Data silos are isolated pockets of information within an organisation that is dispersed throughout numerous databases and are inaccessible to other systems or departments. This phenomenon gives rise to a fragmented data environment, frequently lacking interoperability.
In the banking industry, the prevalence of data silos is a major concern, especially regarding the generation of regulatory reports such as FSCS. Multiple factors contribute to the widespread occurrence of data silos, which include:
- When banks combine or buy other institutions, their data systems generally remain distinct, creating siloed information.
- Numerous financial institutions continue to depend on legacy systems of technology that complicate the process of integrating data.
- A bank’s departments may gather and store data separately, producing silos.
These variables complicate data management, making the generation of FSCS SCV reports inaccurate and delayed for institutions. To enhance operational efficiency and reduce risks, financial institutions must acquire authority over their data.
Challenges Due to Data Silos
According to a recent report by IDC Market Research, businesses lose 20–30% of their annual income potential because of data silos. In addition to being prohibitively expensive, exporting the data can be an incredibly time-consuming process. Customers are dissatisfied when they must repeat information across multiple departments within an organisation, preventing a comprehensive perspective of their journey.
Integration Challenges
Data Extraction and Transformation:
The process of compiling data from various sources for FSCS SCV reports can be laborious and susceptible to inaccuracies. Each silo may have its own format, structure, and definitions, making data extraction, transformation, and loading difficult.Technical Issues:
Integrating data across systems needs technical skills and tools, mandating advanced infrastructure and significant investments.Legacy Systems:
Many banks use IT systems that cannot manage today’s data volume and complexity. These outdated systems typically cannot connect with modern innovation, presenting obstacles.Huge Costs:
Often, substantial investments are necessary to upgrade IT infrastructure, implement data governance practices, and integrate disparate data sources to end data silos. These expenses are likely to be enormous, particularly for smaller financial institutions.
Issues with Data Quality
Quality Shortcomings:
Siloed data is more likely to become inaccurate and inconsistent. Updates may not be reflected in all systems, causing inconsistencies and erroneous reporting. Inaccurate or missing information in the FSCS SCV report can end up in payment delays, exclusion from receiving compensation, or legal complications.Redundancy and Duplication:
The storage of identical data in multiple repositories can result in duplicate data and the unproductive utilisation of storage space. These silos make data consistency difficult, raising error risk. This concerns the FSCS, prompting more inquiry and possible fines.
Visibility and Insights Constraints
Fragmented Customer View:
Banks fail to understand their consumers due to data silos. Efforts to personalise offerings, identify future requirements, and comprehend consumer behaviour are impeded as a result.Poor Decision-Making:
Siloed data limits access to vital information for informed decision-making. Isolated systems may hide crucial data from banks, resulting in inefficient strategies and missed opportunities.
Obstacles in Regulatory Compliance
Issues with Reporting:
Regulators frequently request detailed data. Data silos pose a significant obstacle to the efficient and accurate collection of essential information, which may result in compliance challenges and financial penalties.
Elevated Audit Risk:
Banks encounter challenges in showcasing data governance practices and fulfilling audit obligations due to the fragmented structure of segregated data. This can result in increased costs and prolonged audit periods.
Impairs Agility and Innovation
Limited Data for Analytics and AI:
Data silos hinder sophisticated analytics and AI. Banks or any other financial institutions cannot use their data fully for things like finding frauds, managing risk, and developing new products.Slow Market Response:
Banks cannot swiftly obtain and analyse data to adjust to market movements and client preferences. Such consequences may include lost prospects and a competitive edge.
Security Issues
Increased Attack Surface:
Data silos invite cyberattacks. Security teams must monitor and secure each silo, increasing data security risk and complexity.Risk of Data Leakage:
Data spread across systems increases the risk of unauthorised access, resulting in financial penalties and harm to one’s reputation.
These issues demonstrate data silos’ considerable influence on banking. Banks can achieve numerous advantages, enhance operational effectiveness, and attain a competitive advantage by confronting these challenges head-on and eliminating data silos.
Impact of Data Silos on FSCS SCV Report Generation
A data silo is an isolated data repository under the management of a single department or business unit inside an organisation, similar to how grain and grass in a farm silo are kept separate from the outside world. Usually kept in a stand-alone system, siloed data is frequently incompatible with other sets of data. As a result, accessing and using the data becomes challenging for users in different sections of the organisation.
Data silos can originate from cultural, organisational, or technical factors. They often develop organically in big organisations due to the possibility of autonomous operation, goal-setting, prioritisation, and IT funding by distinct business units. If an organisation lacks a well-thought-out data management strategy, it may result in the creation of data silos, leading to:
- Missing customer title
- Missing customer name
- Invalid date in customer DOB field
- Missing address line
- Missing postcode
- Possible duplicate customer Ids
- Possible ineligible accounts
- Customer detail exist but account detail missing
- Account detail exist but customer detail missing
- Different account balance captured between aggregate balance and accounts balance
- Country code exists in country field
- Country name not matched with ISO standard country name
- Missing or invalid currency code
- Data format issue
- Duplicate passport number
- Invalid company registration number, etc.
The systems would not exchange data without appropriate data integration. This would increase the likelihood of errors and delays by requiring manual intervention to compile the customer’s data for the SCV report.
Thus, the generation of FSCS SCV reports can be significantly impacted in various ways by data silos:
- Since crucial report information is kept separately and is not consolidated, siloed data could fail to adequately represent every aspect of a scenario.
