Financial service providers & insurance companies

Data solutions for financial service providers & insurance companies

We help banks, financial service providers and insurance companies use their data as a real competitive advantage. Our solutions ensure reliable reporting, automated processes, and data-based decisions. And thus for noticeable cost reductions, risk minimization and greater agility in the market.

Find out what's in your data

Turn your data into a strategic advantage

Banks and insurance companies are facing unprecedented challenges. Regulatory requirements and ESG standards are constantly increasing. Customers expect real-time services and the highest level of data security. At the same time, fragmented legacy systems and manual processes are jeopardizing competitiveness. A lack of transparency in data flows increases the risk of compliance violations and makes it difficult to make informed management decisions in real time. Those who seize this opportunity now and leverage their data strategically will not only strengthen compliance but also secure margins and profitability in the long term.

We help you consolidate data across silos, automate processes, and make data actionable—for you, your team, and the entire company.

With deep industry expertise, we analyze your data landscape, establish robust processes, and make information available exactly where it’s needed. So you can unlock the full potential of your data.

We unleash the potential of your data

Our established solutions for financial service providers & insurance companies

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Questions our customers ask
  • Which data initiatives have the biggest economic impact—from cost reduction to risk management to new business models?
  • How do we design agile data governance that meets data protection, risk management and regulatory reporting requirements (e.g. GDPR, BCBS 239, MiFID II, Solvency II)?
  • How do we avoid data silos and create a consistent understanding across departments and systems?
How we support your financial or insurance company
  • Development of a holistic data strategy with a top-down and bottom-up approach that combines efficiency gains and regulatory security
  • Establishment of use case roadmaps including prioritization according to business impact & compliance relevance
  • Conducting data thinking workshops and maturity assessments
  • Development of role & authorization models for data ownership & governance
Our customers were concerned with these questions

Typical questions

  • Which data-driven use cases contribute to our goals?
  • How do we incorporate data governance into unbundling requirements?
  • What roles and responsibilities do we need?
  • How do we integrate data from inventory management or core banking systems, claims or risk management, and CRM/DMS centrally and securely?
  • Which architecture simultaneously meets data protection, auditability and future security requirements?
  • How can regulatory-relevant data be automatically prepared for reporting and auditing?
How we support your financial or insurance company
  • Build scalable, cloud-based data platforms
  • Development of robust data pipelines for regulatory reporting and customer data integration
  • Implementation of automated monitoring and logging to shorten audit processes and make risks visible at an early stage
Our customers were concerned with these questions

Typical questions

  • Which data-driven use cases contribute to our goals?
  • How do we incorporate data governance into unbundling requirements?
  • What roles and responsibilities do we need?
  • How do we automate reporting processes to free up resources in controlling?
  • How do we identify risks or cases of fraud before they cause high costs?
  • How do we increase customer satisfaction through personalized, data-driven services?
  • How do we support our departments with self-service analytics and role-based access?
How we support your financial or insurance company
  • Development of interactive dashboards
  • Implementation of advanced analytics use cases (churn prediction, fraud detection, ESG monitoring)
  • Development of self-service BI that empowers teams and reduces external consulting costs, including training concept
  • Automated reporting that saves time and increases the accuracy of regulatory reports

How we have already successfully supported other financial service providers & insurance companies

By cleverly linking data, we have not only optimized our internal processes, but also broken up data silos and thus secured a decisive competitive advantage.
Vanessa Kremer
Chapter Lead Data & Anaytics/Aachen Real Estate

Modern data architecture

Together with Aachener Grundvermögen, we have set up a modern, data-based infrastructure that supports the efficient handling of large amounts of real estate data. The use of the data vault approach ensures high data quality. At the same time, a flexible architecture is being created that enables both the connection of various source systems and future expansions without any problems.

Financial service providers & insurance companies
Make data effective—step by step

From strategy to self-service: This is how we support financial service providers and insurance companies on their data journey.

Define status quo & use cases

We develop a target image, prioritize use cases and develop a roadmap, tailored to your strategic goals.

Modernize infrastructure

We create the basis with a scalable, secure and maintainable data platform.

Automate processes

Data pipelines, reporting routes and quality assurance are automated — for stability, efficiency and compliance.

Empower teams

We make your departments fit for data — with targeted enablement in Power BI, Tableau & Co., so that you can work independently in the long term.

Scaling

Together, we look at the impact, close gaps and create structures for sustainable success.

Questions that will help you

FAQ

How can a uniform understanding of data be established across systems such as accounting, CRM and risk management?

A uniform understanding of data is created by centrally combining, harmonizing and modelling data from various systems in a technically consistent manner. This results in comparable key figures that can be used for both operational and regulatory reports.

How can regulatory reporting requirements (e.g. MiFID II, Solvency II) be automated based on data?

Automating regulatory reporting requirements requires that data processes, audit rules, and data models are standardized and embedded in repeatable workflows. Reports and messages can then be reliably automated, which reduces effort and minimizes error risks.

How can modern data analysis help identify fraud or irregular patterns at an early stage?

Modern analysis models combine transaction data, customer behavior, and historical patterns to identify unusual activities. Real-time analyses and defined outlier tests help to identify fraudulent activity more quickly and to be able to initiate appropriate measures.

Why does the financial sector need a data strategy?

A data strategy links use cases with business goals, creates clarity in roles and provides a roadmap for scalable data projects, taking compliance and risk management into account.

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