# Driving customer loyalty in financial services with business-wide data decision-making
Author:  Pal Sinha, Barnali 
Author URL: https://financedigest.com/author/pal-sinha-barnali
Published: 2020-10-06
Category: BUSINESS
Category URL: https://financedigest.com/category/business
Meta Title: The Importance of Advanced Data Strategy in Financial Services
Meta Description: Discover the importance of customer loyalty in financial services, and how implementing an advanced data strategy can drive revenue and improve customer
URL: https://financedigest.com/driving-customer-loyalty-in-financial-services-with-business-wide-data-decision-makinghtml

![undefined](https://prod.superblogcdn.com/site_cuid_cm5qst7v3003gwirgwqtxn8i8/images/untitled-design-2020-10-06t105024-1736838823248-compressed.jpg)

_By_ _Helena Schwenk_ _, Market Intelligence Manager at_ [_Exasol_](https://www.exasol.com/en/community/resources/resource/data-strategy-and-customer-loyalty-in-financial-services/)

Financial interactions have drastically increased over digital channels due to COVID-19, with customer behaviour adapting to the restrictions of a pandemic, where economic constraints are in the spotlight and attitudes towards risk have changed. This makes an advanced data strategy more crucial than ever – particularly for financial services organizations, where the economic pressures are inherent.

Amidst the changes of the last eight months, one thing that remains the same is the importance of customer loyalty. Our survey of senior financial decision-makers found 80% consider loyalty a key priority, given its importance to revenue generation and differentiation from competitors.

If [businesses can organise and analyse their customer data](https://www.financedigest.com/how-can-financial-institutions-make-the-most-of-data-for-their-business.html "HOW CAN FINANCIAL INSTITUTIONS MAKE THE MOST OF DATA FOR THEIR BUSINESS?  ") in a way that allows them to interpret and predict the behaviour of their customers, they will be able to extend their relationship with customers. Research from [McKinsey](https://www.mckinsey.com/~/media/McKinsey/Industries/Financial%20Services/Our%20Insights/Reshaping%20retail%20banking%20for%20the%20next%20normal/reshaping-retail-banking-for-next-normal.pdf) supports this, suggesting that organisations need to rethink how they drive revenue to accommodate new consumer behaviours. This might mean new product offerings or repositioning offerings that are advisory and protection focused.

However, this is easier said than done in a sector that has always been data-intensive due to the breadth and depth of its customer touchpoints, with IDC conservatively predicting a 26% CAGR [data growth in financial](https://www.financedigest.com/data-centres-and-the-changing-financial-trading-landscape.html "Data centres and the changing financial trading landscape") services organisations by 2025. That’s without considering how siloed and difficult to [navigate financial data](https://www.financedigest.com/navigating-consumer-data-in-the-finance-industry.html "NAVIGATING CONSUMER DATA IN THE FINANCE INDUSTRY") can be.

Navigating and interpreting this [data demands a sophisticated data analytics](https://www.financedigest.com/the-importance-of-data-analytics-for-success.html "The Importance of Data Analytics For Success ") strategy. [Financial firms need an infrastructure that enables the real-time analysis of governed and operationalised data](https://www.financedigest.com/financial-services-firms-turn-to-big-data-intelligence-to-fight-fraudulent-activity-according-to-xerox-study.html "FINANCIAL SERVICES FIRMS TURN TO BIG DATA INTELLIGENCE TO FIGHT FRAUDULENT ACTIVITY ACCORDING TO XEROX STUDY"), integrating it business-wide while eliminating the unnecessary silos that slow down analysis.

**Strategy and infrastructure**

The first step in this process is to define the data analytics strategy, so that teams can extract all the insights they need from their organisation’s data. This is fundamental to understanding how to improve business operations, new services and products and, ultimately, customer lifetime value.

