Business intelligence for finance: capabilities, tools, and integrations
April 13, 2023
How the financial sector uses business intelligence
Finance business intelligence has a variety of applications, from looking backward to assess financial performance in the past to forward-looking financial management scenario planning and forecasting. Here, we have outlined some of the possible use cases of business intelligence for finance.
Planning, budgeting, and forecasting
- Forecasting a company’s financial performance and operational efficiency (revenue, net income, costs, etc.)
- Comparing actual performance with the planned one and drilling down into the reasons for any discrepancies
- Strategic planning (budget development, working capital management, risk management, resource management, succession planning, corporate tax planning)
- Developing and monitoring operational plans and budgets
- Creating what-if scenarios for business continuity plans
Cost and profitability management
- Monitoring important financial indicators: gross profit margin, OPEX ratio, operating profit margin, and net profit margin
- Determining the actual cost of a product, process, or service
- Product/service profitability analysis
- Identifying the most profitable products, services, customers, and customer segments
- Profit and loss reporting by customer or customer segment for acquiring, retaining, migrating, and growing the most profitable customers
- What-if scenarios and simulation analysis (adding or dropping products/services, adding new customers, changing delivery options, etc.)
- Profitability and cost variance analysis for identifying cost-reduction opportunities and determining profitability levers
- Formation of product and service prices based on the competitor's market analysis, discounts, and the number of refusals
Cash flow management
- Transaction monitoring, including deposits, withdrawals, claims, loans, and repayments
- Tracking quick ratio, current ratio, cash balance, and outstanding debts
- Accounts payable and accounts receivable forecasting
- Liquidity forecasting
- Scenario modeling for cash and liquidity ratios
Performance monitoring and analysis
- Monitoring critical financial metrics, including return on assets, working capital ratio, return on equity and debt-equity ratio, net profit, cash conversion cycles, and operating profit margins
- Monitoring and measuring the performance of the company and individual departments
- Comparing the company's actual performance against the planned one, identifying performance levers
- Value creation calculation
Customer intelligence
- Dynamic customer segmentation based on demographics, geography, or behavioral factors to personalize customer interactions
- Customer spending patterns analysis to identify potential customers/customer segments for cross-selling
- Uncovering the reasons behind customer churn to tailor products or services accordingly and manage churn
- Predicting customer behavior and customer behavior modeling
- Customer scoring for streamlined customer onboarding and predicting delinquency cases
Risk management and compliance
- Risk identification and management, including credit, market, operational and liquidity risks
- Analyzing risk exposure across multiple asset classes (stocks, bonds, cash equivalents, real estate, commodities, and cryptocurrency)
- Detailed analysis of potential deals and investments
- Simulating investment scenarios to identify the best investment opportunities
- Managing financial data for investigations, audits and inspections
- Regulatory compliance
Financial KPIs at a glance
Have a look at a sample financial statement report prepared by Itransition’s BI department that is based on Power BI and aimed at CFOs, financial departments, and C-level executives. It can be used to analyze the financial performance of a company as a whole or a get a more detailed view for the needs of specific departments.
Real-life examples of BI in the financial industry
BI consulting and engineering for a commercial bank
The customer is a privately held Canadian bank focusing on reverse mortgages and financial solutions for retired homeowners. They needed to analyze their performance and evaluate the effectiveness of their products and wanted to develop a BI strategy and get BI suites consultations. Itransition assessed the customer's data architecture, workflows, and business processes and gathered user requirements. Next, the team developed a detailed BI implementation strategy based on the results and prepared recommendations for enhancing the existing data architecture. The team also performed data modeling, designed scalable data stores, redeveloped ETL operations, and conducted a detailed comparison of BI platforms to choose the optimal technology stack.
Stock trading software development
The customer, one of the largest US-based providers of online investment and market research tools for individual investors and traders, approached Itransition to build an investment portfolio management ecosystem. Itransition delivered a set of financial technology tools for individual investors to monitor investments, analyze stock behavior, get notifications on the best investment opportunities, calculate the optimal size of investment based on actual stock data, and manage risks.
BI solution enhancement for InsightSoftware.com
InsightSoftware, a financial software company that delivers turnkey reporting and performance management solutions, approached Itransition to evolve its market-leading financial and operational reporting solution — InsightUnlimited™. Itransition improved the solution’s stability and report building performance, implemented the history tracking features, and performed integration with SAP. The implemented changes helped the customer decrease the report memory usage and reduce report opening time by 30%.
