Development of After Sales Service System for Louis Pion

A subsidiary of Galeries Lafayette Group, Louis Pion is a leading retailer and fashion watch manufacturer. Headquartered in France, Louis Pion has more than 170 stores. ERP used by Louis Pion did not cater to the unique requirements of After Sales Service process of Louis Pion. Because of lack of proper system, issues faced by Louis Pion were

  • Loss incurred due to lack of identification of watches that are under warranty
  • Inconsistency of processes across stores
  • Uncontrolled delays in servicing

To address the above issues, Louis Pion decided to custom develop an application. Multiple vendors were evaluated, Surya was selected based on the development approach, timeline and cost.

Project Execution

At beginning of project, Surya was provided with a high level functional specification. Basis this, Surya created a working prototype using AppBrahma tool, a Microsoft Visual Studio add-on that generates codes for online and batch programs. Once the working prototype was ready, a detailed discussion was conducted with Louis Pion key decision makers which consisted of CIO, Project Manager and IT Manager. Outcome of this discussion was a refined specification which included screen and workflow details. Prototype helped Louis Pion team to quickly finalize functional specifications.

Surya started development and test of core modules using AppBrahma. Post onsite installation, UAT was conducted iteratively by core team. Core team requested for further changes which were delivered during multiple UAT iterations. On acceptance, core team conducted training and the system went live with 5 shops, as pilot run. Few more changes were requested and delivered during this pilot run. Core team conducted training for remaining store users, post which the system went live across 170+ stores.

Louis Pion is using the After Sales Service (SAV) system for last 2 years without any major issue. Surya supports the system with continuous refinement and addition of new features, as and when identified by Louis Pion.


Weeks taken to Go-Live from the contract finalization is 27, 25 weeks earlier compared to the original plan of Louis Pion.



  • Working prototype helped Louis Pion to conceptualize the system and Surya to understand the requirements
  • Since parameter screens were quickly generated using AppBrahma tool, enough time was spent to refine core modules
  • Faster development cycle
  • Iterative UAT and parallel fixes helped to stabilize system with small set of users

Implementation of FTP at Doha Bank

Doha Bank is one of the largest commercial banks in the State of Qatar. It was incorporated in 1978.  Doha Bank provides individuals, corporate and institutional clients across Qatar and internationally. The Bank has total asset of USD 20.36 billion with its loan portfolio of USD 13.96 billion and deposit portfolio of USD 12.42 billion. Doha bank has banking operations in Kuwait, UAE and has recently started its operations in India.

Implementation of FTP


Doha bank was looking for an application to measure and monitor the profitability at various dimensions such as Branch, Department and Relationship Manager. Bank was not following any advanced method of Transfer pricing to measure profitability. Transfer price was calculated manually using traditional method by measuring income and expenses booked in various business units.


In the absence of a transfer pricing system, bank was unable to measure the profitability of products, branches and relationship managers accurately. Hence bank was not able to incentivize right products, branch and relationship managers. Bank did not have any transfer price rate associated with products and hence actual interest rate of product was never compared to analyze the profitability.


After successful implementation of BALM, Surya was the right choice for the implementation of Fund Transfer Pricing solution and hence project was awarded to Surya.

Surya’s new FTP (3.0) solution allows bank to calculate transfer pricing at account level and hence allows multi-dimensional profitability analysis. The System supports Matched maturity method. It supports association of various market and contract curves to derive the transfer price curves for a product. It also allows bank to add proper spread for credit risk, liquidity risk, interest risk, ALCO spread, et al. while deriving the curve, which is be defined and set by the bank.

A Brief on FTP implementation

Surya implemented its new FTP (version 3.0) application to help bank to measure above mentioned requirements. The system is configured to calculate FTP at account level using matched maturity concept.


    • Construction of FTP curve using Market and internal sources using Boot strapping methodology
    • Facility to setup FTP rate based on parameters like product, currency, residual maturity, contractual maturity
    • Application allows users to FTP at different frequencies such as daily, weekly, monthly, quarterly, yearly
    • Cost allocation module is also delivered as part of FTP implementation

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Implementation of SMERATE at FDH Bank, Malawi

First Discount House (FDH) is a wholly owned subsidiary of FDH Financial Holdings Limited and was licensed as a discount house by the Reserve Bank of Malawi on 20 July 2001. First Discount House is currently the only Discount House in Malawi. Operational since April 2002, the company has grown into one of the strongest and most reliable Financial Services Houses in the country. Bank has an asset size of around 112 million USD.

