--- title: Banking & Finance Case Studies | Datamine description: Data analytics for banking improves customer engagement, marketing ROI, business strategy. Case studies for data science success. image: https://www.datamine.com/hubfs/Imported_Blog_Media/Banking,%20Financial%20%26%20Insurance%204.jpg --- [![Datamine](https://www.datamine.com/hs-fs/hubfs/Imported_Blog_Media/Logo-for-website-white-01.png?width=417&name=Logo-for-website-white-01.png "Datamine")](https://www.datamine.com/) - [Working together](https://www.datamine.com/how-to-drive-commercial-growth-with-data-analytics-and-ai-datamine) - [How we work together](https://www.datamine.com/how-to-drive-commercial-growth-with-data-analytics-and-ai-datamine) - [Our Workshops](https://www.datamine.com/envisaging-and-development-workshops) - [Our Pricing](https://www.datamine.com/how-much-does-data-analytics-and-ai-cost) - [Solutions](https://www.datamine.com/oursolutions) - [Case Studies](https://www.datamine.com/industryexpertise/case-studies) - [Retail](https://www.datamine.com/industryexpertise/case-studies/retail) - [FMCG](https://www.datamine.com/industryexpertise/case-studies/fmcg) - [Travel](https://www.datamine.com/industryexpertise/case-studies/travel-tourism) - [Not for Profit](https://www.datamine.com/industryexpertise/case-studies/not-for-profit) - [Media & Entertainment](https://www.datamine.com/industryexpertise/case-studies/media-and-entertainment) - [Telco](https://www.datamine.com/industryexpertise/case-studies/telco-and-technology) - [Utilities](https://www.datamine.com/industryexpertise/case-studies/energy-and-utilities) - [Health & Wellness](https://www.datamine.com/industryexpertise/case-studies/health-and-wellness) - [Government](https://www.datamine.com/industryexpertise/case-studies/government) - [Finance](https://www.datamine.com/industryexpertise/case-studies/banking-and-finance) - [Insurance](https://www.datamine.com/industryexpertise/case-studies/insurance) - [Real Estate](https://www.datamine.com/industryexpertise/case-studies/real-estate) - [Industries](https://www.datamine.com/industry) - [Retail](https://www.datamine.com/industry/retail) - [FMCG](https://www.datamine.com/industry/fmcg) - [Travel](https://www.datamine.com/industry/travel-and-tourism) - [Health & Wellness](https://www.datamine.com/industry/health-and-wellness) - [Not for Profit](https://www.datamine.com/industry/not-for-profit) - [Media & Entertainment](https://www.datamine.com/industry/media-and-entertainment) - [Telco](https://www.datamine.com/industry/telco) - [Utilities](https://www.datamine.com/industry/utilities) - [Government](https://www.datamine.com/industry/government-and-public-sector) - [Finance](https://www.datamine.com/industry/banking-and-finance) - [Insurance](https://www.datamine.com/industry/insurance) - [Discover](https://www.datamine.com/resources) - [Products](https://www.datamine.com/what-we-do/our-products) - [WeekAhead](https://www.datamine.com/weekahead) - [Retailwatch](https://www.datamine.com/ourservices/retailwatch) - [Site Spotter](https://www.datamine.com/ourservices/sitespotter) - [NZ Fuel Prices](https://www.datamine.com/data/fuel-price-nz) - Insights - [Executive Insights](https://www.datamine.com/executive-insights) - [The Boardroom Table](https://www.datamine.com/theboardroomtable) - [Retailwatch Dashboard](https://www.datamine.com/reports/retailwatch-dashboard) - [Telcowatch Report](https://www.datamine.com/telcowatch) - [Downloadable Guides](https://www.datamine.com/resources/datamine-guides) - [Datafix Blog](https://www.datamine.com/datafix) - [The Boardroom Table](https://www.datamine.com/theboardroomtable) - [About us](https://www.datamine.com/about-us) - [How we work together](https://www.datamine.com/how-to-drive-commercial-growth-with-data-analytics-and-ai-datamine) - [The Datamine Story](https://www.datamine.com/the-datamine-story) - [Our People](https://www.datamine.com/being-a-dataminer/our-people) - [Our Values](https://www.datamine.com/en-au/about-us/our-values) - [Our Partners](https://www.datamine.com/company-we-keep-tech-partners) - [Join Us](https://www.datamine.com/being-a-dataminer/join-us) - [Contact us](https://www.datamine.com/contact-us) # Banking and finance case studies ## BANKING and FINANCE ![Banking & Financial-1](https://www.datamine.com/hs-fs/hubfs/Iconography/Black/Banking%20%26%20Financial-1.png?width=45&name=Banking%20%26%20Financial-1.png)   For over 20 years, Datamine has been providing the banking and finance sector with state-of-the-art predictive tools and enhanced analytics.  Over the years, we've helped clients in the financial services industry - such as Westpac, ASB, BNZ, Kiwibank, AMP and ANZ - improve customer engagement, marketing ROI, business strategy and more through the use of data analytics. Scroll down to find out how Datamine has helped Australasia’s leading banking and financial organisations respond to industry challenges and drive competitive advantage.    # WESTPAC MEASURES CUSTOMER SATISFACTION THROUGH 'LOVE SCORE' “Westpac Cards was at a point where we needed to leverage our data to make key decisions about our future marketing investments and strategic priorities.  They provided us with fantastic quality outputs, were always professional and friendly, and gave us insights that enabled us to make some key strategic decisions very quickly and with confidence that we were going down the right track.  I have already recommended Datamine to colleagues in other fields and know that they have been equally pleased with the results." **- ****Head of Call Centres at Westpac** **THE CHALLENGE ** Westpac needed deeper insight into their credit card customers so they could boost card holder profits and reduce churn. **THE SOLUTION** Datamine developed a customer ‘Love score’ so Westpac could measure its customer’s passion for the Westpac brand. The Love model leveraged Westpac’s existing market research Net Promoter Scores (NPS) which Datamine then correlated with customer’s credit card behavioural data, demographics and hotpoints redemption rates – delivering a love/commitment score for every Westpac customer. **THE RESULT ** The love score initiative expanded Westpac’s market research sample results and enabled the bank to segment their credit card customers based on a card holder’s level of ‘love’ for Westpac.  