How Analytics has helped HDFC Securities Increase its Overall Revenue by 40%

The profit from analytics initiatives have been immense for HDFC Securities. 2 years ago, the percentage of transactions in the digital method where 60% of the total transactions using different channels. Presently, it has increased to 83%. Furthermore, the overall revenue has noticed a spurt of 40%, claims Nandkishore Purohit, Head – Digital Strategy and Analytics, HDFC Securities.
Our data analytics blueprint aligns with the overall business strategy and business goals which could be broadly categorized as top-line development, cost reduction as well as risk and compliance management. We are using data analytics in our daily functions for example acquisition, activation and constant meaningful engagement with our clients. This can help us in keeping up with all the changing buying patterns of the customers also as dealing with the business dynamicity of the capital markets. For instance, the item recommendation to a temporary investor and an old buyer is going to be different. I won’t engage in a temporary buyer with an SIP and similarly, an options trading item won’t a long term investor.
We run a great deal of propensity models and determine probably the best investment blend for the consumer on the basis of the investment philosophy and what we are able to offer. HDFC Securities is an Amazon of financial providers. There are a variety of investment choices that we are able to find for the clients and offer him the most effective fit.
We maintain the data integrity at the primary platform and have made several intelligence levels over it with the usage of BI application. A level of analytics is made over both the Demat & materialized investment platform. A complementary partnership system has been developed with the fin-tech companies to be able to get some other associated consumer data. After this, different analytical models are run to produce consumer segmentation.
From an institutional brokerage viewpoint, we do algorithm trading for 4 major clients and also have a committed analytical platform for delivering market insights to the customers.
We have a team of 45 full-time data analysts with us, drawing inferences coming from several customer data sets – whether it is behavioral, consumption or perhaps in some cases – predictive. Apart from this, we’ve interns from different data science institutes, both international and national. Data gathering and indexing are automated by utilizing the BI tool sitting in addition to the analytics layer. 60% of the team is engaged in creating propensity models. The rest 40% works with the stakeholders to supply them inputs and insights.
The team operates in closed-loop with the relevant teams offered by HDFC Bank because the clients are predominantly from the bank. The propensity models are refreshed and cross-examined with the teams in the bank.
As the head of analytics, I decide the proper propensity model to be applied for a specific business problem. To bringing efficacy in utilizing analytics is by correlating data with understanding customer behavior. The industry teams come up with their requirements of the items to be offered as well as the analytics team suggests on which items to be offered to which set of customers.
The company is in discussions with different third party vendors for understanding of use cases and having several POCs. Using the fallout evaluation model, HDFC Securities is carrying out a POC with buyers that were of higher relationship worth but have lowered the engagement in the last several years. They’re showing early symptoms of attrition to the competition. This POC has been working after the previous 1 and a half month and the company have been in a position to win back again 14% of the targeted customers.
In an additional PoC being run for more than 6 weeks now, non-profitable acquisition has been cut down by 30%. This is a component of the attempts to finetune the consumer acquisition system. Using analytics, the sales ratio in the area of advertising has doubled in the previous year.