7 Data Challenges in Financial Services and How to Overcome Them with BI

Table of Contents

    On average, financial companies analyze just 24 percent of big data collected. That means 76 percent of potentially valuable data plus the resources used to capture, manage, and store it get wasted, which is a significant loss.

    The incapacity to harness the full potential of data collected results from several manageable challenges like using outdated technology, human errors during analysis, shortage of skills, and data siloing.

    Our data analysts have highlighted 7 data challenges in financial services and practical ways to overcome them. Read on to learn how to pull maximum value from your collected data.

    Challenge 1: Inability to keep up With New Technology and Tools

    An advanced data ecosystem is the backbone of efficient data management. It helps collect quality data, analyze it in real-time, interpret it, and generate insightful reports for decision-making.

    Despite the benefits, only 59 percent of companies have up-to-date analytics systems and software. A majority, especially small and medium companies, are yet to adopt advanced analytic tools since they regard big data analytics as an expensive affair, preserved for giant corporations with a dedicated in-house team of data scientists.

    Overcoming the Challenge

    Several affordable and highly efficient data ecosystems exist for small to medium financial service companies. Therefore, cost should not be among the reasons you are yet to upgrade your data management tools.

    A Business Intelligence software analyzes big data comprehensively, giving accurate insights for data-driven decisions. Since it is easy to use and affordable, companies of all sizes can implement it into their day-to-day data management operations.

    What’s more? With BI, you get a complete data ecosystem that collects and analyzes data alongside creating data visualizations. The BI ecosystems also share reports for enhanced decision-making. You can use business intelligence solutions as a standalone tool for day-to-day data management.

    Challenge 2: Difficulties in Maintaining Data Quality and Integrity

    Businesses, including financial service providers, generate around  2.5 quintillion bytes of data in a day. With such enormous amounts of data streaming into databases, many financial companies face difficulty analyzing the data without compromising quality and integrity.

    Mainly, integrity and quality issues arise because some companies lack dedicated data analytics tools to handle vast amounts of data. Instead, they use old-fashioned analytics, prone to undetectable human errors.

    Overcoming the Challenge

    Financial businesses can easily overcome integrity and data quality issues by investing in data analytics. Data analytics processes data in real-time, eliminating the error-prone manual processes compromising data quality and integrity.

    BI tools like ClicData have data management features to organize and protect data integrity. They connect data from various sources and centralize it in a secure warehouse while maintaining historical data.

    With data analytics, your financial enterprise is likely to reap several benefits, including :

    • Improved data accuracy
    • Reliable decision making
    • Reduced data loss
    • Availability of reliable information
    • Improved public image

    Challenge 3: Trouble Aggregating Siloed Data

    In a typical firm, financial data comes from multiple sources. Some of it comes from inventory management, financial statements, and monetary transactions. Other data comes from legacy systems and customer relationship management tools.

    Since the data sources for many companies do not work in unison, the data collected often gets siloed. That means the valuable data is stored in multiple repositories instead of one central database.

    Uncomplicated as the issue sounds, data siloing has several issues limiting maximum data use. For example, companies have to spend lots of valuable time aggregating it. In the process, data scientists let go of vast amounts that could have generated valuable business insights.

    Besides losing significant amounts of time, the consolidation process is often marred by human errors, which generate less accurate, misleading reports. Relying on such inconsistent data leads to errors in decision-making.

    Overcoming the challenge

    To dismantle the data silos, your financial company needs good Business intelligence software that consolidates data from apps, CRM, and inventory management systems into a central repository.

    That way, your financial analytics team will have an easy time organizing, analyzing, and visualizing the data. Other benefits of eliminating data silos within your financial service organization include the following:

    • Accurate analytics
    • Enhanced data security
    • Reduced data management costs
    • Improved data visualization

    Challenge 4: Issues Creating In-Depth Financial Analysis

    Though somewhat effective, outmoded data management tools like spreadsheets offer superficial data analysis, denying enterprises an opportunity to get maximum value out of the big data collected.