This enhanced the existing ‘current and potential profitability’ models and enabled Westpac to target marketing communications accordingly. # CHURN REDUCTION FOR RETAILER'S FINANCIAL SERVICES DIVISION **THE CHALLENGE** With a product offering that included credit cards, store cards and insurance products, the financial services division of a nationwide retailer wanted to better understand the characteristics of its customers, their location, demographics and profitability - with a specific interest in who was leaving and joining on a monthly basis. **THE SOLUTION** Datamine created socio-demographic and behavioural profiles of cardholders and created several categories to distinguish groups of customers with similar characteristics and behaviours. Datamine provided a suite of management reporting options - providing a window into customer dynamics and profiling the characteristics of clients who were both leaving and joining. The monthly reports also enabled finance team to monitor the change in delinquency levels and balance transfers in and out of the cardholder base. **THE RESULT** Analysis found that 50% of profit was generated by only 15% of customers, signalling a very high value group that needed to be identified and looked after. Datamine were able to show that although the retailer's card spend had increased year on year, the customer base was actually shrinking, due to churn and minimal acquisition. Motivated by the initial findings, the group further tasked Datamine with delivering solutions by which it could assess whether its lost customers were high or low value, and that could also accurately predict likely credit card ‘churners’.  These reports have provided the company with actionable customer insights leading to more accurately targeted marketing and communications initiatives and an increased return on investment. # KIWIBANK ANALYTICS IDENTIFIES OPPORTUNITIES FOR GROWTH **THE CHALLENGE** Kiwibank wanted to understand more about its existing Business Banking customers and how these businesses fitted within the context of the New Zealand SME market as a whole.  This information was intended to help them develop growth strategies, direct their future marketing communications and inform targeted campaigns.  Kiwibank were looking for cross-sell opportunities for their existing customers, as well as geographic and industry areas where there was potential for acquisition. **THE SOLUTION** Datamine analysed the bank’s current market share by region, business size and industry to identify areas where there was potential to acquire more SME customers.  The project also explored the product holdings of current customers and identified gaps that illustrated cross-sell opportunities for Kiwibank.  This analysis identified a particular Kiwibank product that was of high value, despite relatively small holdings across their customer base.  This provided evidence of an area of great potential for cross-sell initiatives that were likely to deliver high returns. **THE RESULT** Kiwibank had already formulated an image of the ‘ideal SME customer’ which was to be taken into account during this analysis.  The project enabled some of the assumptions that formed this profile to be proven correct and others to be debunked. This profiling project has given Kiwibank a clearer picture of growth opportunities and informed their marketing and communications initiatives.  Kiwibank are now able to target geographical areas where they know there is higher potential and industries that they know will be more profitable to have as customers. # FINANCIAL SERVICES COMPANY ANALYSES NET PROMOTER SCORE **THE CHALLENGE** Our client, a large financial services company, has a customer base of around 500,000 people, meaning it can be difficult for them to accurately evaluate customer satisfaction and loyalty.  However, having quantified the economics behind Net Promoter Score (NPS) and the value of promoters versus detractors to its business, they regularly send their customers a Relationship NPS survey. Our client had an overall goal to gain more clarity around the different factors affecting their NPS and focus resources accordingly on aspects of their business that impact customers the most. We analysed the NPS survey sent in July 2017 which generated around 4,500 responses.  The survey included an analysis of the previous year’s responders, proving that promotors had stayed longer and bought more from them. **THE SOLUTION** For this solution, the Datamine team used a statistical approach, explanatory modelling.  There are hundreds (if not thousands) of variables at play behind every NPS, and ranking them shows which ones are critical to a positive performance and which ones aren’t. Datamine analysed the client’s data, which covered product holdings, digital interactions, customer service interactions, marketing communications, tenure, channels utilisation, audio data, questionnaire free format text and more.  Datamine identified the key actions the business can take to have the greatest effect on NPS: - Increase contacts with customers, particularly those with longer tenure - Focus on providing great customer service - Continue to execute targeted marketing activity **THE RESULT** At Datamine, we have long been convinced of the worth of Net Promoter Scores to any organisation wanting to get a snapshot of its customer satisfaction levels, with one caveat: we’ve always thought it had more to offer. Our client agrees, and with their newly gained insight is now investing in areas that will drive NPS, moving forward with a much better sense of customer service and marketing direction as well as the confidence that their efforts will pay off. 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