ICICI Bank Uses BI to Improve Debt Collection and Reporting System
ICICI (Industrial Credit and Investment Corporation of India) was formed in 1955 as a joint initiative of the World Bank, the Government of India, and representatives of Indian industries. Initially, ICICI focused on providing project finance to Indian businesses, but later, it transformed itself into a financial services group, offering a wide range of products and services.
ICICI Bank was incorporated at Baroda, Gujarat, on January 5, 1994, and received the Certificate for Commencement of Business on February 24, 1994. The bank was a wholly owned subsidiary of ICICI. In 1998, ICICI Bank launched online banking system operations. Today, it has a network of 3,536 branches and 11,162 ATMs in India. It is India’s largest private sector bank and has subsidiaries, branches, and representative offices in various countries.
In 2001, the Boards of Directors of ICICI and ICICI Bank agreed upon the reverse merging of ICICI, ICICI Personal Financial Services Limited, and ICICI Capital Services Limited with ICICI Bank, leading to the integration of the group’s financing and banking operations in a single entity
Debt Collection
The effect of the US subprime mortgage crisis of 2007, initially believed to be limited to the housing loan business, spread to other sectors too. With the economic recession came new challenges for the credit control teams at ICICI Bank. The increased risk level created a need to tighten the credit terms, so the bank had to deal with reduced liquidity. Increasing interest rates and weakening economic conditions were other issues the bank had to face. Amidst these challenges, ICICI Bank had to focus on retaining its customers. It wanted to ensure customer loyalty by providing the best services possible.
Debt collection is considered a crucial area of the banking business, which, if not handled delicately, could lead to loss of customers and ultimately to loss of revenue for banks. ICICI Bank identified that debt collection, if managed in a friendlier way, could secure customer satisfaction and thereby improve customer relationship and loyalty.
With the main objective of using debt collection as a tool for customer retention, the management at ICICI Bank decided to employ BI. Before the BI analytical approach was adopted, ICICI Bank’s debt collection process involved manual allocation by bank personnel. Over a thousand employees were responsible for allocating, on the basis of subjective rules, approximately 300,000 debt collection cases across different locations to channel partners. The process was very complicated, inefficient, and time consuming and created a demand for a technology-driven, analytics-based solution. ICICI Bank decided to adopt the SAS BI Platform to improve its debt collection process.
The bank hired SAS to develop a “centralized debtors’ allocation model,” an analytical model based on customer profiling, collector efficiency, and customers’ history of getting into debts. This model helped the bank allocate cases to appropriate channels. ICICI Bank’s list of defaulters is categorized into high risk and low risk. Thus, debtors coming under the low risk and low outstanding category get a mild reminder, while those under the high risk and high outstanding category may require a visit from bank employees or field agencies.
After the allocation of debtors, the SAS BI Platform is used to run rules. This helps to capture the details of each case as well as the details of the collection agency to which that case needs to be allocated. The data collected is then provided to the bank’s collection workflow system, the collection activities processing system (CAPS), to deliver the details of the case assigned to each individual. ICICI Bank uses multiple channels for debt collection—text messages, emails, dunning letters, and reminder calls through call centers for low-risk cases, and a personal visit or legal action in high-risk cases. SAS BI has enabled this multichannel approach, helping to increase collection efficiency at ICICI Bank.
The main areas in which SAS BI has improved the bank’s functioning are payment recovery, loss forecasting, and risk management. The payment recovery models are based on parameters such as customer credit payment history, risk exposure, cross-holdings, and geographic location. The pattern of customer behavior over the preceding year or two was analyzed while creating these models. The product and the business objective were also taken into account. Customers are identified on the basis of their payment propensity, so these models enable differential treatment. To keep up with factors like changing customer behavior and business dynamics, the models are updated every month or quarter. SAS BI has helped ICICI Bank in the behavioural analysis of potential defaulters. Analytical models identify customers who have the maximum probability of going into the defaulters’ list, and the bank can take immediate action through text messaging campaigns, soft reminders, and flexible credit limits, to prevent loss.
SAS BI has provided various benefits to ICICI Bank such as reduction in credit loss through improvement in the process of debt collection, better utilization of human resources through the use of automated systems, and reduction in the number of days required for defaulters’ case allocation (thus providing more time for collectors to resolve the cases). The intangible benefits provided by the automated system include high transparency and improved customer relationship (because of the use of soft-touch channels for low-risk cases and the allocation of the same employees for customers availing multiple loans). BI has also helped in the identification of strategic customers who could be offered better services.
Reporting System
At ICICI Bank, innovation is considered key to improving the bank’s market share and maintaining its competitive edge. To address the needs for flexibility and scalability in a growing business and to obtain a single view of the customer, the bank decided to implement an enterprisewide reporting system. At that time, multiple reporting systems and tools were in use at the bank, and information dissemination was handled manually by the IT team members. Security concerns over existing data and the need to handle increasing amounts of data called for a user-friendly system that would integrate data sources.
ICICI Bank adopted the SAS Enterprise Intelligence Platform as a single enterprisewide framework. The system has empowered the bank with key benefits such as usability (providing information access to all users across the bank), scalability (addressing queries from many users), interoperability (interacting with all of the bank’s existing data sources), and manageability (managing security concerns).
1. What were the challenges ICICI Bank faced in this case?
2. What type of system existed prior to the adoption of the SAS BI debt collection allocation model?
3. How do you think SAS BI tools have changed allocation processes at ICICI Bank?
4. What benefits has the bank gained by implementing the SAS Enterprise Intelligence Platform?