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Banking & Capital Markets

Transforming how global financial institutions refine their critical data to meet regulatory deadlines, reduce enterprise risk, and accelerate business growth.

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Unlocking A New Paradigm In Regulatory Compliance

Today's data science, data engineering, and data operation's processes and systems no longer meet the requirements of regulators and the needs of business.  Institutions are turning to technology to accelerate project timelines and bridge the gap of limited resources.

Kingland's suite of software products and 30+ years of industry experience in data refining allows us to efficiently work with clients and partners to completely diagnose and accurately prescribe end-to-end solutions for the banking & capital markets industry's most complex data challenges.

Digital Transformation Web

Industry Challenges


Data for Risk & Regulatory Compliance

New regulations, increased regulatory scrutiny, and new risks are exposing gaps, inaccuracies, and deficiencies in the management of the data required to manage risk and comply with regulations.

With Data Refinery, enterprises are able to leverage, improve, and expand critical data to achieve the  “regulatory-grade data” required to meet regulatory standards and mitigate risk.


Transformation & Modernization Programs

Businesses are transitioning legacy applications and operations to modern technology architectures to take advantage of the cloud, leverage data more, and take advantage of Al, to drive business value and improve operational resiliency.

With Data Refinery, enterprises can quickly migrate legacy data and processes, build out next-generation data pipelines, and automate data analytics and management to power next-generation business products and services.


Data as an Asset or Product

Large enterprises are sitting on a treasure trove of data that can add significant value to clients and critical business processes, but the data is difficult to leverage and is largely untapped in its ability to be used.

With Data Refinery, enterprises can quickly assemble new data sets, augment and enrich the data, and develop new data assets to be integrated into business processes and new products.


Data for AI

Organizations are leveraging Al more and more to drive new value, yet the data feeding AI models requires active management to improve the reliability and usefulness of the Al models.

With Data Refinery, organizations can quickly experiment, expand, and improve the data to drive more value from Al investments.


Kingland Product Suite for Banking & Capital Markets

Kingland's product suite combines our 35 years of data management experience with state-of-the-art software development processes and exchange-grade cloud security to form a superpower set of data refinement and data management capabilities, all brought to life by our in-house industry experts.


Connect critical data, core systems, and disparate data tools to orchestrate efficient data projects in a governed, secure, and repeatable way.

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Manage the most critical data on all client relationships to minimize conflicts, comply with global regulations, and maximize growth opportunities.

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Automate and govern the most important decisions related to clients, risks, policies, employees, vendors and regulations.

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Your Data Can Be More

At Kingland, we have built our business to solve the unique business, data, and technology demands of integral companies.

A Client-Centric Approach to Successful Transformation Programs

Transformation programs are all the rage throughout banking and capital markets firms. Almost 90% of banks will have launched a digital...
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Helping Clients Make Better Informed Decisions

Managing a database of client, counterparty, and related data becomes increasingly difficult as a business grows. Whether creating (e.g., onboarding...
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As one of the world's most data-intensive, regulated companies, you don't have the luxury of making a mistake, and neither do we.

The critical data powering your business is your most valuable asset. Integrating and augmenting the various systems that contain it is not for the faint of heart. Kingland integrates data from your existing systems and supports data accuracy across your entire organization, supporting a stronger customer data ecosystem and better business outcomes.


Assessing Critical Data In The Financial Services Industry

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In 2023, Kingland partnered with DIACSUS to survey executives from the world’s top banks, investment firms, and data suppliers about their business and data priorities. While business priorities may vary institution to institution, these executives all agreed to one common priority across their most important initiatives in 2024: Critical Data.  Rather than focusing on the growing volumes of data throughout the enterprise, these executives have realized that 2024 is a year of focus, but as we enter 2024, their focus isn’t necessarily on managing all of the data flowing through their enterprise. 

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Case Study

See How Kingland's Data Automation Software Minimized Risk for a Global Bank

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Kingland solutions support more than 1,800 broker dealers, 300 asset managers, and hundreds of thousands of market participants. With a cornerstone in client data, Kingland is working with FINRA CAT to deliver the Consolidated Audit Trail (CAT) and has delivered and operates the leading Legal Entity Identifier (LEI) utility for DTCC. Additionally, the Kingland Data Platform has supported critical reference data solutions for the US mutual fund industry and risk and regulatory reporting data for various top tier institutions. Kingland's 35 years of industry expertise date back to its original founding as a pioneering regional broker dealer in the 1980s.

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Use Case

Data Refinement for Entity Classifications

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In the world of financial services data, clients and products are two of the most important categories of data. A client or product record may be a simple as a handful of attributes, or as complex as 1,000 attributes to describe all of the characteristics of a client. When we focus on classification data, we are focused in on the data attributes used to group, compare, contrast, and represent the same qualities or characteristics for a specific entity or product. Put another way, classifications typically answer two types of questions:

  • What is the entity or product?

  • What are we allowed to do with the entity or product?

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Use Case

Data Refinement for Customer & Account Data

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Every transaction a financial institution completes traces back to some sort of account, and inevitably, a client or many clients. Client and account data continues to be the lifeblood of banking and capital markets activity, required for operational processes, critical for risk monitoring, and mandated by regulators. As new risks emerge and new regulations are enacted, many times 1 to 2 simple attributes are missing from customer and account information. Additionally, as a customer relationship expands from the products and services they use today, to new products and services, another 1 to 2 simple attributes are missing. The problem of missing customer and account information may seem fairly straightforward, but when the largest institutions have tens or hundreds of millions of customers, even just one simple attribute can be a $10 million problem.

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Banking & Capital Markets Insights

Discover how the world’s most integral companies are making their data work harder.

April 26th, 2022
A Client-Centric Approach to Successful Transformation Programs
A Client-Centric Approach to Successful Transformation Programs
Transformation programs are all the rage throughout banking and capital markets firms. Almost 90% of banks will have...
Read Full
September 28th, 2021
One Reason to Improve your Organization’s Client Data
One Reason to Improve your Organization’s Client Data
Want to improve your organization's client data? Is the improvement as simple as attaining a trustworthy single source...
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August 31st, 2021
Steps to Remove Variant Data from your Multiverse
Steps to Remove Variant Data from your Multiverse
Your data commits crimes against your organization daily, creating variant data throughout the enterprise. Borrowing...
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