Article | January 27, 2022
Marketing—even the best marketers can become victims of a faded ROI. It usually happens when you pick an incorrect marketing strategy or implement it into your marketing model. Due to this, it becomes evident that your business will witness a considerable ROI loss.
What if there were efficient ways to evaluate the right marketing practices before implementing them into your business?
The time has come to implement tech-based marketing practices and actions into the marketing space! In this aspect, AI in finance is integral. Banks, financial institutions, businesses, and service providers need to deploy AI at scale to remain relevant to their business module, automatically improving ROI generation.
So, how can the C-suite use the power of AI in banking and finance marketing to increase or improve ROI?
This article will help C-suite executives like you understand how AI can generate ROI by implementing it correctly.
Why Banks Must Become AI-Enabled?
McKinsey estimates that AI technologies can increase valuation by $1 trillion in global banking each year. According to a Business Insider survey, the potential cost savings and ROI for banks from AI applications will be $447 billion by 2023.
AI Challenges that Coursed with Time
Many banks have even struggled to scale AI across the entire marketing model beyond experimentation. This struggle was due to a lack of a strong AI strategy, fragmented data and uneven data management systems, obsolete operating models, and inflexible and investment-starved technological strategies.
The Rising Scenario of AI in Banks
Several digital engagement trends and technologies stood out during the pandemic. It would be wrong to disagree that businesses are now in the AI-driven digital era. This helps reduce data storage and operational costs, improved connectivity and accessibility of networks, and other rapid advances in AI for finance.
Based on the benefits of artificial intelligence in business, the technology leads to better automation and risk mitigation, which can often outperform human decision-making in terms of rapidity and accuracy. This results in boosting ROI.
Therefore, banks and financial businesses must become "AI-enablers” to compete and thrive. In addition, marketers should embrace AI technologies as the foundation for new and valuable plans to provide diverse customer experiences.
How Can Banks Become AI-Enabled?
Rethink Customer Engagement
AI in banking and finance marketing will aid in the development of personalized, hyper-personalized, and intelligent products and services with new features. The marketing attributes will add more intuitive interactions and advisory capabilities.
Make AI-Powered Decisions
According to Accenture's Banking Technology Vision 2019 study, about 78% of bank marketers believe that AI will simplify user interfaces, letting banks provide a more personalized customer experience.
This study paves the way for efficient AI-powered decisions for futuristic banks. When banks use machine-learning models to interact with each customer in real-time, they can add value in four ways:
Stronger customer acquisition
Reduced operating costs
Reduced credit risks
Higher customer retention and valuation
Providing innovative financial services
By enabling AI in marketing strategies, banks can reap benefits from organizing their efforts by redesigning and building highly flexible and fully automated layers of decisions around four elements:
Scalable development and deployment of advanced analytics (AA) and machine learning (ML) models
Augmenting AA and ML models with “edge” capabilities to reduce costs, enhance and streamline customers’ or clients’ overall experiences
Leveraging AA and ML models for automation, mainly referring to personalized decisions across the customer life cycle and to target potential customers
Strengthen the Integral Technology and Data Management
This refers to the extraction of customer data based on their needs and requirements from various data streams to generate relevant and personalized services from a mass of unstructured data. The entire process necessitates data management, which AI excels at.
Budding AI Opportunities for Increased ROI
In 2019, a report by Deloitte titled “AI: Transforming the Future of Banks” highlights the massive opportunities for AI in banking and finance. It further elaborates on how AI can transform the financial services industry. The research further mentions:
AI presents a plethora of opportunities for financial services organizations, who can better meet regulations, escalate their ROI, improve the customer experience by enabling personalization and leverage their growing data repositories."
Jim Marous, Co-Publisher of The Financial Brand and CEO of The Digital Banking Report
Let’s get some insights into the real-time budding opportunities for financial markets in terms of AI.
Detection of Frauds
AI systems are particularly good at evolving fraud detection methods. Marketers benefit by detecting irregularities in the whole business cycle, which improves ROI generation. Irregularities such as expenditure, pricing, investments, and others can now be detected instantly with the help of AI.
