A Future You Can Bank on
Customer Company Size
Large Corporate
Region
- Asia
Country
- India
Product
- ARIS Process Transformation & Management Platform
- ARIS Connect
Tech Stack
- Cloud Computing
- Database Management
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Cost Savings
- Customer Satisfaction
Technology Category
- Platform as a Service (PaaS) - Connectivity Platforms
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Process Control & Optimization
- Regulatory Compliance Monitoring
- Predictive Quality Analytics
Services
- System Integration
- Training
About The Customer
IndusInd Bank, based in Mumbai, is India’s first new generation bank. Founded in 1994, it has embodied the spirit of innovation and sound business practices of the ancient Indus Valley Civilization. The bank now boasts more than 1,400 branches and 2,285 ATMs spread across geographical locations. Ranked as the 13th most valuable brand in India, FY18 results show a 28 percent growth in total business. By answering customer needs with new and innovative banking services, IndusInd Bank aims to double profits, clients and branches within the next three years.
The Challenge
IndusInd Bank, a leading innovator in India's booming FinTech industry, faced several challenges due to its rapid growth and the acquisition of a credit card business. The bank needed to optimize its internal systems and processes to stay lean, fast, and innovative. The challenges included increasing competition and thinner margins on traditional products, rapid business growth and the fast pace of innovation, back-end process inefficiencies, growing regulatory requirements, and the need to make the business future-ready. To continue outcompeting rivals and hitting growth targets, IndusInd Bank knew it needed to shorten innovation cycles and improve its already industry-leading level of personalized services and customer-support speed.
The Solution
In 2010, IndusInd Bank embarked on a digital transformation and chose local Software AG partner ClayLogix and the ARIS Process Transformation & Management Platform to start. The first step of the transformation involved understanding the bank’s data structures, processes, and systems architecture. The bank found opportunities to reduce duplication, eliminate inefficient versioning, and implement standardized templates. Using Software AG’s ARIS, the bank implemented a single point-of-truth database and role-specific portals. By 2015, IndusInd Bank was ready for the next step: a fully digitalized transformation, including all business and IT processes across all departments and contact centers. The bank is also working to roll out ARIS Connect, so customers can reap the benefits of collaboration, mobile enablement, and cloud-ready features.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Real-time In-vehicle Monitoring
The telematic solution provides this vital premium-adjusting information. The solution also helps detect and deter vehicle or trailer theft – as soon as a theft occurs, monitoring personnel can alert the appropriate authorities, providing an exact location.“With more and more insurance companies and major fleet operators interested in monitoring driver behaviour on the grounds of road safety, efficient logistics and costs, the market for this type of device and associated e-business services is growing rapidly within Italy and the rest of Europe,” says Franco.“The insurance companies are especially interested in the pay-per-use and pay-as-you-drive applications while other organisations employ the technology for road user charging.”“One million vehicles in Italy currently carry such devices and forecasts indicate that the European market will increase tenfold by 2014.However, for our technology to work effectively, we needed a highly reliable wireless data network to carry the information between the vehicles and monitoring stations.”
Case Study
Safety First with Folksam
The competitiveness of the car insurance market is driving UBI growth as a means for insurance companies to differentiate their customer propositions as well as improving operational efficiency. An insurance model - usage-based insurance ("UBI") - offers possibilities for insurers to do more efficient market segmentation and accurate risk assessment and pricing. Insurers require an IoT solution for the purpose of data collection and performance analysis
Case Study
Smooth Transition to Energy Savings
The building was equipped with four end-of-life Trane water cooled chillers, located in the basement. Johnson Controls installed four York water cooled centrifugal chillers with unit mounted variable speed drives and a total installed cooling capacity of 6,8 MW. Each chiller has a capacity of 1,6 MW (variable to 1.9MW depending upon condenser water temperatures). Johnson Controls needed to design the equipment in such way that it would fit the dimensional constraints of the existing plant area and plant access route but also the specific performance requirements of the client. Morgan Stanley required the chiller plant to match the building load profile, turn down to match the low load requirement when needed and provide an improvement in the Energy Efficiency Ratio across the entire operating range. Other requirements were a reduction in the chiller noise level to improve the working environment in the plant room and a wide operating envelope coupled with intelligent controls to allow possible variation in both flow rate and temperature. The latter was needed to leverage increased capacity from a reduced number of machines during the different installation phases and allow future enhancement to a variable primary flow system.
Case Study
Automated Pallet Labeling Solution for SPR Packaging
SPR Packaging, an American supplier of packaging solutions, was in search of an automated pallet labeling solution that could meet their immediate and future needs. They aimed to equip their lines with automatic printer applicators, but also required a solution that could interface with their accounting software. The challenge was to find a system that could read a 2D code on pallets at the stretch wrapper, track the pallet, and flag any pallets with unread barcodes for inspection. The pallets could be single or double stacked, and the system needed to be able to differentiate between the two. SPR Packaging sought a system integrator with extensive experience in advanced printing and tracking solutions to provide a complete traceability system.
Case Study
Transforming insurance pricing while improving driver safety
The Internet of Things (IoT) is revolutionizing the car insurance industry on a scale not seen since the introduction of the car itself. For decades, premiums have been calculated using proxy-based risk assessment models and historical data. Today, a growing number of innovative companies such as Quebec-based Industrielle Alliance are moving to usage-based insurance (UBI) models, driven by the advancement of telematics technologies and smart tracking devices.
Case Study
MasterCard Improves Customer Experience Through Self-Service Data Prep
Derek Madison, Leader of Business Financial Support at MasterCard, oversees the validation of transactions and cash between two systems, whether they’re MasterCard owned or not. He was charged with identifying new ways to increase efficiency and improve MasterCard processes. At the outset, the 13-person team had to manually reconcile system interfaces using reports that resided on the company’s mainframe. Their first order of business each day was to print 20-30 individual, multi-page reports. Using a ruler to keep their place within each report, they would then hand-key the relevant data, line by line, into Excel for validation. “We’re talking about a task that took 40-80 hours each week,” recalls Madison, “As a growing company with rapidly expanding product offerings, we had to find a better way to prepare this data for analysis.”
