understanding the customer in a more comprehensive way are being addressed. Alternate data sources, though available, need to be authenticated to ensure reliability in the underwriting process. The true essence of digital transformation lies in leveraging AI and ML models with the right datasets, enabling enhanced underwriting capabilities.
However, it’s crucial to recognise that while technology transformation might be relatively straightforward, the true challenge lies in the adoption and utilisation of these technological advancements by people within the organisation. Digital transformation goes beyond mere technology implementation; it involves a cultural shift where individuals embrace and fully utilise the implemented systems. The success of digital transformation is contingent on the organisation’s ability to ensure widespread adoption and utilisation of the technology rather than just its implementation.
What are the key drivers and success metrics that fuel your overall digital initiatives?
In the initial phase of our digital transformation journey, there were challenges, notably related to numbers and working constraints, especially during the COVID-19 pandemic. The ground-level feedback was initially lacking, serving as a valuable lesson for us. It became clear that our digital transformation efforts were not flawless and, in hindsight, improvements could have been made in certain processes.
The realisation prompted a retrospective analysis, acknowledging that the inclusion of end-user feedback from the beginning would have yielded better results. Integrating end-user perspectives early on helps reduce rework and ensures more accurate outcomes from the outset, contributing to the overall success of the initiative.
Our success was also attributed to the investment of time in understanding the development needs rather than rushing into the process without a clear plan. Taking the time to brainstorm, formulate effective strategies, and carefully select appropriate platforms has proven to be beneficial for our organisation. This approach enhances the chances of successful implementation, making the entire digital transformation process more efficient. I trust this provides a comprehensive response to your question.
Following the three-year milestone, based on the learnings and challenges, how do you plan to scale up digital capabilities for enhanced operational efficiency and stakeholder acceptance?
Operational efficiency has been a fundamental aspect of our strategy since the beginning. Even in the initial stages and on a smaller scale, we had a well-defined plan and set targets, emphasising the importance of efficiency in our approach. It’s crucial to highlight that our strategic approach extends beyond the current year.
Our operations are built on a cloud-native foundation, as we originated in the cloud environment. This cloud-based architecture ensures auto-scalability, eliminating the need for manual interventions, especially during critical operational periods such as month-end processes. This approach reflects our commitment to harnessing technology to streamline operations and enhance overall efficiency.
The adoption of cloud technology is a result of our innovative team’s efforts, involving experimentation with various proofs of concept (POCs). These experiments have proven that integrating cloud technology adds substantial value to our training processes and overall operational framework. This ongoing commitment to innovation and technology adoption positions us to maintain a swift pace and ensures our readiness for future challenges. I hope this provides a comprehensive response to your inquiry.
Beyond the GenAI perspective and training models, where do you see practical use cases for technology penetration in your industry?
Regarding GenAI, its use case is presently in an exploratory phase due to the novelty of the technology, making it challenging to fully rely on it at this moment. There are inherent limitations with GenAI, notably in the timeliness of the provided data, and external factors like the impending DPDP bill introduce constraints, especially concerning API utilisation.
Given these considerations, this year’s focus will involve careful experimentation, particularly in non-PCI and non-critical data-related aspects. A specific area of exploration is the training module, coupled with insights integrated into our underwriting process. It’s essential to distinguish between insights and automated decision-making; the former empowers credit managers to make more informed and unbiased decisions, contributing to the refinement of AI-ML models.
While GenAI shows promise and represents an opportunity for potential value, our current stance is one of cautious optimism. We are navigating this space with a “let’s see what it can be” mindset, acknowledging the evolving nature of AI technologies and their potential impact on our operations. I hope this provides clarity on our approach to GenAI and its integration into our processes.
Aside from underwriting processes and training models, are there other areas where you are experimenting with technology, or is it still in the evaluation stage?
In various domains, we are currently in the evaluation phase, aligning with the concurrent development of DPDP policies. This evaluation is crucial, given the paramount importance of secure information handling within the realm of PDP. Determining what information can be included and what should be excluded is a part of this ongoing evaluation process.
In this context, the approach that has shown considerable success and reliability is the one I previously outlined. It has proven to be a secure and effective method for managing information within the framework of data protection and privacy policies. As we navigate these considerations, our goal is to establish practices that not only adhere to regulatory requirements but also prioritise the security and privacy of sensitive data. I trust this provides clarity on our current stance and approach in this evolving landscape.
Do you advocate for adopting a multi-cloud strategy for various workloads including your organisation? If so, what are the specific benefits that make this strategy advantageous for your operations?
Our approach involves adopting a multi-cloud strategy, which offers flexibility and risk mitigation by leveraging multiple cloud providers or a combination of cloud and co-located data centres. Even within a single cloud provider, having redundancy across regions can be considered as part of our resilience strategy. This approach is designed to reduce dependence on a single provider and enhance overall system reliability.
Understanding the nuances of our workloads and server usage is crucial to effective cost management. Cloud costs can escalate if not monitored diligently, making it essential to align infrastructure choices with specific workload requirements. In scenarios where clarity is lacking or testing is a priority, co-location provides a viable option.