A robust data [strategy also offers a view into customer](https://www.financedigest.com/why-equipment-assets-should-be-the-source-of-your-customer-strategy.html "Why Equipment Assets Should Be The Source of Your Customer Strategy") retention, identifying clients at risk of being lost, with behavioural analytics providing the basis of personalised action plans. Improvement in these areas will deliver a more desirable [customer experience and a much-improved understanding of customer loyalty](https://www.financedigest.com/how-do-you-build-customer-loyalty-3-steps-to-follow.html "HOW DO YOU BUILD CUSTOMER LOYALTY? 3 STEPS TO FOLLOW").

This can only be beneficial to an organisation’s bottom line; according to Bain & Co., increasing the rate of [customer retention by just 5% can increase profits by up to 95%](https://www.financedigest.com/ai-will-power-95-of-customer-interactions-by-2025.html "AI will power 95% of customer interactions by 2025").

**The price of loyalty**

Actioning an improvement in customer retention is not as simple as gathering insights. Loyalty is earned, and there are [challenges to overcome](https://www.financedigest.com/overcoming-challenges-faced-in-business-from-one-woman-to-another.html "Overcoming challenges faced in business: from one woman to another").

For example, 54% of those we surveyed suggested that [customers have higher expectations of financial services experiences](https://www.financedigest.com/is-your-customer-experience-exceptional.html "IS YOUR CUSTOMER EXPERIENCE EXCEPTIONAL?") than are being delivered on. 42% agreed that digital disruptors were encroaching on their customer base through new experiences and [business models](https://www.financedigest.com/apis-open-banking-and-new-business-models.html "APIs, Open Banking and New Business Models"), while PSD2 and GDPR frameworks are impacting the ability of 41% to improve loyalty initiatives.

These challenges need to be tackled head-on because the risk of gambling on [customer loyalty](https://www.financedigest.com/financial-companies-delivering-better-value-for-customers-in-loyalty-programmes-compared-to-other-sectors.html "Financial companies delivering better value for customers in loyalty programmes compared to other sectors") is too great. The business impact of poor [customer loyalty is serious in terms of higher levels of customer churn (45%), lost opportunities for customer engagement](https://www.financedigest.com/chatbots-the-secret-weapon-to-customer-engagement.html "Chatbots: The secret weapon to customer engagement?") (45%), and lost opportunities for revenue generation (42%).

It costs five times more to [acquire a new customer](https://www.financedigest.com/can-banks-acquire-customers-with-biometric-payment-cards.html "Can banks acquire customers with biometric payment cards?") than to sell to an existing one, and so these concerns are simply too high a set of risks to ignore.

**Driving for improvement**

The good news is that a more comprehensive understanding of [customer lifetime and loyalty](https://www.financedigest.com/how-will-the-introduction-of-digital-banking-impact-customer-perception-and-overall-loyalty.html "HOW WILL THE INTRODUCTION OF DIGITAL BANKING IMPACT CUSTOMER PERCEPTION AND OVERALL LOYALTY?") is possible. The foundations are already there in the majority of cases; 97% of organisations use predictive analysis as part of their [loyalty initiative and customer](https://www.financedigest.com/the-problem-with-measuring-customer-loyalty-and-how-to-overcome-it.html "The problem with measuring customer loyalty; and how to overcome it") insight processes, with 62% considering it a key component.

This high percentage is proof that data [analytics is maturing in financial services](https://www.financedigest.com/how-crowdsourcing-can-help-drive-the-benefits-of-advanced-analytics-in-financial-services.html "HOW CROWDSOURCING CAN HELP DRIVE THE BENEFITS OF ADVANCED ANALYTICS IN FINANCIAL SERVICES"). 96% are very positive about their firm’s data strategy and almost two thirds (65%) agree that data [analytics enable them to predict](https://www.financedigest.com/transportation-predictive-analytics-and-simulation-market-2021-by-global-key-players-types-applications-countries-industry-size-and-forecast-to-2027.html "Transportation Predictive Analytics And Simulation Market 2021 by Global Key Players, Types, Applications, Countries, Industry Size and Forecast to 2027") the future behaviour of customers and offer personalisation.

Although, 48% believe that their data strategy could be improved, showing an appetite for progression. Things are improving, but many are not yet demonstrating their [full potential](https://www.financedigest.com/embedded-finance-is-the-new-norm-in-banking-but-what-is-needed-to-unleash-its-full-potential.html "Embedded finance is the new ‘norm’ in banking, but what is needed to unleash its full potential? ").