Implementation of SMERATE


Malawi doesn’t have any external rating agency which provides customer rating to banks. Basel II implementation at Malawi, required banks to have an internal rating of its customers. Bank also wanted to bring an efficient loan proposal sanction process which will cater the process from proposal request, to rating till approval. This will bring down operational risk involved in proposal sanction process.


Developing a rating model for different types of customers is challenging due to unavailability of data for various type of customers. Manual processing and sanction of proposal usually takes many days as the document has to flow from remote branches to credit officer in the head office. Customer ratings were done manually and were not uniformly maintained for same type of customers


Customer scoring model (SMERate) of Surya allows customer rating based on both qualitative and quantitative parameters. System allows to build multiple scoring models in the system and different types of customers can be rated using the different models. System can be setup to have credit work flow during the sanctions of credit proposals.

A Brief on SMERATE implementation

Surya implemented SMERate along with its work flow engine in FDH. Capturing of customer rating input parameters are automated and are fed into the system when proposals are received. In addition to entry of customer, system also provided facility for the branches to upload original documents submitted by the customers and provide easy audit facility by credit offers.

Surya also helped bank to do one time rating of all its existing customers through a migration process during implementation.


  • System brought efficiency in processing of proposals of both existing customers and new customers.
  • Customer rating mechanism is standardized and hence brings uniformity and allows bank to take better decision
  • All the supporting document for a sanctions are upload against the proposal and auditing became hassle free.
  • Better control on the sanctions, as high volume sanctions are configured to have multi-level approval in the workflow.

For more information please write to

Implementation of CARE and CallRpt at FDH Bank, Malawi

First Discount House (FDH) is a fully owned subsidiary of FDH Financial Holdings Limited and was licensed as a discount house by the Reserve Bank of Malawi on 20 July 2001. Operational since April 2002, the bank has grown into one of the strongest and most reliable Financial Services Houses in the country. 

Implementation of CallRpt


Banks in Malawi are mandated to follow Basel II frame work as per Reserve Bank of Malawi (RBM) guidelines. Banks are requested to identify Risk weighted assets based on credit risk, operational risk, liquidity risk, interest rate risk and market risk. Based on this, capital requirement for the bank is identified. RBM also requested all the banks to submit a set of reports (Call Reports) which includes different reporting schedules for Capital, Credit risk, operational Risk, Market risk, Liquidity risk, Interest rate risk and other financial information to central bank. In total of there are around 48 reports to be submitted by the banks to central bank.


Preparation of the reports as per the central bank reporting format was a challenge for the bank due to complexity of data requirement. Some of the data required were not captured in core banking or treasury systems.

Manual calculation of risk, using Basel II rules was challenging, bank used to spend weeks to calculate the risk and compile central bank reports.


Surya has implemented CARE (capital Adequacy and Risk Evaluation) and has used Risk Reporting Package (RRP) to support Basel II risk calculation and central bank reporting requirement. Flexible rule definition module of CARE, helped to setup Malawi specific BASEL II rules with lesser effort and the project was completed within 3 months.

A Brief on CallRpt implementation

  • CARE applications risk calculation rules were customized as per the BASEL II rules of Malawi.
  • CARE application is interfaced with Surya’s ALM solution, BALM which was implemented earlier to identify liquidity and interest risk.
  • Risk report package allowed Surya to configure complex call reporting requirements of the bank. Due to unavailability of customer rating information in the core banking system, Surya interfaced CARE application with SMERate, Surya’s customer rating application.


  • Generation of reports with a click of a button, with options to maintain and extract history reports from the system
  • All Call reports are downloaded into a single MS Excel with each report in different work sheets as required by RBM. Downloaded reports are compatible for uploading into RBM website without any manual intervention.
  • System is interfaced with core banking system (T24). An entry/upload system also delivered to capture manual data classification.
  • Interfaced system with BALM for liquidity risk and interest rate risk
  • Interfaced system with customer rating system (SME Rate) to get internal rating of the customer
  • Entire processing of call report interface, rules and report batches are completed within 45 minutes
  • Bank can now measure its risk weighted assets in better way which helping bank with better accurate classification of Tier I and Tier II capital

For more information please write to

Implementation of BALM at Doha Bank

Incorporated in 1978, Doha Bank is one of the largest commercial banks in the State of Qatar.  Doha Bank serves individuals, corporate and institutional clients across Qatar and internationally. The Bank has total asset of USD 20.36 billion with its loan portfolio of USD 13.96 billion and deposit portfolio of USD 12.42 billion. Doha bank has banking operations in Kuwait, UAE and recently started its operations in India.

