The Top Challenges Facing Banks in Digital Transformation and How To Solve Them

Digital transformation is a critical aspect of modern business strategy, and the banking industry is no exception. In a complex and ever-growing technology-driven world, banks should embark on digital transformation to stay competitive and drive growth. 

However, as banks adapt to this digital age, they will face challenges requiring innovative solutions to achieve success.

Top 4 digital transformation challenges faced by banks

Complex legacy systems 

Most traditional banks rely on legacy systems to run their business. However, these systems are among the top bottlenecks in digital transformation because they are often slow, inflexible, and difficult to integrate with new technologies.

Besides, replacing these systems can be challenging and costly, making it difficult for banks to optimize their IT infrastructures.

Hence, banks should take a practical approach to modernize their IT infrastructures. This involves investing in modern systems that are more flexible, scalable, and adaptable to change.

High volumes of data

Another challenge that banks have to face in digital transformation is the urgency to handle massive amounts of data. Data has grown exponentially as the financial and banking industry becomes increasingly digitized. This data can come from a variety of sources, including customer information, account statements, transactions, etc. Banks use valuable data to understand market trends, and customer behavior to develop services/products that are tailored to customers. 

However, many banks struggle with data silos, inconsistent data quality, and a lack of effective data processing. 

To deal with these challenges, banks should invest in comprehensive technologies to manage and handle complex data, as well as unlock the true potential value of data.

Barriers to data-driven growth for banks| Accenture Banking Blog
Banks are under increasing pressure to deal with a giant amount of data (Source:

Growing cybersecurity and regulatory compliance

Cyber threats are a major concern for banks, as they continue to grow in frequency and sophistication. This requires investing in advanced cybersecurity measures to protect sensitive data and prevent cyber attacks.

Additionally, since banks operate in a highly regulated environment, they need to comply with evolving regulatory standards. To overcome this challenge, banks must implement robust strategies to enhance compliance and prevent penalties, risks, and financial fraud.

Rising customer experience and engagement

Customers are more demanding than ever. They expect a seamless and engaging customer experience across various channels. According to PwC, up to 73% of customers say a positive experience will strongly influence their consumption decisions.

To meet these expectations, banks should invest in advanced technologies that can provide customers with 24/7 access, personalized experience, and suitable solutions to their needs. 

CRM (Customer Relationship Management) in Banks
Banks can meet rising customer expectations by applying digital solutions (Source:

Must have banking technologies in 2024 for robust digital transformation strategies

The transformative journey in the banking industry is driven by technological advancements. Automation and advanced technologies such as Generative AI, and RegTech have become key trends for banks to solve complex challenges and stay ahead of the curve. 

Artificial Intelligence 

Banks increasingly leverage Artificial Intelligence (AI) to achieve operational excellence and improve customer experiences. Insider Intelligence’s AI in Banking report reveals that 80% of banks recognize the potential benefits that AI can provide.

 AI has become an invaluable tool for financial institutions in a transformative period (Source:

Specifically, banks now adopt AI-powered chatbots to provide a seamless experience and personalized responses for customers by understanding customer emotions and complex queries.

Besides, AI will continue its presence in the banking industry due to its ability to enhance fraud detection and reduce financial risk. With AI and Machine Learning algorithms, banks can detect fraudulent activities, and track loopholes in business systems by identifying patterns in transactions.

Another example of an AI application is risk analysis. By monitoring customer data, financial transactions, and market trends with advanced Machine Learning, AI can quickly and accurately suggest investment options and alert real-time risk.

Generative AI

Last year, several banks started experimenting with Generative AI (Gen AI), with many impressive results. This year will see more adoption across various departments in the banking industry.

Generative AI Unleashed: Charting The Enterprise Future
Gen AI has the potential to bring significant new value to the banking sector (Source:

Banks can take advantage of generative models to boost customer experience by recommending personalized products/services based on customer needs and behaviors.

For example, Wells Fargo, an American multinational financial services company, has added AI-powered enhancement to their mobile app that offers personalized account insights and provides customers with a more comprehensive view of their finances. Currently, the solution offers more than 50 different prompts to a customer based on past and expected future account activity.

This predictive banking feature is a prime example of AI implementation, further highlighting the capabilities of Gen AI in the finance and banking industry.