Traders worldwide are experiencing a new trading landscape where AI-based trading decisions have become even more accessible. AI's ability to detect the most recent trading trends and market status based on relevant data is becoming the benchmark.
Using AI, traders can now create advanced portfolios and gain insights for various types of investors based on their risk tolerance, developing markets, and investment valuations. With the addition of AI, all of these lead to effective decision-making while trading, boosting ROI.
Smooth Customer Identification
Financial organizations such as Capital One and U.S. Bank are leveraging AI in their operations to identify their customers and provide their services worldwide.
AI can facilitate customer identification and authentication. This will automatically strengthen customer relationships, and marketers can provide personalized services. But how? The answer is by using ML algorithms.
ML algorithms in AI monitor user behavior and derive valuable insights based on customer search patterns. These insights would aid bank service providers in providing personalized recommendations to customers, which would boost engagement and reflect on the ROI.
Lowering Costs and Increasing Revenue
According to Infosys, the leading opportunity for AI is in automating the frontline.
The benefits of artificial intelligence in business are automated engaging with customers and significant cost savings."
Virtual assistants for customers and back-office robotics will become an integral part of the operational systems of future banking.
AI in Banking: Organizing a Successful Future
You can’t deny that every change or revolution brings challenges with it. While some businesses still strive to implement AI in banking and financial services, they must look beyond the hype and consider practical applications of AI to increase revenue and create a cohesive and productive business.
The growing use of AI promises to impact the finance and banking industry long-term. AI in finance is making significant strides in implementation and adoption, which can accomplish more efficiently than legacy systems.
Frequently Asked Questions
What is the future of AI in banks?
In the future, AI will enable banking operations through alternative interfaces such as voice, gestures, neuro, VR, and AR. Incorporating these banking solutions will bring a new change and a whole new service landscape for customers globally.
Why do banks need AI?
AI necessitates streamlining banking operations to keep up with the fast pace of other businesses, especially in the aftermath of a pandemic. The transformation is required to boost ROI, provide greater levels of business valuation, reduce risks and remain competitive.
Is AI going to help the finance industry in the future?
The benefits of AI in the finance industry are promising. In most cases, it has increased business profits through efficient customer targeting, automation of repetitive tasks and processes, and faster services to end-users.
Article | May 16, 2022
“Blockchain has remarkable potential for financial institutions, changing and releasing novel abilities to transform financial institutions and banks to interact and collaborate with customers.”
- Max Di Gregorio, Financial Head of PwC, Middle East
The potential of blockchain has piqued the interest of the financial sector in particular. Its distinct functionalities have enabled financial institutions to operate more promptly and inexpensively—reducing their error rate, lowering their capital requirements, and at the most, their vulnerability to cyber-attacks. A survey by Gartner of 251 CFOs and other finance leaders in November 2021 revealed that 47% of businesses were ready to assess blockchain technology in 2022.
An interesting study by Santander FinTech reveals that distributed ledger technology (blockchain services) can reduce costs by approximately $15 billion to $20 billion per annum by 2022, primarily by reducing IT costs.
Businesses looking for ways to cut costs must understand the core mechanisms of blockchain to encourage the next generation of financial innovations.
Blockchain Driving Value in Financial Services
The current enthusiasm for blockchain and the subsequent years of rapid development have provided the finance industry with opportunities to reflect on its successful operations worldwide. Moreover, blockchain has also provided banks with the ability to identify viable and valuable developments in the widespread and growing financial services landscape. Let’s identify some areas in which blockchain technology is revolutionizing banking services:
The benefits of blockchain technology are mostly reducing, not eliminating, fraud in claim management. Also, blockchain is highly recommended for storing historical claims data on the ledger technology. This enables insurers to detect suspicious activity and improve fraud detection easily.
Claim management data controlled under blockchain technology is registered and administered by smart contacts in a particular network.
