Business intelligence for finance: capabilities, tools, and integrations

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

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 for TradeSmith

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 for TradeSmith

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 for TradeSmith

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%.

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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

Common integrations for BI in the financial sector

CRM software

Invoice management software

Investment portfolio management software

Loan management software

Accounting software

Core integrations

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

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

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

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

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.

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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:

BI implementation cost factors
  • 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.

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.

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.

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.