Bank speeds time to market with advanced analytics
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- Merry Tracey Garrett
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1 Bank speeds time to market with advanced analytics Danske Bank slashes time to develop critical analytical models by 50 percent and improves decision making with Statistica s advanced analytics platform. Case Study Company profile Company Danske Bank Industry Financial Country Denmark Employees 18,478 Business need To deliver timely and accurate credit decisions and other customer services in today s 24/7 world, Danske Bank needed to be able to quickly build and deploy advanced analytical models. Solution Using Statistica s advanced analytics platform, the bank was able to slash model development time in half while delivering more sophisticated and accurate models, enabling better decisionmaking and customer satisfaction. Benefits Slashed time to develop and deploy analytical models by 50 percent Improved decision making with more advanced analytical models Delivered an easy-to-use, standardized toolbox that can quickly be customized to meet users needs Ensured fast ROI by deploying easily and integrating smoothly with existing systems
2 Danske Bank Group is a Nordic universal bank and one of the leading financial enterprises in northern Europe. It offers a full range of banking services to its five million customers, with an emphasis on retail banking. To deliver quick and accurate service to those customers around the clock, Danske Bank relies on advanced analytics from Statistica. Analytical models are critical in today s 24/7 banking world. Banking is no longer confined to traditional bankers hours of 10 a.m. to 3 p.m. Today, customers access their accounts, transact business and even apply for loans 24/7/365. To provide those services, financial institutions need a variety of analytical models, such as risk models that predict the credit worthiness of loan applicants and models that assess the value of assets. These models enable the bank to quickly respond to a loan application, for example, not just with denial or approval, but with a specific credit limit. And those responses need to be fair and accurate. We have reduced the time we spend on models up to 50 percent with Statistica. Our development process is much leaner and smoother compared to what it was before. - Jens Christian Ipsen, First Vice President, Danske Bank 2
3 Creating and updating its analytical models used to be a slow, labor-intensive process for Danske Bank. First, the business modelers designed what a model should look like, using their own set of tools. Then they handed the model over to IT, who started over and hand-coded the model again in our legacy systems, recalls Jens Christian Ipsen, first vice president of Danske Bank. With so much manual effort and rework, this was a very long process that was not meeting the needs of the business or our customers.. Seeking more than just the right functionality Danske Bank began looking for a solution that would streamline model development and provide the advanced analytics it needed both in the present and into the future. Wisely, the bank detailed not only its functional requirements but broader selection criteria as well, including speed of implementation, ease of use, ability to integrate with existing systems, total cost of ownership and quality of vendor support. Based on those criteria, the bank chose Statistica. Statistica provides us with a standardized toolbox that we can easily customize to meet our needs, so we are able to constantly challenge and update our model portfolio. - Kim Madsen, Head of Model Framework, Danske Bank 3
4 Statistica was the right choice for us because it met our functional requirements and much more, explains Ipsen. The solution fit well into our platform and enabled us to use our existing architecture. Our business users were quite comfortable using the solution. And in my role, I find the best part about Statistica is that we have really good cooperation from Statistica s support organization. Statistica delivered everything we needed. Slashing time to market by 50 percent With Statistica, Danske Bank is now able to quickly develop and deploy the statistical models it needs to serve customers quickly and accurately. My team uses Statistica to both develop the models and put them into production where we use it in the front line, explains Kim Madsen, head of model framework, Danske Bank. When a customer applies for a loan, for example, our answer is based on those models, which use a variety of data, 3 including data related to the customer as well as external data, such as data from credit bureaus. We use Statistica to find patterns in that data related to good and bad financial behavior, predict whether a customer will default within a year, and determine credit worthiness. Those models must change and be replaced over time to keep up with market demands, such as increased demand for mobile access to banking applications. As a bank, we need to continually innovate to meet our customers requirements, notes Madsen. Statistica s predictive analytics are the foundation to meeting those demands. Statistica provides us with a standardized toolbox that we can easily customize to meet our needs, so we are able to constantly challenge and update our model portfolio. In fact, with Statistica, Danske Bank can deliver new models twice as fast as before. We have reduced the time we spend on models up to 50 percent with Statistica, reports Ipsen. Our development process is much leaner and smoother compared to what it was before. 4
5 Ensuring regulatory compliance This better speed to market is critical not only to attract and retain customers, but also to satisfy compliance regulations. After the financial crisis, regulators developed many new requirements fo banks. Our models have been under increasing scrutiny for example, we have had to recalibrate all our models, Ipsen explains. In this area, we have definitely seen the benefits of the Statistica platform. Because it is so easy to use, we have been able to do far more than we could before. Advanced modeling Moreover, with Statistica, Danske Bank can produce more advanced and accurate models than before. It s critical that our models are accurate that we can make the right decisions and provide customers with the right prices and the right credit limits, says Ipsen. With Statistica, we can do more advanced modeling than we could before. It is a key part of our larger strategy around analytics, which involves not only structured data but Big Data in our data hub. These advanced analytics translate directly into better service for customers. One way to meet customer demand is to help customers better manage their finances by getting insights into their household economy, adds Madsen. Statistica s predictive analytics supports the model framework to achieve this goal. With Statistica, we can do more advanced modeling than we could before. It is a key part of our larger strategy around analytics, which involves not only structured data but Big Data in our data hub. - Jens Christian Ipsen, First Vice President, Danske Bank 5
6 The scalability to meet future needs Danske Bank has already ramped up its use of Statistica, and is confident that the solution will continue to meet its needs as banking requirements evolve. We re creating a lot of models and processing a lot of data almost 20,000 calculations each day, notes Ipsen. One of the reasons why Statistica is important for our business is that moving forward, we will need to build more and more models to use in our business processes. We already have initiatives to put more processes on mobile devices, and we will need to gain additional insight around customer behavior to make even more automatic decisions. I m confident that the Statistica platform can scale to meet our needs into the future. About Statistica Statistica s advanced analytics, big data and IoT offerings provide you endless possibilities to innovate your enterprise. Whether it s uncovering the genetic basis of a disease, reducing hospital readmissions, mitigating financial risk, or ensuring procedural validation, Statistica enables organizations to transform in new and exciting ways. By embedding analytics everywhere and empowering a wider community of citizen data scientists, you ll accelerate innovation, improve customer experiences, and streamline your enterprise for the future. View more case studies at statistica.io/resources Statistica and the Quest Software logos and products as identified in this document are registered trademarks of Quest Software, Inc. in the U.S.A. and/or other countries. Other trademarks and trade names may be used in this document to refer to either the entities claiming the marks and names or their products. Quest Software disclaims any proprietary interest in the marks and names of others. Availability and terms of Quest Software, Solutions and Services vary by region. This case study is for informational purposes only. Quest Software makes no warranties express or implied - in this case study. March 2017, Quest Software Inc. All Rights Reserved. CaseStudy-StatisticaDanskeBank-US-AA-00000
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