The potential areas of claim management to benefit from blockchain services are:
Interpreting incidents claimed in banks
Soliciting excessive claims cover
Uncovering the process of delayed pay-out
Diminished profitability from excessive or lower pay-outs
Due to these unfortunate instances in the claim management process, the FBI studies that over 700 insurance companies in the U.S. receive over $1 trillion annually in premiums. The estimate of the total cost of insurance falls under the heading of fraud, valued at more than $40 billion annually.
This indicates how critical it is to promptly develop an intellectual capacity to recognize fraud in the banking system.
Blockchain in financial services eliminates untrusted parties in financial institutions and banks. Based on its efficient database, it has removed the status of a middleman.
At the same time, blockchain facilitates the use of “smart contracts,” which are self-executing contact systems for automating manual processes. The technology covers everything from compiling claim data to providing relevant claims to customers. In this way, businesses can reduce the costs of manual processes that require multiple employees, assets, and infrastructural needs.
Apart from this, blockchain in finance has massive opportunities by transforming some of the essential traditional services of banks, including:
Legal Management and Regulatory Reporting
With blockchain, data accumulation can be stored and protected simultaneously while removing asynchronous reporting cycles across regulatory, statutory, and management reporting.
A blockchain-based initial coin offering (ICO) has garnered popularity as a new financing model in fundraising. In this model, smart contacts are generated, which results in reduced costs that stay in demand and encourage non-stop trading globally.
Blockchain technology has simplified trading by storing transaction-related documents in a database. As a result, it eliminates the need for multiple copies of documents, plummeting operational costs to a bare minimum. The technology consolidates all data into a single sizeable digital document that can be modernized in real-time and accessed by all network users.
Ornua, an Irish dairy product manufacturer, partnered with Barclays to accomplish the world's first blockchain and banking trade transaction in 2019. Similarly, IBM and Maersk teamed up in 2020 to develop the first cross-border, blockchain-based supply chain system.
Digital assets can be distributed more quickly than paper-based or physical assets. Their electronic format assists in streamlining the transaction process and reducing administrative and physical storage costs.
Digitized assets such as stocks, shares, and funds can be managed end-to-end on a blockchain or existing systems through application programming interfaces (API). Keeping digital assets reduces substantial business costs and allows CFOs to invest in other costs to improve business ROI.
Where does Blockchain Fit in Finance?
According to a recent Deloitte 2020 Global Blockchain Survey, 84% of financial experts responded that blockchain will eventually reach mainstream adoption in the finance sector by 2023.
However, other financial experts also mentioned that 29% of businesses are still skeptical of blockchain implementation. They are considering a “wait and see” strategy. According to them, blockchain services are not among the top five strategic priorities for their businesses. At the same time, 21% of businesses are clueless about where to begin with blockchain technology implementation in their businesses.
Therefore, CFOs should consider implementing blockchain services that will provide a better understanding of the technology. They can then identify and prioritize the financial pain points that the technology can potentially address. To begin with, here are some ways to better understand blockchain usage.
Blockchain mainly benefits financial businesses in terms of crowdfunding projects and security generation. With built-in authentication keys and distributed networks, blockchain addresses some of the most critical vulnerabilities in the IT infrastructure of banks today. This mostly refers to the centralized systems that prevent hackers from hacking and controlling a bank's network.
Facilitating Faster and More Affordable Transactions Internationally
Ripple, a blockchain services company provider, is the most notable player operating in international transactions. Even so, the company is best known for its cryptocurrency platform because it uses blockchain-based global solutions for affordable money transactions.
The centralized blockchain network enables the transaction process seamlessly, popularly using SWIFT mode. That means, instead of relying on a network of complicated services and correspondent banks, international transactions can be settled directly on a public blockchain. Again, this helps alleviate the high cost of maintaining a global network of correspondent banks.
“SMBC lately initiated live transactions on the Marco Polo platform in Japan with major Japanese exporters. We hope to provide effective blockchain-based finance solutions to our customers globally by collaborating with Marco Polo Network.”
