Thank you so much for joining us in this interview series. Before we dive into our discussion our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path?
I have been fascinated with computers since I received my first one as a young teen in the ’90s. I thought it was the coolest thing and spent hours on it. That first computer was the catalyst that sparked my interest in computer programming and encouraged me to pursue education and a career in computer science.
When I was heading into university, I was lucky to be able to pick computer science as my undergraduate major as it was my top choice. In India, where I got my undergraduate degree, major selection was based on competitive ranking in a common entrance exam that all incoming undergraduates need to take.
Throughout my schooling and career, I have always had a goal in mind for where I want to be next. When I was in undergrad, I knew I wanted to pursue my master’s in computer science in the U.S. and eventually work for Microsoft, both of which I was able to accomplish, and this ultimately led to where I am today.
What do you think makes your company stand out? Can you share a story?
Socotra is a policy administration core, with modules for billing, rating, document generation, UI and more, that enables insurance carriers to build, launch and maintain any kind of personal (such as home, renters, auto) or commercial (such as commercial fleet, cyber, worker’s comp) insurance offerings. Socotra is the only insurance core platform built from consumer-grade cloud technology.
The insurance industry, as you know, has been around for centuries and the policy administration systems of the ’80s and ’90s, which were built on mainframes, are difficult and expensive to manage and tend to be extremely fragile. This led to the creation of improved systems in the early 2000’s by some of our current competitors who were still burdened by the limitations of on-premise setup. Socotra joined the evolution in 2014 because it was time for insurance software to grow up. We have since leap frogged competition by building a modern tech stack that is born in the cloud and designed for extreme product flexibility. Since we never had an on-premise set up, we do not have to deal with legacy tech debt which proved to be a significant competitive advantage. Almost all of our competitors spent years migrating their on-premise applications to the cloud which is a non-trivial investment. Since we completely bypassed the need for such a migration, we could focus on innovating faster and bringing a platform developed using proven cloud native software development best practices to insurance carriers.
You are a successful business leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
I would say that my most defining strengths are my optimism and stamina. Throughout my career, I have always told myself that I will not always be the smartest or the most talented person in the room, but I will definitely be the most persistent person. One of my favorite authors, Octavia E. Butler, put it very succinctly when she said, “The big talent is persistence.”
I learned early on to become very comfortable surrounding myself with people who are smarter than I am. Instead of getting intimidated, I let them inspire me to elevate my own performance and standards. I have learnt to be secure about my own capabilities, know the value that I bring to the table and use these opportunities to collaborate with other talented and motivated individuals to work towards the greater good.
Lastly, I believe I am very good at both giving and receiving constructive feedback and taking the time to put the feedback into practice. This is the number one trait I look for when I hire someone on my team, so it’s only right that I be good at it as well. Here’s a quote that resonates with me, “Average Players want to be left alone. Good players want to be coached. Great players want to be told the truth.” It’s not always comfortable to give or receive constructive feedback but in my opinion, it is the most essential trait to be a successful leader.
Let’s now move to the main point of our discussion about AI. Can you explain how AI is disrupting your industry? Is this disruption hurting or helping your bottom line?
There is a lot of promise for how AI can significantly improve the insurance industry. But first we need to cut through the hype and start discussing real and useful applications of AI and think through the end-to-end user experience that AI can enable. Here’s how I think about it. Anytime there is a human being making a decision, there is a set of data that they have consumed which they are using to make that decision. This is where the power of machines is undeniable. They can consume extremely large amounts of data which is beyond any human capability. As a result, any decision making point within a process becomes an opportunity for AI to augment the human-decision making process. Especially when it relates to financial decision making where there is zero room for error, AI is not at a place yet to replace the humans making these decisions. Its value lies in collecting, synthesizing and presenting information for the person making the decision in a way that helps them make better informed decisions.
We are all consumers of insurance policies, and with every policy there is a decision in terms of quoting and issuing policies and approving claim payments to a particular person with a unique set of attributes. There are many decision-making points throughout the lifecycle of an insurance policy that were historically made by humans. Those are the areas where AI can make the biggest impact. For example, detecting a fraudulent claim is possibly something a machine can do much better than a human being just because of the sheer amount of data that a machine can be trained on which would be impossible for a person to consume. In such scenarios, having AI make a recommendation that still gets reviewed by a person adds that additional level of safety to decision making.
AI has been a great addition to the insurance industry over the past several years. With the amount of data being collected still growing, AI makes it possible to sort through this information to enhance efficiency, provide proactive steps for insureds and enhance customer service. This includes everything from better predictive abilities to improved risk assessment and the ability to upsell or cross-sell products. AI is improving the experience of buying and using insurance.
Which specific AI technology has had the most significant impact on your industry?