BI consulting and engineering for a commercial bank
The customer is a privately held Canadian bank focusing on reverse mortgages and financial solutions for retired homeowners. They needed to analyze their performance and evaluate the effectiveness of their products and wanted to develop a BI strategy and get BI suites consultations. Itransition assessed the customer's data architecture, workflows, and business processes and gathered user requirements. Next, the team developed a detailed BI implementation strategy based on the results and prepared recommendations for enhancing the existing data architecture. The team also performed data modeling, designed scalable data stores, redeveloped ETL operations, and conducted a detailed comparison of BI platforms to choose the optimal technology stack.
Stock trading software development
The customer, one of the largest US-based providers of online investment and market research tools for individual investors and traders, approached Itransition to build an investment portfolio management ecosystem. Itransition delivered a set of financial technology tools for individual investors to monitor investments, analyze stock behavior, get notifications on the best investment opportunities, calculate the optimal size of investment based on actual stock data, and manage risks.
BI solution enhancement for InsightSoftware.com
InsightSoftware, a financial software company that delivers turnkey reporting and performance management solutions, approached Itransition to evolve its market-leading financial and operational reporting solution — InsightUnlimited™. Itransition improved the solution’s stability and report building performance, implemented the history tracking features, and performed integration with SAP. The implemented changes helped the customer decrease the report memory usage and reduce report opening time by 30%.
BI consulting and engineering for a commercial bank
The customer is a privately held Canadian bank focusing on reverse mortgages and financial solutions for retired homeowners. They needed to analyze their performance and evaluate the effectiveness of their products and wanted to develop a BI strategy and get BI suites consultations. Itransition assessed the customer's data architecture, workflows, and business processes and gathered user requirements. Next, the team developed a detailed BI implementation strategy based on the results and prepared recommendations for enhancing the existing data architecture. The team also performed data modeling, designed scalable data stores, redeveloped ETL operations, and conducted a detailed comparison of BI platforms to choose the optimal technology stack.
Stock trading software development
The customer, one of the largest US-based providers of online investment and market research tools for individual investors and traders, approached Itransition to build an investment portfolio management ecosystem. Itransition delivered a set of financial technology tools for individual investors to monitor investments, analyze stock behavior, get notifications on the best investment opportunities, calculate the optimal size of investment based on actual stock data, and manage risks.
BI solution enhancement for InsightSoftware.com
InsightSoftware, a financial software company that delivers turnkey reporting and performance management solutions, approached Itransition to evolve its market-leading financial and operational reporting solution — InsightUnlimited™. Itransition improved the solution’s stability and report building performance, implemented the history tracking features, and performed integration with SAP. The implemented changes helped the customer decrease the report memory usage and reduce report opening time by 30%.
Looking for a trustworthy BI technology partner?
Financial BI selection criteria
Choosing the optimal BI technology is one of the major steps in a BI implementation project. The complex process is built on a comprehensive analysis of current and future business needs, goals, and expectations, which are unique for a company. However, the following functionality appears to be beneficial for most companies in the financial sector:
Vast data integration capabilities
including pre-built connectors and easy-to-use APIs for consolidating data from internal and external systems located on-premises or in the cloud
Automated data management
including data ingestion, data transformation, and data quality management capabilities
Advanced data governance and security management
to safeguard data from breaches and leaks, as well as to ensure compliance with the strictest industry requirements
Augmented analytics capabilities
to automatically generate actionable insights for end users with ML techniques
Advanced data visualization and reporting capabilities
to present complex data and insights in a visually appealing format
Self-service capabilities
including NLP support and drag-and-drop user interface to drive analytics decision-making for end-users with no tech expertise
Top business intelligence tools for finance
To start your technology evaluation process, we offer a list of current market leaders according to the 2022 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms.
Chart title: Magic Quadrant for Analytics and Business Intelligence Platforms Data source: Gartner (March 2022)
Power BI is an end-to-end BI platform that enables self-service business analytics at the enterprise scale. The tool offers more than 150 pre-built connectors that integrate with various data sources, including relational and non-relational databases, data warehouses, big data software, local files, and spreadsheets. The tool satisfies the analytics needs of non-tech users with self-service data preparation, analysis, reporting, and visualization, as well as the needs of skillful data analytics and data scientists. Power BI offers rich visualization and reporting capabilities and safeguards corporate data with row-level security, bring-your-own key support, and data encryption. The product is available as a SaaS option running in the Azure cloud or as an on-premises option in Power BI Report Server.