- Mr. Kazuo Yoshimura, Managing Director & General Manager, Global Trade Finance Department
In a nutshell, blockchain has the potential to revolutionize the finance function. It will provide CFOs with the tools and capabilities necessary to become key business partners in the strategic planning process while running a highly efficient and trustworthy operation.
Frequently Asked Question
Why is blockchain essential in finance?
Blockchain technology provides better capital optimization by reducing high operational costs. When banks share a blockchain, the entire functionality of the banking system reduces the initial individual costs required for managing transactions at a bank.
What is blockchain used for in banks?
Blockchain in banks is used for both public and private networks. It can be implemented in the financial cores by adding new services, transactions, accounting, and other features. It allows customers to do faster, more secure, and cost-effective transactions.
How does blockchain benefit banking and financial systems?
Blockchain technology improves payment transparency, trust, efficiency, and security and reduces costs for financial services firms and users. Now, payments from one bank to another can be made instantly.
Article | March 17, 2021
Risk events in the banking sector and financial institutions can trigger huge losses. Risk events can be managerial, technological, security, and operational. With these operational hazards, the need for protection rises in banks simultaneously. Banks need to function seamlessly, faster, and more accurately in such circumstances.
According to a report by Barclays, prominent banks worldwide have suffered nearly $210 billion in losses from operational risk from 2011 to 2019. Most of these losses were caused by unavoidable errors made by employees and systems when interacting with clients, transactional flaws, and fraud.
Since the global financial crisis, including the pandemic, banks and other financial institutions have become highly observant of their efficient risk management needs. As a result, banks can use techniques to anticipate and fix risk events before or at the right time. However, some strategic risks or challenges still prevail. Let’s understand what those are first!
Strategic Challenges in ORM
Risk management in banks and financial institutions has always been a complex function. Out of which strategic risks are mostly recorded. What are the most prominent strategic risks that banks usually suffer from?
Large & Complex Data Processing
The processing of large and complex data risks puts banks under pressure to monitor exponentially. Most banks still face the challenge of collating extensive customer data, data inputs, processing, and unreliable and dysfunctional tools, which results in the loss of potential clients and fees.
Inefficient Risk Identification Parameters
Most banks do not have risk management tools like KRIs, KCIs, and KPIs. As a result, they are inefficient and do not have a holistic view of the data, which leads to inappropriate risk identification. Further, most banks also do not have consistent risk management protocols across their business, which poses a significant risk to the operational infrastructure of those banks.
Loss of Data Management
Loss of data is also an essential risk that banks face several times. Data management is an integral part of the banking operation, which means it needs core risk management strategies to keep it secure. Data management includes several functions, but the most essential is maintaining data records securely. This is one of the prime risks that banks, even today, keep a close eye on.
The Current State
While banks have been aware of operational risks, they need to be prompt in adapting risk management capabilities and tools to eradicate the complexities and introduce smoothness in the workflow. Currently, banks have developed taxonomies on risk-identification and risk-assessment processes, extensive controls through cloud support, and cyber and control-testing procedures.
While the banking industry practically succeeded in reducing the industry-wide regulatory system, there are now fewer losses from operational risks in banks.
"In financial services, if you want to be the best in the industry, you first have to be the best in risk management. It's the foundation for every other measure of success. There's almost no room for error."
John Stumpf, chairman and CEO of Wells Fargo
Integration of ORM Strategies
Evaluate Risk Profile
Every financial institution and bank should assess their risk profile to reduce operational risks and improve information security. It should also evaluate the resilience of its business processes, map them to associated risks and controls, and build a database of potential operational risk events. To facilitate this under operational risk management, deploy analytics into the process and evaluate potential threats at a particular time. In this way, banks can minimize risk factors in the future.
Introduce Risk Indicators
Most banks examine their sales-operating models meticulously because of regulatory concerns about sales practices, such as product features, incentives, sales procedures, frontline-management routines, and customer-complaint processes.
