Transformation of retail and SME banking through Agentic AI

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Agentic AI in retail and SME banking is a new stage in the development of digital solutions, when artificial intelligence not only helps perform individual tasks, but also makes decisions and acts autonomously to achieve business goals.

The deployment of such systems opens banks opportunities for more precise risk management, accelerating processes and creating personalized services, the importance of which becomes critically high in a rapidly changing financial environment.

Definition of Agentic AI and its key features

Agentic AI is a new paradigm of autonomous AI agents capable of making decisions, learning from large datasets and interacting with customers and the bank’s internal systems without constant human involvement. Unlike classical machine learning systems, Agentic AI is built on multi-agent systems, where each agent can independently analyze the situation, choose optimal scenarios and initiate actions in real time. At the core are advanced AI decision-making models integrated with cloud platforms and big data processing tools.
The COREDO team has repeatedly faced the challenges of implementing such platforms in banks in the EU and Asia: for example, when launching automated services for SME clients in Estonia we integrated Agentic AI for instant transaction analysis and automatic client verification, which reduced KYC procedure time from days to minutes.

Differences between Agentic AI and machine learning with RPA

In classical machine learning and RPA (robotic process automation), the focus is on creating algorithms that solve strictly defined tasks according to given rules. Agentic AI differs fundamentally: its agents are able to independently formulate goals, adapt to changing conditions, detect anomalies and propose new scenarios unavailable to traditional systems. This allows not only the automation of routine processes but also the creation of intelligent services capable of self-learning and scaling.
COREDO’s practice confirms: when implementing Agentic AI into banking compliance systems in the UK it was possible to achieve a 30% reduction in manual labor for handling suspicious transactions and improve fraud detection accuracy thanks to generative artificial intelligence and predictive analytics.

Technologies in the banking sector 2025 – Agentic AI

By 2025, the world’s leading banks are betting on integrating Agentic AI with cloud infrastructures, big data platforms and intelligent automation technologies. Key trends include the development of multi-agent systems for real-time transaction monitoring, the introduction of generative AI for personalizing the customer experience, as well as deep integration with legacy systems through APIs and middleware solutions. Solutions developed by COREDO for banks in the Czech Republic and Singapore have shown that proper integration of Agentic AI not only speeds up processes but also ensures compliance with new regulatory requirements in the EU and Asia.
Thus, the integration of Agentic AI becomes an integral part of the strategic transformation of banking services worldwide, anticipating changes in retail and SME banking.

Transformation of retail and SME banking with Agentic AI

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The transformation of retail and SME banking with Agentic AI begins a new era where autonomous AI agents not only optimize internal processes but fundamentally change the approach to servicing customers and small businesses. Thanks to the ability to make decisions independently and learn from every interaction, Agentic AI becomes the foundation for more personalized, proactive banking services that distinguish retail and SME solutions in a competitive environment.

Improving customer experience and personalization of services

Agentic AI radically changes the approach to customer interactions: now a bank can offer personalized financial products, respond instantly to requests and forecast the needs of SME clients. Through deep analysis of behavior and transactions, AI for small and medium businesses creates individualized offers, increasing loyalty and reducing customer churn.

In one of COREDO’s projects for a bank in Slovakia, the implementation of Agentic AI made it possible to automate the selection of credit products for entrepreneurs, taking into account not only financial history but also industry trends, seasonality and even customers’ behavioral patterns.

Automation of KYC and AML procedures for security

The automation of KYC and AML is a key driver of Agentic AI adoption in banks across Europe and Asia. Modern platforms are capable of collecting, analyzing and verifying client data in real time, detecting suspicious operations and generating reports for regulators. Agentic AI for combating fraud uses predictive analytics and machine learning to identify complex money laundering schemes and prevent financial crimes.

COREDO’s experience in Estonia and Singapore shows: automating client verification and implementing multi-level AI agents not only reduces the risk of fines but also significantly speeds up the onboarding process, which is especially important for international clients.

Optimization of scoring and SME lending

Agentic AI transforms SME lending processes by automating credit scoring, analyzing non-trivial data sources (for example, behavioral and industry indicators), as well as dynamically reviewing limits and lending terms. As a result, banks can make decisions faster and more accurately, reducing default rates and expanding access to financing for small and medium-sized businesses.

In COREDO’s case for a bank in Cyprus, the implementation of autonomous AI for scoring increased approval rates by 18% without increasing credit risk, and application review time was reduced from 48 hours to 20 minutes.

Transaction monitoring and prevention of financial crimes

The use of autonomous AI for transaction monitoring provides round-the-clockreal-time monitoring of operations, instant detection of suspicious schemes and automatic escalation of incidents. Examples of using Agentic AI to prevent financial crime include the implementation of multi-layered filters, self-learning models and integration with global sanctions databases.

The COREDO team implemented a system in an EU bank where Agentic AI independently detects new types of fraud by analyzing millions of transactions in real time and instantly responding to anomalies, which reduced direct fraud losses by 27% in the first year of operation.

Agentic AI in banks: business effects and benefits

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Agentic AI in banks is a new stage in the development of autonomous intelligent systems capable of making decisions and performing complex operations without constant human intervention. Today, such technologies offer banks unique business effects and benefits: from cost optimization to increased team productivity and the implementation of more accurate risk management models.

Improving efficiency and reducing costs

The impact of Agentic AI on banks’ operational efficiency manifests in the automation of routine processes, reduction of application processing times, lower compliance costs and a reduced human factor in critical operations. As COREDO’s practice shows, the implementation of autonomous AI agents allows banks to reallocate resources to the development of new services rather than manual data processing.