- The reconciliation of data from many sources can be hindered or ruined, as the data definitions and formats are inconsistent.
- Manual data extraction and manipulation become imperative without integration, thereby elevating the potential for human error, and prolonging the creation of FSCS SCV reports.
- Data silos hinder comprehensive understanding of report information, potentially hindering the detection of emerging trends or potential issues.
- As data silos can significantly increase report generation time owing to manual labour, it leads to missed deadlines and potential regulatory non-compliance.
- Manually merging siloed data can lead to higher costs and resource demands for FSCS SCV report generation due to its laborious and error-prone nature.
Breaking Down Data Silos in Banks: A Detailed Analysis
Centralised Data Repository:
This serves as the cornerstone for addressing data silos. Create a central data warehouse with the sole purpose of storing all FSCS-relevant customer information. The implementation of this centralised repository eliminates the necessity to manually gather information from disparate systems and guarantees data consistency.Data Consolidation Process:
Data must be meticulously cleansed and transformed from a variety of sources. This comprises:- Standardising data formats (e.g., date formats, currency codes)
- Removing duplicate entries
- Resolving inconsistencies
Data Integration from Multiple Sources:
In addition to basic account information, it is important to link data from several consumer touchpoints such as accounts, transactions, demographics, and activities to produce an overall picture. With this integrated data strategy, FIs can create a comprehensive Single Customer View for every customer. A more accurate FSCS compensation calculation is possible with the understanding of their financial assets, risk profile, and bank connection.Single Customer View:
Combining data from several platforms creates a single consumer profile. A comprehensive view of a customer’s financial situation, including account balances, historical transactions, and risk profiles, is provided by this Single Customer View (SCV). By adopting this comprehensive perspective, precise identification of qualified clients and their secured deposits under the FSCS initiative is enabled.Data Governance:
Establishing explicit guidelines for data collection, storage, access, and utilisation constitutes defining data policies and standards in strict accordance with the reporting requirements of the FSCS (such as account balances and eligibility requirements). Ensuring consistency across all systems is achieved via standardising data formats, definitions, and code.Data Ownership and Access Control:
Designing strong data governance frameworks that grant ownership of certain data sets to departments while maintaining data security and privacy. Furthermore, access controls must be put in place to limit access according to user responsibilities and requirements, protecting sensitive customer data that is essential for FSCS SCV reporting.Cracking Down Departmental Barriers:
Lack of coordination and communication within departments frequently results in data silos. Collaborative initiatives and the use of interactive data platforms are essential for fostering a culture of information sharing and cooperation.Cloud Computing:
FSCS reporting can be enhanced by utilising cloud-based data processing and storage options. Cloud computing provides:- Scalability for effective handling of massive data volumes.
- Adaptability to changing FSCS reporting needs.
- Cost-effectiveness by removing pricey on-premise infrastructure.
Automation Tools:
Implementing automation tools can significantly improve banks’ FSCS SCV reporting by streamlining the process, reducing manual effort, improving data accuracy, enhancing efficiency, increasing regulatory compliance, and enabling better decision-making. Examples of automation in FSCS SCV reporting include data extraction tools, data quality checks, and AI-powered anomaly detection. By embracing automation, banks can enhance the accuracy, efficiency, and compliance of their reporting, strengthening their position within the regulatory framework and reducing human error.
Macro Global’s Ultra Solution to Combat Data Silos Problem
To overcome data silos problem in the context of regulatory reporting compliance, particularly in the Financial Services Compensation Scheme (FSCS) Single Customer View (SCV) domain, the following solutions and suites provided by Macro Global can be instrumental:
FSCS SCV Enterprise Solution Suite
SCV Alliance
- Offers a data-driven compliance platform for banks and financial institutions.
- Provides a comprehensive solution with 175 well-classified risks for automatic validation and compliance with FSCS requirements.
SCV Forza
- An automation platform tailored for FSCS SCV reporting.
- Enables streamlined regulatory operations, from data collection and cleansing to audit and screening.
- Can handle various data formats, including structured, semi-structured, unstructured, and database-specific formats. Supports data from various database systems like SQL, NoSQL, and data lakes, enabling seamless extraction and processing of data from different sources.
Key Features
- Utilises an intelligent platform for seamless data integration.
- Manages account segregations effectively to generate precise SCV reports.
- Facilitates seamless integration with Core Banking Systems (CBS) for multi-level data validations.
- Implements AI-based fuzzy logic to prevent data duplication and ensure accurate SCV reports.
- Adheres to ISO standards and FSCS regulatory requirements.
- Provides third-party integrations with databases like FCA DB, Royal Mail DB, and others.
- Incorporates data mining, cleansing, enrichment, and reconciliation functionalities.
- Enhances operational efficiency by reducing time-consuming inefficiencies.
- Guarantees data accuracy and compliance, ensuring “Green Status Adherence” with PRA.
- Improves risk management by proactively resolving exceptions and eliminating errors.
- Implements robust data protection measures in a secure Azure Cloud environment.
- Incorporates stringent encryption, authentication, and firewall measures for secure data handling.
By leveraging Macro Global’s SCV Alliance and SCV Forza, financial institutions can streamline their regulatory reporting processes, ensure data integrity, and enhance operational efficiency while maintaining compliance with FSCS regulations and industry standards.
SCV Alliance
FSCS SCV Audit Platform