Risk management in the banking sector can now be possible as banks can enhance their operational risk coverage with the help of the ‘three lines of defense” model. This model is widely used to define and manage operational risks. It is a solution framework that functions at a granular level to help identify and control risks. The target framework should include sources of risk that most banks lack, such as:
A clear definition of accountability at each level of the risk plan
Established levels of communication and feedback from various levels of management
Uniform monitoring of all potential risk exposure sources, such as portfolio management, employee tracking, or even disaster management
The key objective for banks is to move beyond legal risks and focus on all business processes to ensure they are covered fully for the future.
Initiate Training for Employees
Employees play an integral role in managing operations in banks and financial institutions. Therefore, to ensure the effectiveness of the same, employees can be given training on operational risk management programs and functions of management programs to make them aware of the potential risks and ways to overcome them. This is extremely important for those banks and financial institutions looking to launch a new customer interface, roll out new products or services, or adapt new business processes with technology implementation.
Asset management is one of the essential parts of operational risk management in banks and financial institutions. So, for asset management, bank managers should be concerned about two major things—the role of asset management and how to develop a good plan for managing assets. Asset management identifies and manages risks that arise when certain assets are used.
To exclude risks in bank operations, a fundamental strategic asset management plan will include the following six phases:
Acquisitions (including leases or rentals)
Risk assessment and management
After these phases have been covered, banks must count their assets. Here is the following inventory of assets that need to be included. They are:
Total count of assets
The value of each asset
Details of acquired assets
The expected life cycles of the assets
Banks can easily implement a robust risk management plan for future safety by accessing all of them.
A Comprehensive Approach to ORM
Banks taking a comprehensive approach toward building an ORM (operational risk management) framework can bolster business growth rapidly. The first step to creating a productive ORM capability is to access the existing risk potential in banks. This would help banks create a base out of all internal and external risk events. Then, to deal with the different types of risks, the development of key risk indicators (KRI) will serve as early warning signals to potential risks. Once the banks successfully identify it, they can decide on mitigation options.
Next, the question arises, how can financial businesses and institutions establish a robust ORM for risk management in the banking sector? The key to establishing an effective ORM is training employees to anticipate future risks, especially during the launch of products, changes in customer interface, outsourcing services, or shifting the core of a business module.
As banks and other financial institutions have embraced agile work modes, ORM experts have become an integral part of the operation. Like, JPMorgan Chase, ORM lies at the heart of all its processes. It is where the bank develops and tests new business offerings and practices to check the potential risks in the following. In addition, other U.S. banks have built a dedicated cyber-risk team that simulates attacks and takes action to prevent potential operational risks.
However, identifying and alleviating operational risk is a significant and crucial task that needs to be left only to the ORM experts.
A Move Forward with the Operational Risk Management Framework
The components of risk management in banks examined above have proved beneficial for the operational risk management function.
Operational risk management in the banking sector should ensure that an institution's operational risk framework is reliably implemented and performs well. The institution should ensure that the framework provides thorough coverage across the various operational risk event types and conduct ongoing support for individual components and the overall operational risk framework.
Businesses and financial institutions should leverage the operational risk management framework as part of a broader effort to improve sustainability, including estimation of forecasting efforts. Therefore, the operational-risk discipline can create a more secure and profitable institution in the future.
"The art of banking is always to balance the risk to run with the reward of a profit”
Jamie Dimon, chairman and CEO of JPMorgan Chase
Frequently Asked Question
What are the most prominent operational risks in banks?
Process risk, systems risk, external event risk, and legal and compliance risks are the significant operational risks in banks.
What is the primary function of operational risk management?
The primary function of operational risk management is to reduce risks through risk identification, measurement and mitigation, risk assessment, monitoring and reporting.
How to identify operational risks in banks?
Banks must assess and manage operational risk using various tools and strategies. Banks identify potential operational risks in the following ways:
Business disruptions and systems failures
Accounting or data entry errors
Inaccurate client records
Article | April 29, 2022
Digitalization is a high-priority initiative that has uplifted the banking industry by exploring new profitable areas. However, the strategies for becoming digital must rely on efforts to focus on making a bank’s administration and internal operations more efficient. Digitalization refers to a wide range of tools that can create personalized and hyper-personalized experiences for people.