With the recent excitement around Generative AI, the recent conversations tend to gravitate towards that being the focus; but it’s important to remember that AI has several distinct but related sub-fields that each are better suited to tackle different set of problems. Therefore, it is important to utilize and experiment with multiple technologies based on what problem or task we are setting out to solve. For example, GenAI is great for looking at past policies and summarizing the terms based on a customer’s history. Machine Learning (ML) which uses statistical methods and algorithms to make classifications or predictions can help with detecting payment or claims fraud. Natural Language Processing (NLP) which allows computers and humans to communicate using natural language is useful to automate customer care conversations.
Can you share a pivotal moment when you recognized the profound impact AI would have on your sector?
I have been working with AI since 2016 when I started with Amazon Alexa, and I always knew it would have a tremendous impact. At my previous company, we were using GPT models to build conversation AI tools and chatbot experiences which were used by large enterprises such as HSBC, Delta and Virgin Media, even before ChatGPT was introduced.
However, my disappointment lies in the overhype AI receives and I worry that it will eventually turn off a lot of people. The introduction of ChatGPT cannot be over-emphasized because it provided an incredibly easy to use interface to such a powerful model, making it accessible to a wide range of users when previously only a small section of the engineers were using the large language models. That accessibility led to the overhype, and the true usefulness of this technology has not matched the over exuberance that we have witnessed. We are in a cycle where people are very disillusioned about its usefulness.
If AI is implemented correctly, it could have a huge impact in aiding human decision making — whether for customer support, retail, insurance, or college admissions. AI has a big part to play to make those decisions more informed and make them more bias free. Whether we will be able to completely eliminate bias in AI is an active discussion. There is no doubt that some experiences that AI enables even today are nothing short of magical. My favorite AI tool that I have used till date is Gong which summarizing calls and provides insights. I use it daily and find that it makes information consumption very efficient.
How are you preparing your workforce for the integration of AI, and what skills do you believe will be most valuable in an AI-enhanced future?
It is fascinating to observe the debates that have risen surrounding AI and learn how people react so differently. We have some industry leaders who believe AI is key to eliminating scarcity while others fear that it will doom humanity. We are navigating through a very interesting phase in the tech industry and the verdict is not in yet.
My belief is that to better understand and prepare for AI adoption, more than a specific skillset, what is needed is a specific mindset. I have two recommendations for any tech team including mine. One is to personally use the technologies relevant for your role because there is no better way to sift through the hype and noise other than to see the technology or tools in action yourself. And the second is to identify opportunities to experiment with using AI to solve some problem at hand. Now the experiment could very well fail but the learnings from that is what will guide your next steps.
What are the biggest challenges in upskilling your workforce for an AI-centric future?
Amid the buzz around AI’s potential to revolutionize the insurance industry, many insurers find themselves grappling with its unfulfilled promises. Chatbots fall short of expectations and predictive models aren’t as accurate as hoped. To prepare for the AI-centric future, one of things that we obsess about at Socotra is to make data which is foundational for building any kind of AI-powered capability on top of our platform extremely accessible. With this, we will be ready to enable our customers whenever they are ready to adopt AI for their use cases.
When it comes to upskilling the workforce, AI will become the forcing function for people to upskill themselves. AI will support the development of our skills and push us to be more advanced. Having seen what models like ChatGPT produce, they are very good at solving straightforward coding problems; what they are not good at is troubleshooting. This might eliminate the role of a junior developer or somebody who is not very skilled at programming. Highly skilled developers will continue to be valuable because the advanced troubleshooting and optimization skills they possess cannot be mimicked by AI yet. Overall, AI will raise the productivity bar and the only skills that will become obsolete are the more basic-level skills.
What ethical considerations does AI introduce into your industry, and how are you tackling these concerns?
There are always drawbacks that have to be balanced with the limitless opportunities that new technology provides. As we have seen with the proliferation of AI available to the public, there is bias and prejudice associated with AI and training data.
AI is not ready for mass adoption because of this bias. It is also why there is still a need for human intervention, for an additional human review and judgment rather than blindly following the decisions recommended by AI.
In insurance, and in anything finance related, the decisions we make impact lives. For example, with the decision whether to issue a policy to a specific person or accept a claim, we are talking about somebody’s financial health. Even if the AI is right 99.9% of the time, the 0.01% of the time it is wrong has a big impact; the tolerance for a mistake is very low. The way to tackle this for now is to always have that human intervention before any of these key decisions.
What are your “Five Things You Need To Do, If AI Is Disrupting Your Industry”?
- Always be learning. The amount of evolution that occurs in technology daily is almost past comprehension. You don’t need to be up to date on all applications of new technology but pick a few that particularly interest you or that will be especially impactful upon your work and life. Also, stay abreast of the trends and soft skills that are related to new advances in technology. Continue to hone your problem-solving and creative aptitude to evolve along with the advancements in AI.
