Improve cross-selling capabilities

More than 70% of HDFC Bank's credit card portfolio is now from cross-selling

As one of India’s largest banking institutions, HDFC Bank has embraced sophisticated information technology to pursue its expansion from corporate banking to become a world-class provider of wholesale and retail financial services. SAS provides a broad range of analytics to help HDFC Bank make credit decisions, enhance its cross-sell and up-sell marketing, and comply with strict regulations.

In the mid-1990s, the Housing Development Finance Corporation Limited (HDFC) was among the first to receive an "in principle" approval from the Reserve Bank of India (RBI) to establish a private bank, part of the liberalization of the banking industry. In just a few short years, Mumbai-based HDFC Bank has expanded from its commercial banking roots to the broader world of retail financial services, with a footprint stretching across the country and encompassing a broad range of offerings.

Thanks to an unswerving commitment to a world-class technology infrastructure, more than 18 million customers can visit more than 1,700 networked branches in hundreds of cities, use thousands of ATMs, and take advantage of online and telephone banking. What's more, those IT investments and deployments have evolved into the foundation for even greater value than streamlined transaction processing. Drawing on their massive volumes of data – managed in large data warehouses – HDFC Bank is using sophisticated solutions from SAS to generate an entirely new class of analysis and insights relating to customer relationship management, regulatory compliance, credit assessments and more.

Achieving the 360-degree view

According to Munish Mittal, Executive Vice President and Head of the Technology Solutions Group, HDFC Bank views cross-selling to existing customers as a crucial growth strategy. "One of the most important functions of our data warehouse is to achieve a consolidated view of the relationship our bank has with each customer," he said. "We want a 360-degree view that shows us the credit card account, fixed-deposits, asset accounts – the totality of their relationship – so that we can segment our most profitable customers to offer more attractive products, services and pricing, and create an overall better relationship with them."

SAS, combined with the bank's CRM solution, helps HDFC Bank model its customer data and assign propensity to buy, spend and (for credit and debit cards) activate. SAS helped the bank target sales communications to its customers thereby reducing the number of calls each customer receives. Additionally, the highest-performing, highest-margin strata of customers - the "Imperia" customers – receive an almost concierge-like experience with aggressive, attractive pricing and multiple cross-selling offers. "When we know that the customer is high in the value chain," Mittal said, "we know that there's a stronger level of profitability in that relationship. So we reach a greater number of higher-margin customers at far lower cost."

The correct product for cross-sales promotion is identified using the customer profile, life stage and behavioral dynamics. The predictive power of this analysis encouraged the bank to extend the use of SAS to inbound channels; thereby further reducing the number of calls from the bank without compromising meaningful interactions with the customer.

Today, more than 70 percent of HDFC Bank's credit card portfolio is a result of cross-sales to existing customers of standard liability products, such as savings and salary accounts.

We want to study the behavior of the customer because it can help us develop more accurate, predictive forecasts for our business. Those predictive models not only prevent losses by spotting likely defaults, they can also predict propensity to buy or propensity to convert.

Munish Mittal
Executive Vice President and Head of the Technology Solutions Group

Improving the compliance posture

Anti-money laundering regulation creates strict burdens for banking institutions around the world – and India is no exception. HDFC Bank uses SAS as part of a stringent and focused program for monitoring and identifying potentially fraudulent transactions. For instance, SAS helps identify suspicious activity such as layering or moving money to multiple accounts, finding large single-day cash deposits, opening a number of accounts in a short period of time or sudden activity in long-dormant accounts.

"The Know Your Customer [KYC] aspect of banking is very important in anti-money laundering regulations," explained Mittal. "As we on-board the customer, we run that customer through certain profiles and cross-check against a list of banned individuals. Identifying a customer and matching him against good and bad lists requires very clean data. SAS helps us do some enrichment and data cleansing to strengthen our KYC compliance."

According to V. Chakrapani, Executive Vice President, Audit & Compliance at HDFC Bank, the comprehensiveness of SAS' scenario modeling has made monitoring of transactions "from an anti-money laundering perspective, qualitatively rich and dependable, and has enabled the bank to file qualitative suspicious transaction reports to the Financial Intelligence Unit."

Lowering credit risk

One of the biggest challenges for any retail bank is administering a sound credit-underwriting policy. HDFC Bank makes thousands of credit decisions every day. "We have hundreds of credit officers working on originating and approving loans," said Mittal. "We process more than 1,000 applications an hour every day. Many of these scenarios require instant loan approval. For instance, a customer at a two-wheeler dealer wants to take his purchase with him immediately. We combine our in-house lending, loan origination and scoring solutions with SAS technology to provide our customers with the luxury of instant financing decisions."

Using SAS, HDFC Bank interfaces to a credit-bureau report, validates the customer's identity and runs the application through various models – such as propensity to default. The result is that HDFC Bank delivers an answer to the requestor within minutes, online. "SAS delivers an exceptional level of performance and reliability in these scenarios," Mittal said.

In the absence of a unique identification, such as a Social Security number, SAS helps identify group and customer level debt exposure. This benefits the bank in many ways:

  • The credit officer can view customer level debt exposure across all other loans within the bank.
  • The bank can reject customers who have a derogatory repayment in other loans within the bank. On an average, every month the bank rejects up to 2 percent of applicants because of an existing derogatory repayment. Assuming a probability of default and loss given default of 50 percent, HDFC Bank is saving nearly 1 percent of its total annual disbursement from potential credit losses.
  • In accordance with regulatory guidelines, SAS helps identify standard exposures of defaulted customers so the bank can initiate preventive measures and provisions. On average 8-10 percent of HDFC Bank's total gross non-payment accounts (NPA) are related NPAs (meaning this customer has another defaulted exposure).

Taking intelligence to the next level

When it comes to business analytics, HDFC Bank has ambitious plans to achieve new insights. "We want to take our business intelligence to the next level," said Mittal. "We want to study the behavior of the customer because it can help us develop more accura 500

Cannot serve request to /content/sascom/en_za/customers/hdfc.html on this server


ApacheSling/2.2 (Day-Servlet-Engine/4.1.44, Java HotSpot(TM) 64-Bit Server VM 1.7.0_21, Linux 2.6.18-274.el5 amd64)