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ableX für Finanzwesen

FINANCE

TOPICS THAT MOVE

The financial industry includes banks, insurance companies, mutual funds, stock exchanges and other service providers that deal with money management. It is highly regulated and has to deal with issues such as risk management, compliance, financial technology (fintech), and the fight against financial crime. Digitalization and the rise of cryptocurrencies and blockchain technologies are current trends that are transforming the industry.

Regulatory
Compliance & Reports

Financial institutions are under pressure to meet a variety of often complex and rapidly changing regulatory requirements. Compliance with laws and regulations such as Basel III, MiFID II or the GDPR requires precise and reliable data as well as efficient data reporting processes.

Data integration
and quality

Mergers and acquisitions are not uncommon in the financial sector, which often leads to fragmented data landscapes with incompatible systems. Integrating these systems and ensuring high data quality across all business areas is a major challenge.

Risk management
and analysis

Data plays a key role in risk management. Inaccurate, outdated or incomplete data can lead to incorrect risk assessments, which in turn can result in financial losses. Financial institutions need to collect and analyse complex data from various sources in order to assess and manage their risk.

Cybersecurity and 
Data leaks

Financial institutions are a prime target for cyberattacks, and data leaks can result in significant financial and reputational losses. Securing sensitive financial data against attacks and internal threats is therefore a top priority.

Datenmanagement Lösungen für das Finanzwesen

Discover with us the data management solutions for Finance!

REGULATORY COMPLIANCE

Regulatory compliance is of utmost importance in finance, and a dedicated data management system can provide extensive solutions and benefits:

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SOLUTION
INTEGRATED COMPLIANCE MODULE

The system includes specialized modules that map current regulatory requirements and automatically adapt to ensure compliance.

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CONSOLIDATED DATA HOLDING

It consolidates financial data from different business areas to create a unified database for reporting.

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AUTOMATED
REPORTING

The system automates the creation process of reports required for supervisory authorities such as BaFin or the ECB and ensures their timely submission.

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ADVANTAGE

RISK REDUCTION

The risks of regulatory violations are reduced through automated checks and alert systems.

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ADVANTAGE

TIME AND COST

SAVINGS

Automated processes reduce manual effort and associated reporting costs.

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ADVANTAGE

PRECISE AND

TIMELY REPORTS

The quality and accuracy of compliance reporting is improved, resulting in a reliable information base for regulators.

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ADVANTAGE

FASTER

REACTIONS

The system can be quickly updated to comply with new laws and regulations, strengthening the company's flexibility and adaptability.

An effective data management system in finance not only makes it easier to comply with complex regulatory requirements, but also improves the efficiency and reliability of reporting, which increases the trust of regulators, investors and customers.

RISK MANAGEMENT AND ANALYSIS

A data management system used in finance for risk management and analysis can provide the following solutions and benefits:

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SOLUTION
HEADQUARTERS
RISK DATABASE

The system creates a central platform for collecting and managing all risk-relevant data.

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RISK ANALYSIS
TOOLS

It integrates advanced analytical tools that support quantitative and qualitative risk models to assess different types of risk.

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REAL-TIME RISK MONITORING

Real-time data processing allows the system to quickly respond to market changes and identify risks

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ADVANTAGE

IMPROVED

RISK DETECTION

The system allows financial companies to identify risks more quickly and take appropriate action.

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ADVANTAGE

DATA DRIVEN

RISK ASSESSMENT

It enables precise and data-driven assessment of credit, market and operational risks.

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ADVANTAGE

REDUCTION OF

LOSSES

Through proactive risk management potential losses can
be minimized.

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ADVANTAGE

REGULATORY

COMPLIANCE

The system supports compliance with risk management regulations
and standards as set by financial regulators.

Such a data management system enables financial institutions to strengthen their risk management, resulting in better capital allocation, increased financial stability and stakeholder confidence.

DATA INTEGRATION AND QUALITY

In finance, a specialized data management system enables an effective solution for data integration and quality:

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DATA
CONSILIDATION

The system unifies data from different sources and systems, creating an integrated view of all financial information.

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QUALITY
CONTROLS

It carries out ongoing quality controls to ensure the accuracy, completeness and reliability of the data.

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FILE
CLEANUP

Automated cleansing functions detect and correct errors, duplications and inconsistencies in the data.

