EarlySalary is an innovative lending platform who brings together new credit scoring systems for superior customer profiling and, change the way loans in India are taken. The online platform is backed by a strong leadership team that aims to build a new credit scoring platform that combines traditional credit scoring with new social and online scoring technology-linked risk assessment concepts, to deliver a revolutionary new business set to change the lending market in India.
Balakrishnan Narayanan, Head of Analytics at EarlySalary is a seasoned Analytics professional with over a decade of extensive experience in diverse industries including banking, financial services, consulting and ITES. He is responsible for building analytical capabilities within the risk, marketing and customer analytics space. He has designed and implemented an AI based loan underwriting platform on traditional and non-traditional data, that helps identify customer behaviour and their risk pattern. He has been a part of leading financial institutions like Standard Chartered Bank, GE Capital and ICICI Bank, therein contributing to the field of advanced analytics and strategic initiatives. His prior experience involved consulting engagements with organizations across geographies including Europe and UK, where he was instrumental in driving innovation for Fortune 500 companies. He holds a Master’s Degree in Business Analytics from UCD Michael Smurfit Graduate Business School in Dublin, Ireland.
- How did you decide to be in analytics field?
Banking industry was one of the early adopters of analytics as they had quantum of structured data. I was at the right place to taste the initial success. What intrigued me were the sheer size of customer data that was available and the task of application at the mammoth scale. As I started going deeper into this subject, I was convinced that this is what I wanted to do.
- What are the unique challenges you face when hiring entry level talent in analytics?
One of the major challenges in the field of analytics is the Demand and Supply gap. The market for sure is more of a candidate driven market. Though there is a huge demand for experienced professionals, companies are struggling to hire freshers straight out of colleges. One of the reasons is that our education system is not up to date with the current market realities and the latest global developments. Candidates who have received training in data science or have some knowledge about it have a very high expectation from the job without actually being ready for the same. Diversity is another big challenge in this industry which needs to be mitigated soon.
- How do you overcome these?
Pay attention to the company’s culture fit and look for people who are smarter than you and can challenge the status quo for the benefit of all. Having the right job descriptions and finding candidates who fit the role is the next step. One needs to be clear on the kind of skills you are looking for from the candidates. The organizations should have the right sourcing strategy and more importantly, a candidate management strategy as some might take your offer and not join. A faster recruitment process engine with shorter lead time is a must. One also needs to be ready to invest in the candidate.
- Any specific initiatives within the organization to help bridge skill gaps?
An organization is successful only if they invest in building their people. Learning needs to be made a habit and there should be a collaborative spirit of knowledge sharing. Three important areas we focus on would be: Building technical capabilities, Sustainable process to enable re-skilling & cross skilling, Building the right set of behaviors aligned to the values and culture
- Is EarlySalary focused more on analytics services or products?
Yes, it’s a collaborative team effort among a solid product management team, technology team and analytics team to bring a great solution to the customer’s problem.
- Is the organization focused on big data and predictive analytics?
Analytics has been a key differentiator for us and there has been a focus on it right from day one when we started. The entire management has been supportive to invest in the right people and skills for the future.
- What are the skills anticipated in your company for hiring in future?
Some of the key behaviors that we look for are risk-taking ability, startup culture fit, ownership mindset and the ability to drive change. On the technical side, it depends on the role for which we are hiring. We look for a mix of three key areas; technical capabilities which include proficiency in tools like python for building models, SQL & other big data skills for extracting data and tableau for visualization. If it is for a data scientist role then proficiency in statistics is a must, along with the other technical skills. Domain knowledge is critical for someone to work on analytics solution. Freshers can acquire this only on the job.
- Hiring time frame?
Somewhere between one to three months. The sooner it is the better for us.
- How do you currently hire talent at the entry level?
We use a mix of sources like Campus, Referral, Community collaborations and other job portals. The highest number of our new hires comes from LinkedIn and referrals.
- Do you believe that non engineers can perform well in analytics?
Absolutely. I am an MBA in finance who moved into analytics without an engineering background. You should be determined, committed to upgrade yourself and be willing to adapt to changes in an ever changing and dynamic field like analytics. Patience is key, which unfortunately is missing in most millennials today. You need to torture the data long enough for it to confess and give away the patterns that you are interested in.