Scaling AI in finance and ROI of implementation

Scaling AI in the financial sector requires flexible architecture and competent change management. The ROI from implementing Agentic AI is calculated based on reductions in operating expenses, revenue growth from new services and improved customer satisfaction. In one of COREDO’s projects for a bank in Asia, the return on investment in Agentic AI was 220% in 18 months due to reduced AML costs and an increased number of SME clients.

Moving to issues of risk management and compliance becomes a critically important stage for effectively scaling Agentic AI in the financial sector.

Risk management and compliance with Agentic AI

Agentic AI integrates into banks’ compliance systems to automate monitoring, reporting and risk management. This allows not only compliance with international standards (for example, AMLD in the EU or MAS in Singapore), but also proactive identification of new threats. The solution developed by COREDO for a bank in the United Kingdom enabled a shift from reactive to proactive risk management, reducing the number of incidents by 35%.

Thus, the integration of Agentic AI into banks’ compliance systems creates a foundation for more effective risk management and regulatory compliance, which is especially relevant when expanding technologies into retail and SME banking.

Risks of integrating Agentic AI into retail and SME banking

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The risks of integrating Agentic AI into retail and SME banking require special attention to how the new autonomous systems interact with existing technological and organizational processes. Despite significant potential to improve efficiency and reduce operating costs, the implementation of agentic AI often faces a number of challenges, especially when working with outdated IT infrastructure and complex internal bank processes.

Integration issues with legacy systems: technical and organizational

Integrating Agentic AI with banks’ legacy systems is one of the main technological challenges. Old platforms often do not support modern APIs, have limitations in processing large volumes of data and do not provide the required level of security. In COREDO’s practice for a bank in the Czech Republic, a phased migration was implemented: through middleware solutions and cloud services it was possible to ensure seamless operation of the new AI agents with the existing infrastructure.

Regulatory requirements and compliance in Europe and Asia

How to ensure Agentic AI meets regulators’ requirements in the EU and Asia? It is important to consider the specifics of national and international standards such as GDPR, AMLD, PSD2, MAS Guidelines. The COREDO team supports projects at all stages, including legal expertise, AI model audits and the preparation of documentation for regulators. This approach minimizes the risk of fines and accelerates the approval of new services.

Ethical and systemic risks of AI agents

Agentic AI brings not only technological but also ethical challenges: transparency of decision-making, prevention of discrimination, personal data protection. Systemic and algorithmic risks require the implementation of explainable AI mechanisms, regular model audits and access control to data. At COREDO we recommend integrating ethical principles and risk assessment procedures at early stages of Agentic AI deployment.

Agentic AI in international banks: best cases and practices

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Agentic AI in international banks today sets a new standard for efficiency, autonomy and personalization of banking services, from improving customer service quality to automating key processes and minimizing risks. The best cases and practices demonstrate how the implementation of such solutions not only optimizes operational activities but also opens new opportunities for retail and SME banking.

Transformation of retail and SME banking with Agentic AI

Global banks are already demonstrating impressive results: in Singapore the implementation of autonomous AI agents allowed one of the leading banks to reduce new customer verification time from 48 hours to 15 minutes, and in the United Kingdom to reduce fraud levels by 30% thanks to predictive analytics and automated transaction monitoring. In COREDO’s case for a bank in Estonia, Agentic AI enabled bringing new products to the small business market by fully automating the scoring and microloan issuance process.

Scaling and change management when implementing AI

Scaling AI solutions requires a clear change management strategy: staff training, phased integration, testing on pilot segments, and continuous performance monitoring. COREDO’s practice has shown that successful projects are built on close collaboration between IT, legal, and business teams, as well as on deploying flexible Agentic AI platforms capable of adapting to the requirements of different jurisdictions.

Practical tips for entrepreneurs and executives

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Practical tips for entrepreneurs and executives are especially relevant in the context of modern banking technologies. Today Agentic AI opens new opportunities for automation, risk reduction, and improving customer experience, making businesses more competitive. Below are the key steps to prepare a business for successful work with banks in the era of Agentic AI.

How to prepare a business for banks with Agentic AI?

AI for small and medium-sized businesses opens new opportunities for quick access to financing, personalized products, and automated services. I recommend preparing corporate processes for digital transformation in advance: ensure transparency of the corporate structure, prepare high-quality KYC/AML documentation, and implement internal data governance procedures.

How to choose a banking partner with Agentic AI

Banking technologies in 2025 require partners to be not only innovative but also compliant with regulatory and ethical standards. When choosing a bank, pay attention to the maturity of Agentic AI platforms, experience in your industry, and the presence of transparent compliance procedures. The COREDO team recommends conducting independent audits of AI platforms and assessing their integration with your business processes.

AML in AI-banking: how to minimize risks

Automating KYC and AML is key to reducing risks and accelerating operations. It is important to regularly update internal policies, train staff, and use solutions certified to international standards. COREDO’s practice shows that integrating Agentic AI with systems for combating financial crime not only helps meet regulator requirements but also protects the business from new threats.

Key takeaways and steps for action

Agentic AI is becoming a strategic tool for transforming retail and SME banking, providing new levels of efficiency, security, and personalization. Nevertheless, implementation success depends on proper integration with legacy systems, adherence to regulatory and ethical standards, and the business’s readiness for change.

I recommend:

  • Building Agentic AI implementation on a clear change management strategy and phased integration.
  • Choosing partners with proven AI expertise and experience operating in your jurisdiction.
  • Implementing metrics to assess effectiveness (cost reduction, revenue growth, risk reduction, ROI from Agentic AI implementation).
  • Continuously improving AML/KYC procedures and auditing AI models for transparency and compliance with standards.

COREDO’s experience confirms: only a comprehensive and strategic approach to implementing Agentic AI enables not only meeting market requirements but also outperforming competitors, creating a resilient and innovative business amid digital transformation.

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