Product differentiation
- Augmented analytics capabilities, including intelligent narratives and anomaly detection capabilities
Pricing
- Power BI Desktop
- free
- Power BI Pro
- $9.99 per user/month
- Power BI Premium
- $20 per user/month or $4,995 per capacity/month with an annual subscription and an unlimited number of users
- Power BI Embedded
- from $1.0081/hour
- Free trial
- for 2 months
Limitations
- The on-premises version has functional gaps when compared with the cloud service
- Azure-only deployment
Tableau is a visual analytics platform that can be deployed in the cloud or on-premises. The platform offers native integrations with 80 data sources and supports self-service data preparation and no-code analytical data querying. Tableau is a user-friendly solution that caters to the needs of both power and casual users with visual data exploration, intuitive dashboard creation, NLP capabilities, and drag-and-drop capabilities. In addition, the tool enables enterprise-grade security by restricting user access with user filters and row-level security.
Product differentiation
- Intuitive analytics experience based on its patented VizQL engine, a user-friendly design
Pricing
- Tableau Creator
- $70/user/month
- Tableau Explorer
- $35/user/month (fully hosted by Tableau)
- Tableau Explorer
- $42/user/month (on-premises or public cloud)
- Tableau Viewer
- $12/user/month (fully hosted by Tableau)
- Tableau Viewer
- $15/user/month (on-premises or public cloud)
- Free trial
Limitations
- High premium pricing
- A steep learning curve
Qlik Sense empowers business users at all skill levels to make better business decisions elevating data literacy with seamless connectivity to hundreds of data sources, automated data preparation, AI-generated analyses and insights, drag-and-drop report and dashboard creation, and NLP capabilities. In addition, Qlik Sense offers data storytelling capabilities, group sharing, collaboration, smart search, and automated ML capabilities. The tool also supports shared, managed, and personal spaces, as well as row- and column-level security.
Product differentiations
- Deployment flexibility, including cloud, multi-cloud, and on-premises installation
Pricing
- Qlik Sense Business
- $30/user/month
- Qlik Sense Enterprise SaaS
- custom pricing is available upon direct request
- Free trial
Limitations
- Product pricing complexity
Common integrations for BI in the financial sector
CRM
software
Invoice
management
software
Investment portfolio
management software
Loan
management
software
Accounting
software
Core integrations
Accounting software
Importing data on financial transactions across assets and liabilities for finance teams to:
- Monitor and measure the company's profitability with comprehensive financial reporting
- Forecast accounts payable and accounts receivable
- Assess financial performance drivers
- Forecast future financial scenarios
Customer relationship management (CRM) software
Exporting customer data, customer sentiment, and customer transactions to:
- Identify the most profitable customers and customer segments
- Effectively profile customers
- Develop new cross-selling and upselling marketing campaigns
- Uncover the reasons behind customer churn
- Track changes in customer behavior
Loan management software
Importing loan data and information on borrowers to:
- Track and measure average loan cycle time, amount, pull-through rate, average loan value, application approval rate, and the probability of default
- Identify target customers and improve customer acquisition
- Better manage delinquency
- Assist in loan servicing
- Forecast loan demand and loan profitability
Investment portfolio management software
Importing client profile and investment data to:
- Analyze existing and potential investments
- Identify optimal investment time and amount
- Analyze investment risks
- Build models to make strategic, data-driven investment decisions
- Forecast stock behavior and optimize financial portfolios
Invoice management software
Importing invoice data (date of issue, numerical data, payment terms, taxes, invoice processing status) to:
- Get an insight into the volume and statuses of invoices
- Identify the average time for a payment cycle, late payment, fraudulent payments, and duplicate payments
- Conduct invoice processing analytics to identify process bottlenecks and overpayments
- Forecast invoice payments
Finance BI benefits
Smart decision-making
BI helps make sense of enormous amounts of disorganized data quickly and systematically. Companies can analyze internal and external data and make more efficient business decisions with immediate access to business data. At the push of a button, decision-makers can answer the questions like: What was this quarter's performance? How does a chosen strategy impact the received profit? What is the status of the customer credit pipeline?
Increased customer lifetime value
Business intelligence software helps identify the most profitable customers and target them with new products and services, creating discount and customer loyalty programs to retain those in doubt. Additionally, business intelligence tools are helpful for tracking customer retention metrics such as customer churn, revenue churn, repeat purchase rate, and customer lifetime value.