Implementation of BALM


Doha bank was in search for an ALM solutions with flexibility in defining ALM Products which can handle multiple country operations. One of the main concerns for the bank was interface execution time. Because of banks earlier experience of unsuccessful ALM implementation, bank requested Surya to execute a proof of concept (POC) before finalizing Surya’s System. Surya team executed POC in 2 weeks and the project was awarded to Surya.


Bank didn’t have a system in place for ALM and all the reports were generated manually by collecting data from various source systems manually.

  • Collection of source data from CBS and treasury system to analysis risk and identifying maturity profile to bucket source data
  • Time taken to compile data and generate statutory and other management reporting for individual countries and at group level
  • Time taken to generate BASEL III reports for reporting requirement of consolidated currency, significant currency for different countries’ operations as per respective central bank guidelines.


Surya has implemented its ALM solution, BALM at Doha bank at its individual geographic operations and consolidated operation. BASEL III module of the application automated the statutory reporting requirement. This project was executed in the span of 2 months.

A Brief on BALM implementation

BALM implementation was started in the month of June 2014 and was completed for its Doha, Kuwait, UAE and consolidated operations within 2.5 months. Implementation of BASEL III module for Qatar central bank reporting was implemented in the span of 1 month. Surya implemented BASEL III for Kuwait after Kuwait central bank finalized the guidelines in March 2015.


  • Liquidity and interest risk analytical functions for individual country operations and at group level
  • Automation of MIS reports for both management and statutory reporting
  • Generation of BASEL III reports based on each country central bank directions with audit functionality of drill down
  • Entire interface processing from data generation is automated to run daily. Entire data processing interface processing takes less than an hour in contrast to previous execution time of more than 24 hours.
  • Automated alerts are provided to alert users on status of execution of interfaces
  • Tools are delivered to users for the reconciliation of BALM report values with source system
  • Tools are provided to users to maintain the interface configuration parameters
  • Surya has delivered custom MIS reports which allows bank to analyse country wise, sector wise exposure analysis

Doha bank started its operations in India in March 2015. Bank is planning for BALM implementation in Indian operation after completing implementation of core banking solution.

Implementation of BALM and FTP at International Bank of Qatar

International Bank of Qatar (IBQ), is based in Doha, Qatar. IBQ offers banking solutions in the areas of retail, private and corporate banking/finance requirements. It is one of the oldest existing banks in Qatar and celebrated its 50th anniversary in 2006. IBQ opted to implement BALM, Surya’s Asset Liability Management solution and FTP, Surya’s Funds Transfer Pricing solution.

Implementation of BALM


Despite recent financial turmoil, the economy of Qatar has maintained a stable growth rate. Much of this can be attributed to strict regulation and supervision by Qatar Central Bank and the Asset-Liability Management Committees of banks. As a result, banks have to measure and manage Liquidity and Interest Rate Risk, and analyze various scenarios and ratios for regulatory reporting on an on-going basis. In addition, the ALCO at IBQ sets the level of risk tolerance and imposes over all threshold limits.


IBQ had an in-house Microsoft Excel based solution that catered to ALM requirements. However, the drawbacks of this solution were:

  • IBQ was not able to generate requisite ALM reports and ratios.
  • ‘What if’ scenarios could not be modeled
  • Data entry and calculation were manual. Data was sourced from various transaction systems like Core Banking, Treasury, and Microsoft Excel.

To conclude, there were various difficulties faced by the bank. In addition there was a high possibility of human error, and the time taken to generate these reports was unduly long. This made monitoring liquidity and interest rate risk an up-hill task. Informed decisions could not be taken on the basis of the reports generated by the existing ALM solution.


As the existing Microsoft Excel based solution could not meet IBQs requirements, IBQ sought to implement an integrated ALM solution. As part of the selection process multiple ALM solutions were evaluated by IBQ, and BALM, Surya’s ALM solution, was adopted by IBQ for implementation.

A Brief on BALM implementation

BALM was implemented in IBQ in 2012. Implementation was completed in a short span of nine weeks and BALM went live in fourteen weeks from the start of the System Study phase.