- Experiment and try something new. When ChatGPT first came out, there were a bunch of articles about what it can do and how advanced it was. After experimenting with it, I learned that while it is amazing to summarize text, it is not as useful to come up with original content. It is a helpful assistant, but the powers of ChatGPT are overblown. I recommend that when you hear about cool new AI technology, try it out first and experiment with its capabilities.
- It is important to not be victims of the gimmicky nature of these technologies. We can work together to dig deeper to find the usefulness. Having a solid framework in terms of how we are making product-related decisions and how we evaluate the usefulness of technologies is very important. We must revert back to our product management principles of identifying the customer, the value proposition, validating if it is something they are willing to use or pay for and determining if we have built in a feedback mechanism. We cannot assume that just because we are using AI that it will be received well.
- In our eagerness to build these AI features, we aren’t paying attention to how much it costs us. For example, while the operating costs of utilizing these AI technologies are coming down, they are still pretty steep. It is important to pay attention to how much it costs to develop and maintain AI features and whether the incoming revenue is worthwhile to be spending the investment.
- It is important to think of what we could be doing with the resources if we weren’t building these AI features. For example, could we have built a platform with more value in other ways that would have been a better investment of our time, resources and effort?
What are the most common misconceptions about AI within your industry, and how do you address them?
The one that I often encounter is that there is a lot of confusion between use of automation and AI, and people often conflate these two concepts. Automation performs repetitive tasks that follow predetermined rules. Automation systems are designed to run independently of human instruction, reducing manual intervention and increasing efficiency. However, automation systems can’t learn or adapt to changing environments or complex real-world situations. On the other hand, AI uses machine learning and advanced algorithms to learn from data, adapt and make decisions without explicit programming. AI systems are designed to identify the best course of action when faced with new information and scenarios. AI can simulate human processes like problem-solving and decision-making.
The one thing that I think the insurance industry, given its generally risk-averseness, got right about AI was its initial skeptical reaction. Insurance tech often lags behind the general technology industry, and it is doing the same when it comes to AI, which I don’t think is necessarily bad. This ‘wait and watch’ stance is beneficial because we are skipping through the hype cycle, letting it settle down and then acting on it. There are a lot of discussions on how AI can be used in insurance, and at Socotra we are optimizing and efficiently finding the right use cases that will deliver actual value to our customers.
Can you please give us your favorite “Life Lesson Quote”? Do you have a story about how that was relevant in your life?
My favorite life lesson quote is “Lessons in life will be repeated until they are learned.” When I was younger, and when something didn’t turn out the way I wanted it to more than once, I would ask myself, “why is this happening to me?” The first time I heard this quote, it clicked with me right away. It is a great reminder that a better question to ask yourself when failure or a challenging situation occurs more than once is, “What is the lesson I’m not learning here?” That reframing instantly makes you empowered and prevents you from falling into a victim mindset. Personally, it has helped me take charge and take action whenever I encounter any challenges.
Off-topic, but I’m curious. As someone steering the ship, what thoughts or concerns often keep you awake at night? How do those thoughts influence your daily decision-making process?
From a work perspective, my most important priority is to ensure that I have the right people in the right spots within my organization, and once I have the right people, my job is to ensure they feel fulfilled in their role. Most of the time, if something is keeping me up at night, it is likely about this topic.
When it comes to AI, the thing I worry about personally is the impact it will have on our children in terms of how it will, in combination with social media, be utilized in ways that can lead to bad things, for example, online bullying. AI has made it very easy to create deep fakes and spread misinformation in an amplified manner. At this point, there are no controls. There is much discussion about regulating AI, but this is a more immediate need. Children are one of the most vulnerable segments of our community; how do we protect them while we figure out the necessary guardrails or regulation?
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. 🙂
I am a big believer in the power of sponsorship to elevate talented people, especially into the executive ranks. I think as humans we naturally gravitate towards people who project confidence and sometimes as a result, people who are great at presenting themselves get promoted to a point of failure because they may not actually possess the skillset needed to succeed in that role. Alternately, people who are truly talented may not always have the swagger to earn an executive seat on their own. We can all agree that there is nothing more inspiring than reporting into a great leader and nothing more damaging than promoting an incompetent person into a leadership role. Right now, sponsorship happens on an ad-hoc basis, and whether an individual finds a sponsor that can help them get to the next level is a matter of pure luck. I often think about what it would look like if we formalized sponsorship more across the tech industry so we can curate and train the future set of leaders,and in doing so helped create a leadership culture that is more diverse and more talented than what we have today. The idea is not without its pitfalls but I wonder if this is one way to bring in more women into the executive ranks. I think it’s worth a shot.
How can our readers further follow you online?
Readers can connect with me on LinkedIn.
Thank you for the time you spent sharing these fantastic insights. We wish you only continued success in your great work!