Icici bank put option

Icici bank put option

Posted: aалина Date: 21.06.2017

In mid, the credit control teams at ICICI Bank were confronted with a new set of challenges. Following the subprime mortgage crisis of in the United States, the world economy witnessed a slowdown. The effect of the subprime turmoil, that was once thought to be limited to the housing loans business, had started spreading to other sectors.

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As risk levels accentuatedcredit terms needed to be tightened. As a result, the banks were also required to deal with a new challenge of reduced liquidity, which was threatening to become a powerful economic decelerator.

Deterioration in the macro-economic environment and the rising interest rates further intensified the challenges faced by banks; ICICI Bank was no exception. Amidst these challenges, ICICI Bank had to ensure that its customers remained satisfied with its services and did not switch to its competitors.

Debt collection was identified as the key process where a friendlier approach could result in improved customer satisfaction and loyalty. One of the important steps in the debt collection process was choosing the appropriate customer-approach channel for each case.

ICICI Bank decided to use business intelligence BI to achieve this goal. A novel approach to debt recovery.

One of the most pertinent aspects that ICICI Bank had to pay attention to was debt recovery. Although the primary function of recovery agents is to ensure debt collection, the bank wanted to carry out the process delicately without losing its customers. Thus, the bank introduced customer-friendly practices, which, in addition to ensuring collection, were aimed at improving customer relationship and its own brand value.

The bank uses multiple channels for debt collection. This includes non-intrusive channels such as SMS, e-mails, IVR, dunning letters, and reminder calls through the call centers, which are used to handle early delinquencies.

The serious delinquents require a personal visit or may even need initiation of legal action. India, with its varied demographics and diverse customer segments, posed a challenge when it came to servicing the heterogeneous customer-base. The vastness of the Indian market resulted in heavy dependence on the field agencies for debt collections, unlike the western world, where majority of the delinquent pool is serviced by the call centers.

The bank management, with the aim to transform debt collection as a customer retention tool, decided to use technology to achieve the objective. It employed analytical models developed with SAS that factored in several parameters such as efficiency of collector, customer profile, risk behavior, and exposure. For instance, low risk and low outstanding debtors may just need a gentle reminder, whereas high risk and high outstanding debtors need to be directly contacted via field agencies or bank employees.

Prior to the adoption of technologyover a thousand employees of the bank used to manually allocate around 30 lakh delinquent cases across more than locations to around 2, channel partners based on subjective rules.

icici bank put option

However, the manual allocation proved inefficient, and the scale of the exercise called for an analytics-based solution. This data is made available to the collection work flow system CAPSwhich delivers the details of the case assigned to each individual. The vendor was not involved during the deployment owing to lack of experience in the Indian debt collection process.

However, post implementation, the vendor optimized the code and ensured that the solution complied with the international standards.

Offering self-service and a multi-channel approach have improved efficiency in debt collection at ICICI Bank. The BI unit BIU has played a vital role in important projects like centralized allocation and score cards. The project has resulted in a major shift in the DSMG strategy and improved collection efficiency. Projects like customer categorization have provided crucial insights for strategic decision making.

Key processes where BI has proved helpful Tangible benefits. Follow Anti Money Laundering AML guidelines, the ING Vysya way. Maia 1Key provides HDFC Life with option for BI upgrade. Business intelligence tool to be deployed at Tata AIG Life. Yahoo deploys open source BI tool made in India. SAP BW aids enterprise-wide data management at Essar Steel. Key processes where BI has proved helpful. Customer behavior during the last 12 to 24 months was analyzed depending upon the product and business objective while building these models.

These models help identify and hence give differential treatment to customers based on their payment propensity. The bank now has 10 payment propensity scorecards and 34 segmentation models across customer segments and products, built over two years.

The models are updated on a monthly and quarterly basis factoring in the changing customer behavior and business dynamics. The scorecards are deployed using SAS. This is a critical strategy deployed for non-delinquent customers across products.

It involves behavioral analysis of the potential defaulters to assess their credit orientation and worthiness. Traditional methods react to delinquency that has already occurred, whereas the pre-delinquency management gives an edge by raising an early alarm.

Analytical models are developed to identify customers who have higher probability of forex price pattern trading delinquent. Further, these customers are offered a wide range of services like best forex signals trade copier reminders, SMS campaign, new payment schedule, and flexible credit limits.

An important tool for risk management adopted by banks at a portfolio level. Using analytics across the spectrum in DSMG has brought about a number of efficiencies in the process. This, along with extensive use of data and models to evaluate performance livestock sales in alberta prioritize or de-prioritize icici bank put option, has been widely recognized as the best-in-class use of analytics in collections.

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A novel approach to debt recovery One of the most pertinent aspects that ICICI Bank had to pay attention to was debt recovery. Reporting of the key parameters.

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