How Banks Have Evolved with Technology Implementation
The banking industry has been consistently embracing technological advancements. Since 2020, banks globally are making heavy investments in digitalization and are focusing on efficient banking operations. With the help of digitalization, the banking and financial sectors are going through a paradigm shift and are progressively offering personal touches to their operations, services, and products.
Most banks now offer digital features that allow customers to conduct basic banking activities remotely using a browser or a mobile app. This development has resulted in less traffic at bank branches and has assisted banks in optimizing costs and capital expenditures fairly. Hyper-personalization in banking is becoming increasingly important. As a result, the use of technology in banks has equally surged, mainly in operations and customer services.
Hyper-personalization has become an essential part of banks and other financial services providers. With this, banks are now focusing on core customer experiences to provide unique services to their customers. Today, new-age customers need hyper-personalization in banking.
In 2020 ‘The Future of Retail Banking,’ A Deloitte report has stressed that hyper-personalization is crucial for banks and enables them to respond to customers’ basic needs.
While this approach is widely accepted in the banking system, let’s understand a brief difference between hyper-personalization and personalization and which method is more enticing to customers.
Personalization vs. Hyper-Personalization
Personalization focuses on promoting a customer’s name, location, purchase history, buying behavior, and others. The most common example is including the first name of a customer in an email or promotion asset.
The hyper-personalization approach uses a customer’s browsing habits and then reveals real-time behavioral data to determine customer needs. The entire activity builds contextualized communication and encourages more incredible conversions driven by AI and aligned data. For example, they send push notifications to customers, adding high-engagement sections on the website—chatbots.
Therefore, it is evident that personalization banking will be further enhanced and become more personal with hyper-personalization. According to a study by Deloitte, banks are ready to embrace digital opportunities, which would be advantageous for over a trillion dollars. The movement will continue until 2025 and beyond.
Growing Expectations from Customers
Since 2020, banks worldwide have been striving to improve their customer experience and business operations. The digital transformation of the banking sector has changed consumer banking trends. This gives rise to one of the main concerns — what are the top priorities for customers regarding banking services? According to a survey by Wipro, 80% of customers expect their banks to provide upgraded services with improved products and easily accessible apps and websites. At the same time, 20% of customers hope banks have valuable services to benefit them. In addition, 5% of them expect improved communication channels for distributing products and services.
On the other hand, according to a recent Salesforce survey, two-thirds of today's customers expect their banks to understand their unique needs and expectations. Moreover, up until 2021, 52% of customers found hyper-personalized offerings from their banks. Therefore, banks must extensively use customer data to anticipate customers’ banking needs.
Gartner estimated that approximately 48% of customers want value-added services, making hyper-personalization engagements of strategic relevance. This was followed by personalization in banking with products and services.
When it comes to using hyper-personalization in banking, Capital One, a U.S.-based company, stands out. It is one of the finest examples of digital marketing. It usually sends notifications to clients, assists them with simple tasks, sends new offers, and efficiently manages personal finances. In addition, they are currently using geolocation technology by partnering with several retailers. With this, they can reach customers and provide them with purchasing offers.
The Marketers’ Complications
What were the practical problems or challenges for marketers approaching their customers right away?
Markets face several roadblocks to achieving the desired level of personalized customer engagement. Some of these challenges include:
Profile: Marketers usually face challenges in categorizing, compiling, and saving online and offline customers’ data.
Identity: Marketers must deal with the fragmentation of customers' identities and how they see them across devices and channels.
Relevant Communication: Marketers often fail to reach people at scale across different channels with relevant information.
Measurement: Marketers often complicate the accuracy of measuring customer behavior, buying habits, and needs.
Therefore, marketers need to sort out these parameters and then proceed strategically to deliver hyper-personalized engagement to customers. Now let’s find out how to do it.