Furthermore, Gen AI accelerates innovation by creating synthetic data for effective model training. This synthetic data enables banks to represent diverse risk scenarios and identify correlations, dependencies, and emerging risks, thereby facilitating proactive risk management.

Low-code or no-code platforms

Gartner forecasts that by 2025, as many as 70% of new business applications will use low-code or no-code technologies. 

Emerging technologies like low-code and no-code platforms increasingly become key trends in banking for several reasons. By eliminating the need for traditional coding and testing, low-code or no-code allows for rapid application development in a cost-effective manner. These applications can automate workflow, integrate with existing systems, and are tailored to the needs and preferences of their customers. Besides, banks can greatly enhance the time to market for digital banking products and services using low-code and no-code approaches.

Low-Code and No-Code: Solutions that Are Solving Key Tech Challenges for  Businesses
Low-code and no-code platforms allow banks to customize and automate workflows (Source:

Let’s take a look at the successful story of Bendigo Bank, one of the largest banks in Australia. To provide a more cohesive and high-quality customer experience, Bendigo Bank has chosen a low-code platform, an ideal solution for creating business-related apps. In about a year and a half, Bendigo Bank rolled out 25 customer-focused applications, requiring less time and costs than traditional coding apps.


As mentioned, the increasing complexity of regulations is a major challenge for banks.

The emergence of RegTech (Regulation Technology) is a game-changer for financial businesses to automate processes and meet their regulatory expectations.

Digital innovation driving the need for RegTech (Source:

Incorporating sophisticated AI and Machine Learning models, banks can analyze data to detect suspicious activity and forecast possible fraud activities.  Additionally, automation, cloud computing, and big data can help banks simplify regulatory processes, eliminating the time and resources required to manage regulatory requirements.

Significantly, RegTech solutions provide financial institutions with real-time regulatory reporting changes so they can meet their reporting obligations and adhere to regulatory requirements.

Intelligent Document Processing 

Banks have to deal with massive data, with the amount of bank data created each second increasing by 700 percent by 2020, according to The Hill. However, banks still need to process a high volume of data manually, causing longer processing times, unnecessary waiting lines, and an unpleasant customer experience.

With the ability to automatically process complex data (structured/unstructured), Intelligent Document Processing (IDP) can help reduce tedious paperwork, allowing for enhanced processing time and a more seamless experience for customers.

Intelligent Document Processing can solve complex data challenges in the banking industry (Source:

Significantly, to achieve the goal of optimal effectiveness, banks can combine IDP and Robotic Process Automation (RPA). After IDP collects, analyzes, and extracts key data, RPA passes the output data from IDP processing to other systems. Combining these two technologies creates an end-to-end automation process and prevents interruptions.


Blockchain, a decentralized ledger technology, provides a secure and transparent transaction platform. This disruptive technology is becoming increasingly commonplace in financial services.

One of blockchain’s remarkable features is its security and transparency. Besides, based on its decentralized nature, banks can improve data security, reduce costs, and streamline operations.

Another notable and innovative application of blockchain in banking is smart contracts. These automated and self-executing contracts have revolutionized the business world. Significantly, by streamlining and automating the actions required in an agreement or contract, smart contracts allow direct and secure transactions between parties, thereby speeding up the transaction processes.

Explore more disruptive solutions for banks to thrive in the ever-changing landscape here!

Wrapping Up

In today’s rapidly evolving technological landscape, digital transformation is a must for banks to stay relevant and meet the rising needs of their customers. However, the journey to digital transformation is often challenging. Banks must deal with legacy systems, complex data processing, unwanted cybersecurity and regulatory compliance, and rising customer experience and engagement.

By recognizing and addressing these challenges, and leveraging the power of innovative technologies, banks can be confident in the digital transformation journey and achieve a prosperous future in the digital era. 


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akaBot (FPT) is the operation optimization solution for enterprises based on RPA (Robotic Process Automation) platform combined with Process Mining, OCR, Intelligent Document Processing, Machine Learning, Conversational AI, etc. Serving clients in 20+ countries, across 08 domains such as Banking & Finances, Retails, IT Services, Manufacturing, and Logistics…, akaBot is featured by Gartner Peer Insights, G2, and ranked as Top 6 Global RPA Platform by Software Reviews. akaBot also won the prestigious Stevie Award, The Asian Banker Award 2021, etc.

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