Risk mitigation
Using real-time and historical data analysis along with market and industry trends, BI software helps companies navigate more confidently in the volatile market and successfully manage risks. For example, companies can timely identify fraudulent activity or discover prospective delinquency cases to mitigate accounts payable risk. BI software also helps monitor employee conduct to ensure compliance with strict regulatory requirements.
Personalized customer experience
Business intelligence software facilitates massive customer data capture, dynamic customer segmentation, and behavior data mining and analysis. It enables personalization of content, product and services, pricing, and expert advice to evoke cross-selling and upselling, build customer loyalty, and enhance customer experience.
Time savings
With many repetitive tasks on their hands, finance departments leverage BI software to shorten the data aggregation and analysis cycle by automating data collection, entry, analysis, and control.
Minimized errors
Manual collection and organization of large amounts of data from multiple sources is time-consuming and error-prone. Therefore, companies use BI software to increase trust in data, save time and ensure high data quality – with no duplication, inconsistency, and loss.
Optimized marketing effort
With the BI software in place, companies can get an insight into marketing campaigns' profitability, measure spending, identify messages resonating with customers, and determine areas for improvement.
Need help with implementing financial business intelligence within time and budget?
BI implementation cost factors
The cost of implementing and managing a BI solution consists of hardware, software and labor costs that are defined by the complexity of the BI solution. To get a ballpark estimate of the financial BI solution, you have to define the following:
- Data sources – their number, integration flexibility, deployment environment
- Data for analysis – its volume, structure, variability, and format
- Initial data quality and data quality requirements
- Data storage layer complexity, if it includes an enterprise data warehouse, data marts, complementary data storage
- Data analytics complexity including the number of entities, data flow complexity, if ML and AI are required, streaming financial analytics, and real-time data analytics
- Data visualization and reporting requirements, including embedded reporting, self-service BI, custom visualization, and mobile support
- Data security and compliance requirements
Finance BI: adoption challenges and their solutions
Unreliable data
Inaccurate, incomplete, inconsistent, and irrelevant data can ultimately compromise the usefulness of a BI system-generated report or dashboard.
Inaccurate, incomplete, inconsistent, and irrelevant data can ultimately compromise the usefulness of a BI system-generated report or dashboard.
To ensure sufficient and valid data enters the BI solution, a company should build a comprehensive data quality management framework. This framework guides the processes of:
- Data quality assessment
- Data profiling
- Data standardization
- Data transformation
- Data quality control
An inseparable part of the data quality management program is ensuring that users understand the importance of proper data management and actively participate in data quality management activities.
Responsible data democratization
BI propels data democratization, meaning any authorized user can leverage business intelligence to make data-driven decisions. However, users can intentionally or unintentionally compromise data safety.
BI propels data democratization, meaning any authorized user can leverage business intelligence to make data-driven decisions. However, users can intentionally or unintentionally compromise data safety.
An effective self-service BI solution is well-governed. To protect corporate data and ensure the derived analytics insights add value, comprehensive data governance policies and rules should be applied:
- Access to information based on user roles
- Dynamic data masking and end-to-end encryption of sensitive data
- Multi-factor user authentication options
- User activity monitoring
- Regular risk and vulnerability assessments
- Complete data audit trail
Lack of company-wide adoption
End users are uncomfortable with the newly integrated software, even though it offers self-service capabilities such as interactive visualization, NLP, and drag-and-drop interface, continuing to use familiar tools such as Excel or other SaaS applications.
End users are uncomfortable with the newly integrated software, even though it offers self-service capabilities such as interactive visualization, NLP, and drag-and-drop interface, continuing to use familiar tools such as Excel or other SaaS applications.
To help mitigate the issue, we recommend companies to:
- Continuously monitor user activity and logs of user requests to identify potential adoption problems and issues
- When starting the deployment, find a relevant use case that demonstrates tangible benefits of the BI software and addresses specific pain points to encourage people to use the new software
- Promote company data culture and encourage continuous learning by delivering role-based user training, training videos, or other resources
Make financial BI a success with expert help
Finance is one of the most data-heavy industries, representing an excellent opportunity to process, analyze, and leverage data. In this scenario, business intelligence becomes a key enabler for business leaders to manage their financial organizations successfully. However, according to one of the recent surveys, the BI adoption rate in the industry is at most 50%. There are several reasons behind that, one of which is the need for a coherent BI implementation strategy and practical experience in selecting and implementing proper BI tools. If you're ready to implement an effective BI solution and maximize its ROI, you may rely on Itransition’s certified BI consultants.
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