**What’s possible**

One financial organisation fulfilling its data potential is [Revolut](https://www.financedigest.com/the-digital-finance-revolution-empowered-consumers-turn-digital-to-protect-financial-security.html "The digital finance revolution: empowered consumers turn digital to protect financial security"). As one of the UK’s unicorn companies it is no stranger to explosive growth, with data volumes [growing 20-fold within a 12-month period](https://www.financedigest.com/global-tool-holders-market-is-anticipated-to-reach-over-us-1604-5-mn-by-the-end-of-the-projected-period-growing-at-a-cagr-of-5-1-fmi.html "Global Tool Holders Market is anticipated to reach over US$ 1,604.5 Mn by the end of the projected period, growing at a CAGR of 5.1%: FMI").

![Helena Schwenk](https://prod.superblogcdn.com/site_cuid_cm5qst7v3003gwirgwqtxn8i8/images/hschwenk-1736838822973-compressed.jpeg)

Helena Schwenk

Such growth made the maintenance of 800 dashboards and fielding over 100,000 SQL queries on a daily basis very challenging. To cope, Revolut transitioned to an in-memory data analytics database that suited its need for a flexible, [hybrid cloud environment](https://www.financedigest.com/how-to-manage-identity-in-a-hybrid-cloud-environment.html "How to manage identity in a hybrid cloud environment").

By acting as a central data repository, the database has saved [time across multiple business units as is now able to resolve queries and reports](https://www.financedigest.com/credit-suisse-executives-reassure-investors-after-cds-spike-financial-times-reports.html "Credit Suisse executives reassure investors after CDS spike, Financial Times reports") in seconds instead of hours. According to Revolut’s data scientists these query times are now 100x faster than with their previous solution. This improves decision-making and allows Revolut to explore customer demographics, debit card statements, online and mobile transfers, and [payment and point-of-sale data](https://www.financedigest.com/understanding-the-realities-of-payment-data-monetisation.html "Understanding the realities of payment data monetisation") in almost real-time.

Moreover, every employee has access to this repository as a ‘single source of truth’. This data is available for interrogation too, with [business intelligence](https://www.financedigest.com/social-business-intelligence-market-to-reach-a-valuation-of-us29-bn.html "Social Business Intelligence Market to reach a valuation of US Bn") (BI) tools and self-service access available to everyone as opposed to just the data scientists. [Key performance indicators](https://www.financedigest.com/alanine-market-key-players-swot-analysis-key-indicators-and-forecast-to-2029.html "Alanine Market Key Players, SWOT Analysis, Key Indicators and Forecast to 2029") (KPIs) were based upon this data as well, standardising performance goals for everyone across the entire organisation.

As a result, Revolut has defined tens of thousands of micro-segmentations within its customer base, built ‘next product to purchase’ models that increase sales and customer retention, and delivered granular personalisation to over 13 million users.

**Beating the competition**

The same principle applies for traditional banks or young start-ups: offering quick, easy and satisfying [services to customers](https://www.financedigest.com/how-customer-services-has-changed-during-covid.html "How Customer Services Has Changed During Covid") to drive retention is paramount. By using data to identify and predict customer trends, organisations can learn where to differentiate themselves from competitors and deliver the right products and services at the right time.

Whether [data is stored in the cloud](https://www.financedigest.com/normalizing-advanced-cloud-data-security-with-normalyze-from-amer-deeba-and-ravi-ithal.html "Normalizing Advanced Cloud Data Security with Normalyze from Amer Deeba and Ravi Ithal"), on-premise or both, the right data analytics database – backed by a committed and robust data strategy – is key in a post-COVID world. It must emphasise the optimisation of the collection, management and integration of [data to empower users to be more informed and more efficient for business-wide benefits that drive](https://www.financedigest.com/how-alternative-data-drives-e-commerce-success.html "How Alternative Data Drives E-commerce Success") loyalty and last.


---
This blog is powered by Superblog. Visit https://superblog.ai to know more.
---