From personal banking services to wealth management, how is data analytics reshaping the GCC banking sector?
Advanced data analytics enable businesses, including banks, to enhance decision-making, improve service delivery, and tailor the service to growing customer expectations. By understanding customer’s needs, the banking sector can have a more accurate picture of its community of customers to serve them better. The adaptation of the business products via customer data analytics coming from the customer perspective will bring a real and meaningful impact on the banking sector’s future.
At NBF, our strategy has been to respond to change with agility and thrive on it to enhance and strengthen our offering. Digital transformation has been sitting at the very centre of its development journey. Over the years, we have been working tirelessly to ensure the user experience reflects enhanced efficiency, better security and resilience, and faster or instant servicing. Our new branches are increasingly becoming more digitised and our customers have responded well to emerging technology. Moreover, we have been integrating automation and robotics to eliminate paperwork from banking processes and on the corporate banking side, developed trade finance payment facilities and other digital platforms to continue enhancing our offering.
A great example of this is our latest innovation, NBF CONNECT, a platform that has been co-created alongside the SME community. We have long recognised the indispensable value that SMEs bring to the country’s economic engine. With COVID-19 accelerating the digital world’s transition, we wanted to step in and be the first to help digitize this vital sector. As such, we joined forces with SMEs to build a platform that meets their business needs and helps them navigate their growth-journeys.
What security and data privacy risks are emerging as a result of a pandemic-driven customer data gold rush within the GCC financial service sector?
Proper data analysis will help us serve our customers better and ensure successful customer experiences. As one of our focuses is SME businesses, we have launched the NBF CONNECT platform to enable B2B transactions and other systems based on customer feedback. All this information is flowing through different channels, including customer feedback, and is analyzed in our CRM in terms of customers’ needs and requirements.
As mentioned correctly, the data gold rush is assisting in better customer service, and the emerging risk continues to be about data leakage and Identity theft, especially by using social engineering (Phishing emails, WhatsApp messages, fake/lucrative advertisement using social network channels) to penetrate people and systems. We at NBF follow strict data protection mechanisms, as we ensure data observation is moral, ethical, legal and fair. In addition, we configure stringent access rules – need to know – and configure the data leakage systems to protect this information from potential incidents. Also, as part of our corporate social responsibility, we conduct various awareness sessions for our customers.
What does clean data mean? And how are regional banks synchronizing consumer data and their customer relationship management to meet their clients’ evolving demands amid the impact of COVID-19?
Acceptance of Data as an economic asset is well-recognised. It can be listed as one of the key agendas for discussion by boards and management committees of organisations globally. Data and contextual information generated from that have now become a basis for organisations to make more effective decisions, thereby benefiting from operational efficiencies and increased business value. However, it is also a fact that data which has not been managed effectively has resulted in organisations losing time, money and effort.
Clean data is a set of data ready for analysis after removing or modifying incorrect, incomplete, irrelevant, duplicated or improperly formatted data. The information that are removed or modified are usually unhelpful when it comes to analyzing data, as it hinders the overall process and results in producing inaccurate results.
Data cleaning is not merely about erasing information to make space for new data, but instead finding how to maximize a data set’s accuracy without necessarily removing information. Having clean data, i.e., ensuring that the data is fit for purpose, depends on the data management practices followed by an organisation that, to name a few, includes metadata and master data management, stewardship framework, data quality rules, etc.
It begins with managing the quality of the data through well-defined data governance policies & standards that are embedded in the organisation and robust technology & system architecture ensuring that the various stages of the data life cycle (capturing, cleaning, classifying, storing, using and disposal) are managed in the best possible manner. Leadership commitment towards these objectives goes a long way in ensuring that the data’s health and reliability are maintained at all times.
As a result of the COVID-19 pandemic, all industries are closely following how this will affect consumer and business behaviour and preferences in the short, medium and long-term. Many surveys are conducted to understand how COVID-19 pandemic reshaped customers’ behaviours. Below is the finding by The Banking Experience survey conducted by Mintel-Comperemedia in the USA.
Key Findings:
- 50% of consumers & 76% of businesses said the COVID-19 pandemic changed how they interact with their financial institution.
- Of these respondents, 66% of consumers and 73% of businesses feel that these changes will be permanent.