With BALM in place, IBQ now has a clearer picture of its risk positions. Some of the business objectives that were met with BALM are:

  • Risk Managers now enabled to precisely analyze the impact of a wide variety of business decisions on the bank’s balance sheet.
  • Risk Managers now are not only able to measure changes in Net Interest Income and Margin with changes in macro-economic factors, but can also forecast the NII and Margin.
  • Compliance with regulatory norms has been enhanced with increased accuracy and consistency of data and assumptions.

Functional objectives that were met with BALM:

  • BALM has enabled interface with all data sources thus reducing significantly the time required to upload, aggregate and validate data. Processing of data is done on a daily basis with throughput time of 15 minutes.
  • Scenario Analysis helps to simulate various ‘what if’ situations by applying multiple transformation functions on native and scenario data.
  • Trend Analysis helps to study behavior of products and ratios over a period of time.

Key Ratio Builder enables users to create and monitor tolerance limits of multiple ratios.

Surya Advantage

With a view to meeting users’ needs and convenience, our Solutions are developed for deployment either as an integrated suite of products, or selectively on a modular basis, as required by financial institutions. The former option reduces time and costs of implementation, while the latter permits users to adopt solutions sequentially, matching implementation to their incremental needs and priorities.

For more information please write to

Implementation of BALM at Axis Bank

Axis Bank is one of the three largest private sector banks in India, providing services to customers from SME, agriculture, retail business segment and large & mid corporates, the bank has a growing asset size of above 60 Billion USD. The Bank has a large footprint of around 2400 domestic branches. The overseas operations of the Bank are spread over seven international offices with branches at Singapore, Hong Kong, DIFC (Dubai International Financial Centre), Colombo and Shanghai and representative offices at Dubai and Abu Dhabi.

Implementation of BALM


After opting for a new core banking solution, Axis Bank was looking for an Asset Liability Management solution to manage and mitigate their financial risk as per the ALM guidelines from Reserve bank of India.


Bank didn’t have a system in place for ALM and all the reports were generated manually.

  • The main challenge was to retrieve large volumes of data from Core banking and Treasury systems (Finacle Core, Finacle Treasury and FinnOne)
  • The time taken to extract data and generate report manually was too long
  • Segregation of ALM products into multiple sub products was not easy due to complex mapping between ALM products and General ledger accounts
  • It was difficult for bank to meet the increased demand of additional reports from Regulatory authorities
  • Lack of data and tools for fine tuning the Asset Liability Management system


Axis chose Surya’s BALM as a best fit solution for asset liability management including ability for regulatory compliance and ease of use and maintenance. BALM resolved the main concern of the bank for centralization for effective and timely assessment of risk.

A Brief on BALM implementation

BALM was implemented in Axis Bank in 2002. The project was completed in a span of 3 months. Application has been upgraded to newer version twice in last 10 years in the bank. The minor upgrades are provided periodically whenever there is demand from Central bank for new reports.

BALM at Overseas branches

BALM is also implemented at five overseas operations of the Bank in the year 2013 – 14

  • Axis Bank – Srilanka
  • Axis Bank – Dubai
  • Axis Bank – Singapore
  • Axis Bank – Hong Kong
  • Axis Bank – Shangai

The implementation of overseas operations was quick and completed in a span of 3 Months.

A BALM consolidator application is also implemented in Axis Bank India to give a consolidated view of Domestic as well as overseas ALM reports.


Surya’s solution has given Axis Bank with detailed analysis at consolidated and granular level for better decision making especially in time constrained activities.

  • BALM handles large volumes of data each day with quick transformation and calculation throughput
  • The entire process of data upload and report generation takes less than 4 hours in domestic operation
  • For Overseas operations, data interface execution takes less than 1 hour
  • With a successful interface mapping between BALM and General Ledger codes, bank is able to create new ALM products and bifurcate the existing products into multiple ALM products on its own
  • For entire Term loan portfolio of bank, Loan cashflows are generated in BALM interface for segregating outstanding loans into appropriate buckets
  • With consolidated BALM application in place, bank is able to get a consolidated view of domestic and overseas operations’ ALM position. The consolidator not just provides basic ALM reports but also gives all other analytics of Liquidity and Interest Rate risk at consolidated level
  • The consolidation of domestic and overseas operation takes less than 10 minutes. Consolidation is done after executing individual operations
  • Apart from regulatory reports, Bank is able to analyze and monitor Net Interest Income, Duration, Market Value of Equity, Several balance sheet Ratios etc.
  • Compliance with regulatory norms has been enhanced with increased accuracy and consistency of data and assumptions

For more information please write to