Emerging technologies, mainly AI, data analysis, automation, and blockchain, give an insight into customers’ needs, behavior, and activities like transactions, money transfers, deposits, availing insurance, and other banking activities. Marketers can leverage these technologies, crack code, use hyper-personalization in strategies, and work to meet customers’ needs.
There are a series of interconnected strategies following technology in banking that will enhance the use of hyper-personalization in banking in the future. It will enable customers' digital requirements according to products and services and identify intent-based customers in the banking system.
Series of Interconnected Strategies
Having an accurate identification of customer profiles and details determines how to proceed with hyper-personalization. First, you must build a digital identity solution that links customer data across devices and locations. After this, study and get profound customer insights with the help of a third-party customer database to obtain accurate customer information such as:
Online and offline purchases
Cross-device information according to the usage of personal devices
By identifying these parameters, marketers can effortlessly create a community for their highly engaged customers. In this way, marketers can include value-proof hyper-personalization methods to reach out to customers and fulfil their expectations in banking.
Lead Generation & Nurturing
For lead generation and nurturing, marketers should activate paid search, paid/owned social media, and affiliate sites using intelligent and real-time customer data. This will help understand the effectiveness of the platforms in generating potential leads and nurturing them in the best ways.
A Data-Driven Path
Banks using customer data can monetize it by differentiating between actionable and non-actionable customers. Even so, they can conduct data-driven optimization (DDO), a measurable approach when banks interact with their customers. This approach includes monetizing and identifying customers’ behavior patterns and optimizing their decision-making processes faster and more accurately.
In addition, data-driven optimizations range in different types and sizes—for example, new features, CTAs, pricing, page flow, navigation, and templates. With the help of these, marketers can get a lot of data and use hyper-personalization strategies accordingly.
A Hybrid Environment
Given the current situation, banks should prioritize intelligence by implementing a security-rich hybrid cloud for their hyper-personalization in their banking processes. With this in place, banks can efficiently, inexpensively, and rapidly deliver hyper-personalized services to customers under a hybrid setup. For this, banks should have a robust data analytic infrastructure that can filter the most operational customer data.
Prominent Examples of Hyper-Personalization in Banking
American Express Sends Videos to Increase Engagement
American Express’s business model includes hyper-personalization of its customers globally.
We’re delegating much deeper hyper-personalization at a company level.”
Harry Mole, Director of Marketing at American Express
American Express demonstrates its commitment to hyper-personalization by creating videos for its customers. For example, it makes videos accompanying a customer's monthly credit card statements. The video helps customers explore and learn new ways of managing their credit shares. It also helps them learn about account creation for new customers, share financial tips and tricks, and introduce new rewards. These activities further help consumers maximize the benefits of their American Express account.
Since using a hyper-personalization strategy, American Express has seen a threefold increase in marketing conversations and a considerable decrease in the cost of acquiring new customers.
Edward Jones Uses Personalization to Increase App Downloads
Edward Jones, a financial services firm, offers a mobile app that allows customers to easily access their accounts and investment options. The app effectively conveys the benefits of security and convenience and is equally friendly. Edward Jones initiated an email campaign to encourage customers to download and engage with the entire app. It added a messaging section for app users and highlighted services such as tracking investments, depositing checks, transferring funds, and more without visiting a branch.
Frequently Asked Question
What do customers expect from their bank?
Customers need assistance and want their needs to be understood by their banks. They do not prefer a generic approach to services. They prefer a more customized and solution-driven approach.
How is the hyper-personalization approach implemented in banks?
Hyper-personalization in banks can be implemented in the following ways:
Compile essential customer data and utilize it to create strategies
Create hyper-personalized content according to the customer base
Distribute the content across channels to reach customers
Why is personalization important in banking?
According to a study by Gartner, 67% of customers are unaware of the services and products their banks offer. So, with the help of personalization, they can easily connect to banks’ offers, benefits, and services. This is where personalization comes into play.