- Nearly half (42%) of consumers expect automated tools to support their financial wellness based on the insights that their bank has about them. Additionally, 52% of consumers are comfortable using a chatbot or virtual assistant to perform banking activities.
- Nearly three-quarters (73%) of respondents said their bank should be recommending specific products/solutions based on the information they have about their business.
- When business leaders were asked what solutions, they expect their bank to provide in the future, the three most popular choices from business leaders were:
- Virtual assistants to help manage company finances (60%),
- Secure mobile-optimized treasury management platforms (54%),
- Secure online treasury management platforms (52%).
Here are some examples on how regional banks are synchronizing consumer data and their customer relationship management to meet their clients’ evolving demands
| Data & digital initiatives | Action taken by Banks |
| Digital transformation | Developing digital customer acquisition platform |
| Blockchain-based KYC | Platform designed to enable businesses new to the UAE to open accounts entirely digitally. |
| Leveraging customers demographic and transactional data | Displaying personalised banners, including products and services customers may need in a crisis or otherwise |
| Leveraging customers demographic data | Identifying the vulnerable ones (like self-employed, high-debt, old-age customers, etc.) and reaching out to them with customised products and helpful advice. |
| Service usage behaviour | By leveraging branch locator pages, ATM listings in Google and more, to drive users who are potential branch visitors to online channels. |
| Interest clusters & AI | Creating COVID-Sensitive Products & Services to the right beneficiaries. For example – Payment holidays, moratoriums for loans, relaxation in EMIs, less stringent KYC norms, waiving minimum balance charges. |
How do you envision consumer data mining in the next decade? And how can GCC banks leverage analytics to explore new avenues of growth or new business models?
Extracting meaningful information through the process of data mining is widely used to make critical business decisions. In the coming decade we can expect data mining to become as ubiquitous as some of the more prevalent technologies used today. Some of the key data mining trends for the future include:
- Multimedia Data Mining: It involves the extraction of data from different kinds of multimedia sources such as audio, text, hypertext, video, images, etc. and the data is converted into a numerical representation in various formats. This method can be used in clustering and classifications, performing similarity checks, and to identify associations.
- Ubiquitous Data Mining: This method involves mining data from mobile devices to get information about individuals. This method has a lot of opportunities to be enormous in various industries, especially in Banking.
- Distributed Data Mining: It involves mining a considerable amount of information stored in different company locations or at other organizations. Highly sophisticated algorithms are used to extract data from different locations and provide proper insights and reports based upon them.
- Spatial and Geographic Data Mining: Extracting information from environmental, astronomical, and geographical data also includes images taken from outer space.
- Time Series and Sequence Data Mining: This type of data mining is based on cyclical and seasonal trends and analyzing random events that occur outside the regular series of events.
The spurt of big data has opened enormous opportunities for the banking sector to grow. Looking at the tremendous impact of analytics and how it has completely transformed banking functions, it should be considered an essential part of every initiative. GCC banks can leverage analytics capabilities at scale to achieve a new level of customer understanding and targeting. Applying digitization at scale can deliver an almost seamless integration of banking services into clients’ daily routines.
Some key banking analytics to explore new avenues of growth
- Better Personalization with Rich Data: Clustering of customer base with advanced criteria, where human-centric, design thinking pillars and CRM tools help banks match customer needs to real-time solutions.
- Digital-only Banking: With the high cost of a physical branch network and an increasing number of customers switching to digital channels, digital-only banking entities are growing rapidly. More and more banking organizations are expected to move to digital-only banking in 2021 to protect their customer base and expand their market share, empowered through open banking APIs and cloud technologies.
- AI-Driven Predictive Analytics: The banking industry can consolidate both internal and external customer data that is rich and financially viable, not only to know their customers but also build their predictive profiles. With the enhanced use of data, banks will provide consumers with value driven services through next best actions, instead of blind selling products as they will be able to minimize customers churn, fraud and money laundering.
- Payments Infrastructure: Payments infrastructure will always remain the most active area of innovation in the banking industry. Driven by dynamic consumer expectations and technological changes, innovations in the payments industry will persist. The driving force behind the differentiation will be data and technology, changing the dynamics of payments.
Sources:
https://www.flatworldsolutions.com/data-management/articles/data-mining-future-trends.php