Our recent developments, including the circular you mentioned regarding cloud setup, are actively being monitored for potential impact on our strategy. We are attuned to industry shifts and regulatory updates to ensure our cloud infrastructure aligns seamlessly with emerging trends. This proactive approach positions us to adapt swiftly to changes in the cloud landscape, enhancing our organisational resilience and strategic positioning.
Can you share the measures you’ve implemented to safeguard overall data security and privacy in the digital roadmap you’ve created for your organisation?
Well before the implementation of the DPDP bill, our organisation proactively addressed the sensitivity of customer information. In the initial year of our operations, we meticulously formulated a robust data strategy, encompassing clear data classifications and guidelines on handling privacy data. This strategy delineates methods for masking sensitive information, implements access controls, and identifies specific groups authorised to send and receive Personally Identifiable Information (PII) data.
Within our architectural framework, departmental data has already been segregated, ensuring a structured and controlled data environment. Approximately 70 to 80% of the DPDP bill aligns with our existing data strategy. A comprehensive review of the bill highlights a substantial focus on privacy and data control measures, areas that our strategy preempts and covers comprehensively.
During the cloud setup phase, we took meticulous care to ensure data sovereignty within our geographical boundaries, preventing data from crossing international borders. Access controls and data classifications have been ingrained in our practices from the outset. Any data or file transmission undergoes classification, clearly indicating whether it is internal or external.
The DPDP bill accentuates the importance of consent management, including customer consent and the role of a data officer. While anticipating the bill becoming a circular, we acknowledge the need to address specific gaps related to consent management. Nonetheless, regarding data practices, our pre-established plans have been effectively implemented, positioning us well for compliance with evolving data protection regulations.
In your overall journey so far, have you encountered any roadblocks or challenges from a technology perspective? If so, have you identified areas for improvement, and what measures are being taken to address and mitigate those issues?
In our organisation, we recognise the significance of both learning and unlearning as crucial components of our growth journey. Given the diverse backgrounds of our team members, it is imperative to acknowledge that processes that were effective in different contexts may not necessarily align with the current stage and objectives of our organisation. Hence, unlearning those outdated approaches becomes essential. Concurrently, we prioritise learning what is most suitable for the present state of the organisation to foster continuous improvement.
Productivity in our organisation is increasingly driven by Key Performance Indicators (KPIs). We have consciously shifted our focus towards KPI-driven initiatives, providing us with a structured framework to concentrate on our objectives. This approach facilitates the evaluation of our actions, ensuring they align with the desired outcomes and contribute significantly to achieving our Target Performance Areas (TPAs).
The emphasis on productivity being KPI-driven has become more pronounced in our discussions and decision-making processes. This strategic shift towards KPI-driven practices has proven beneficial in maintaining a clear focus on our goals and assessing the effectiveness of the steps we take in achieving our TPAs. It serves as a guiding framework that aligns individual efforts with the broader organisational objectives, fostering a more streamlined and goal-oriented approach.
Are you exploring partnerships, especially in the AI/ML domain to accelerate your processes and enhance future data analysis capabilities?
As discussed earlier, minimising vendor dependency is a deliberate strategy for us. We place a strong emphasis on utilising internal teams to handle various aspects of our operations, ensuring a greater degree of control and independence.
We boast a substantial analytics team complemented by an extensive in-house technology team. This internal team is not only responsible for the development of models but also comprises skilled data analysts. We take pride in our self-sufficiency, and our current strength lies in the proficiency of our internal team, which is fully capable of independently developing sophisticated models.
While we acknowledge the value of seeking external expertise to fast-track processes when necessary, our internal team’s capabilities are such that they can autonomously undertake the development of models. This underscores our commitment to fostering a robust and self-reliant internal environment, aligning with our strategy to minimise vendor dependency.
Are you exploring partnerships with Fintech firms for collaborative solutions, similar to the trend observed with major financial institutions?
We have abstained from external collaborations, specifically for system development, with the exception of engaging certain fintechs that offer services such as bank system analysis. Our organisation does not pursue co-creation ventures for system development; instead, we pride ourselves on independently creating and developing our systems in-house.
Our operational model aligns with a Software-as-a-Service (SaaS) approach. While we maintain self-sufficiency in our system development, we have strategically integrated with fintech partners for various functionalities. These integrations cover diverse areas such as lead management, statement analysis, and crime checks. These collaborations are instrumental in augmenting our capabilities, allowing us to leverage specialised services from fintech providers. Despite these partnerships, we remain self-sustained in our core system development endeavours.
What’s the update on your digital platform, Nirmaan, which aims to provide MSMEs with an inclusive opportunity to grow their business?
Currently, we are deeply engaged in the analysis of analytics data, with a specific emphasis on the feedback received for various pages, following the recent overhaul of our Nirmaan site. This initiative has been spearheaded internally, underlining our commitment to articulating the inherent benefits to our valued customers.
Within the Nirmaan initiative, there have been noteworthy technological advancements. A robust feedback cycle has been instituted, ensuring continuous improvements based on the insights garnered. Simultaneously, we are actively integrating new elements to enhance the overall initiative. Notably, the collaborative network of partners associated with Nirmaan is expanding steadily, rendering it a dynamic and evolving program. This growth underscores our commitment to the continuous enhancement and adaptability of the Nirmaan initiative.