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ADVANTAGE

RELIABLE

DATA BASIS

The system minimizes the risk of compliance violations and the associated penalties and sanctions.

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ADVANTAGE

IMPROVED

DECISIONS

Automating the compliance process saves time and resources that would otherwise be required for manual reviews and reporting.

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ADVANTAGE

EFFICIENCY

INCREASE

Compliance with regulatory requirements protects the company's reputation and strengthens trust among stakeholders and customers.

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ADVANTAGE

COMPLIANCE

AND REPORTING

The system can be quickly updated to meet new regulatory requirements, increasing the company's agility in an ever-changing legal environment.

By implementing a robust data management system, financial institutions improve
their operational efficiency, strengthen their compliance structure and lay a solid one
Basis for strategic business decisions.

CYBERSECURITY AND DATA LEAKS

A sophisticated data management system in finance offers significant solutions for cybersecurity and data leak prevention:

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SOLUTION
COMPREHENSIVE INFRASTRUCTURE

The system integrates multi-layered security protocols including firewalls, intrusion detection systems and encryption to protect data.

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ACCESS CONTROLS

Strict authentication procedures and role-based access controls ensure that only authorized users have access to sensitive financial data.

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CONTINUOUS
MONITORING

It constantly monitors network activity to detect unusual patterns that could indicate potential security breaches or data leaks.

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ADVANTAGE

PREVENTION OF

DATA LEAKS

Early identification of security risks can prevent data leaks, protecting the integrity of customer and company data.

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ADVANTAGE

IMPROVING CUSTOMER TRUST

Ensuring data security increases customer confidence in the financial institution's ability to protect their information.

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ADVANTAGE

REDUCTION OF
OPERATIONAL RISKS

Preventing cyberattacks and data leaks minimizes the risk of financial loss and legal consequences.

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ADVANTAGE

MAINTAIN COMPLIANCE

The robust cyber security structure supports compliance with industry standards and legal regulations regarding data protection and information security.

A cybersecurity-focused data management system enables financial institutions to operate on the front lines of protection against cyber threats and is an essential component to ensuring their operational and financial stability.

OUR KEY FEATURES.
YOUR INDIVIDUAL SOLUTION.

We offer a variety of functionalities that are just waiting to be put together for your individual use. Take advantage of our flexibility in building data models and taking your very individual processes into account. Experience with us, without much programming,
how we can get the best potential out of your data!

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Klassifikationsmanager

Classification manager

ableX's Classification Manager is a powerful tool that allows users to automatically categorize and organize their data. It uses algorithms and predefined rules to organize data into structured groups, enabling systematic analysis and easier discovery of information. Users can define their own categories tailored to their specific requirements and processes, creating a personalized data structure. This feature supports compliance with data standards, facilitates reporting, and improves the overall efficiency of data management by automating sorting of large data sets, saving time and increasing accuracy.

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DQR Editor

The "DQR Editor" (Data Quality Rules Editor) is a specialized feature within ableX that allows users to implement detailed data quality guidelines and precisely control their application. This tool provides a user-friendly interface to set specific parameters for data validation, such as format checks, value range restrictions, and dependency rules between data fields. The editor allows these rules to be applied to records to identify and correct inconsistencies, duplicates and errors. This allows organizations to proactively manage and continually improve the quality of their data, resulting in trustworthy data and informed business decisions.

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Data field mapping

The "Datafield Mapping" feature in ableX is a critical tool that gives users the ability to meaningfully map data fields from a variety of data sources. This feature creates compatibility between heterogeneous data formats, which is essential for synchronizing information across different systems and platforms. With data field mapping, corresponding data fields are identified and linked, which creates a homogeneous data view. This is particularly advantageous when data from different systems such as CRM, ERP or external third-party databases need to be consolidated. It plays a central role in data migration, data import or data merging, for example by ensuring that 'customer number' in one database is correctly linked to 'client ID' in the other.

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Referencing

The "Referencing" feature in ableX is a crucial tool for structuring and meaningfully connecting database content. It allows users to create unique references between records that serve as references. These references are essential for establishing relationships between different data elements, such as between customer and order data in a sales database. Referencing is also important when importing and exporting data between different systems, as it helps ensure the correct mapping between different fields Ensuring data sources. It plays a central role in ensuring data quality, especially in complex systems where the accuracy and reliability of information is critical for operational decisions, reporting and analytics.

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