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Banking

Legal Enforcement Request Management with Agentic AI

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Business challenge and opportunity

Banks face a large and growing volume of requests from Legal Enforcement Agencies (LEAs) like police, cybercrime units, and other state agencies investigating crimes such as money laundering, terrorism financing, and fraud. These requests, arriving as emails with PDF or image attachments, demand swift extraction of account details, customer data, and transaction histories. The current manual process of most banks relies on analysts to find and extract data which is often slow and susceptible to human error.

This manual workflow introduces operational risk, potential compliance issues, and significant delays in sensitive investigations. For small finance banks with lean teams, the pressure is even more intense.

Automating this process with an agentic AI offers a significant opportunity. It promises faster response times to help solve crimes, a reduced manual workload, higher accuracy, and audit-ready documentation. By solving this challenge, banks can free up valuable employee capacity, build trust with regulators, and dramatically improve efficiency for thousands of monthly requests.

Technical challenges

By automating intake and analysis, banks can accelerate LEA request handling while improving accuracy, compliance, and investigative outcomes. However, there are key operational and technical challenges to overcome:

number 01

Manual data extraction
Inability to automatically ingest and interpret incoming requests can lead to slower case intake, inconsistent handling, and higher operational risk. Delays in response times to LEAs, increases backlogs, and creates exposure to missed or incomplete requests — putting regulatory compliance, strict Service Level Agreements (SLAs) and institutional reputation at risk.

number 02

Data silos across systems
Data is often spread across separate systems such as email, document storage, Customer Relationship Management (CRM) platforms, and core banking platforms. Fragmented information prevents a single, reliable view of each request. This slows investigations, complicates audits and reduces confidence in decision‑making. Without the integration of Agentic AI, the process is reliant on human abilities to read, identify the agency requests and response data elements, leading to intensive time delays and quality issues.

number 03

Security and access control
Strict security, privacy and governance requirements demand tightly controlled access across analyst and back-office teams which can slow workflows.

number 04

Regulatory workflow limitations
Existing systems often lack the workflows needed to support AI within regulated, auditable processes. The lack of AI-ready workflows can prevent organizations from adopting automation, which limits productivity gains.

Our solution

Using the Kyndryl Agentic AI Framework, Kyndryl helps banks with:

Kyndryl delivers an Agentic AI solution that automates the end‑to‑end handling of LEA requests, reducing manual effort and speeding the time-sensitive process.

The AI agent reads large numbers of incoming data requests through emails and attachments, extracts key identifiers and case metadata based on the specific agencies’ guidelines, and classifies each request into a predefined workflow, allowing for a much faster response.

As a next step, the agent integrates with core banking and other transaction systems to retrieve relevant customer and account information.

Kyndryl Consult assesses APIs, CRM workflows, and security and governance controls to ensure a strong foundation for agentic AI, while Kyndryl Vital applies user‑centric design and rapid prototyping to validate workflows, reduce adoption risk, and accelerate time to value.

Kyndryl’s robust observability and zero-trust architectures provide a foundation for secure and bank policy-guided execution. By combining deep observability with zero trust enforcement, organizations gain real-time insight, controlled access, and confidence that every workflow executes within approved policy boundaries.

Kyndryl’s approach enables scalable AI orchestration that is designed to meet customers’ regulatory requirements by enforcing policy-as-code execution, auditable workflows, and controlled access.

Benefits you could achieve

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By automating intake, analysis and response workflows, banks can achieve measurable operational gains while strengthening compliance and investigative outcomes:

  • Cut processing time: Achieve a significant reduction in processing time by eliminating manual data extraction.
  • Increase accuracy and speed: Provide analysts with a consistent, validated input format, minimizing human error and accelerating case resolution.
  • Improve compliance and auditability: Benefit from better audit trails and gain clearer visibility into request patterns and law enforcement agency interactions.
  • Strengthen regulatory relationships: Enhance your bank's reputation for timely and accurate cooperation with law enforcement through automated summaries and standardized responses.
  • Free up your team: Reallocate your operations team's capacity, allowing them to shift from administrative tasks to higher-value investigative work.
  • Help solve financial crimes: Contribute to helping law enforcement solve financial crimes faster.

One Kyndryl customer was able to deliver:1

>50%

reduction in LEA processing time

>60%

reallocation of its operations team’s time to higher-value investigative work

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Why Kyndryl

With decades of mission-critical operations experience, we bring deep expertise in designing, building, and managing AI across complex IT estates.

The Kyndryl Agentic AI Framework brings together the right governance and security controls and human oversight to enable businesses to move beyond isolated pilots to integrated, intelligent systems. It combines secure, scalable agent orchestration with real-time observability and governance, powered by Kyndryl Bridge.

Through Kyndryl Consult, we align AI strategy with business outcomes. Kyndryl Vital provides proven user-centered design and rapid prototyping. And our trusted delivery experts support frictionless integration and help with reskilling and upskilling to build the foundation for success at scale.

We apply a forward engineering approach — using insights from existing systems to design and deploy future-ready AI agents and architectures that are adaptive, resilient, and scalable. Our method is grounded in open ecosystems, data sovereignty, and transparent decision-making.

And with a carefully selected alliance ecosystem — across cloud, data, and AI — we bring the right partners and technologies together to design fit for purpose solutions and orchestrate AI at scale without disrupting the business.

With Kyndryl, AI becomes a core capability — not just a tool — driving productivity, innovation, and growth.

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  1. This document is current as of the initial date of publication and may be changed by Kyndryl at any time without notice. Not all offerings are available in every country in which Kyndryl operates. The performance data and client examples cited are presented for illustrative purposes only.  Actual performance results may vary depending on specific configurations and operating conditions.  Kyndryl products and services are warranted according to the terms and conditions of the agreements under which they are provided.