    Using such tools defeats the purpose of spending your valuable resources collecting several gigabytes or terabytes of data, most of which do not help.

    Overcoming the Challenge

    Your firm can overcome this challenge by investing in groundbreaking tools designed to analyze data in great detail. With in-depth financial analysis, your company uncovers the complex patterns needed to make strategic operations, marketing, and pricing decisions.

    On the other hand, the insights from in-depth analysis tighten your position in the market, giving you the muscle to keep growing even when the financial sector is distressed. In-depth data analysis comes with other merits, including:

    • New opportunities for business growth
    • Optimized operational cash flows
    • More options for cost savings
    • Improved forecasting
    • Healthy organizational change

    How do you quit superficial analysis for in-depth financial analysis? While several financial tools offer financial reporting, BI analytics tools take the top slot. BI leverages the power of cloud computing, machine learning, artificial intelligence, and other technologies to analyze data sets exhaustively.

    With deep data analysis, your business can rely on BI to generate valuable data on critical financial KPIs, including net profit, burn rates, budget variance, return on equity, sales growth, account receivable turnover, and revenue concentration.

    “BI makes a real difference for financial teams. It takes us beyond just handling data, straight into the realm of actionable insights. The ability of BI to parse through vast datasets and deliver easy-to-understand reports, metrics, and trends really is a game-changer for the industry. It’s especially valuable in providing accurate insights into customer risk, loan defaults, and cost recovery, helping us manage operational costs and boost the bottom line. When we integrate advanced BI platforms with our existing financial software, we not only automate data tasks but also gain precious time for strategic planning, greatly enhancing our financial planning and analysis efforts.” – Max Benz, finance expert at BankingGeek 

    in depth financial analysis

    Challenge 5: Complexity Creating Reports Quickly

    As much as there are several advanced tools designed to streamline report creation, the issue comes in acquiring those tools. Some financial firms or departments feel like switching from their usual way of doing things is laborious, even when the benefits of change are apparent.

    Other firms are reluctant to automate report creation simply because they fear spending on new systems that could fail. After all, these companies have a couple of case studies of enterprises that couldn’t get their desired ROI after spending a significant budget on automation.

    Overcoming the Challenge

    Automating is the best way to expedite report creation and presentation. Unlike manual processes, automation tools use innovative technologies to create easy-to-follow, visually appealing reports in record time.

    Apart from expediting the report creation process and cutting down costs, automating reporting comes along with multiple paybacks like:

    • Helping your IT team work faster
    • Eliminating repetitive, monotonous tasks
    • Standardizing the report creation process
    • Eliminating human errors associated with creating reports

    Many BI solutions like ClicData are designed to automate the reporting process from start to end. Even financial companies without an in-house team of data scientists can easily create detailed reports using these business intelligence tools.

    Discover how Scrubbed, a consulting firm specialized in corporate finance consolidation uses ClicData for global account consolidation.

    Challenge 6: Trouble Making Accurate Financial Forecasts

    When analyzing data, many financial organizations focus on short-term goals, an issue that exposes many organizations to detrimental but avoidable market shifts. Even those focusing on the long term find challenges in making accurate forecasts.

    What is forecasting? In simple terms, financial forecasting entails using past performance records to plan for the future. It helps identify future weaknesses that can slow growth and opportunities that would propel your business to the next level.

    Overcoming the Challenge

    Like breaking up data silos and creating reports, your business should leverage Business Intelligence accurately to plan for the future. Disruptive technology helps make logical predictions based on past sales, revenue, and market performance.

    With efficient speculation, your firm gets the upper hand in making high-level plans for future hiring, budgeting, expansion, and financing. In the event of negative market shifts, your company will remain resilient for a reasonable duration.

    Challenge 7: Issues Sharing Data and Communicating With Stakeholders

    Chief financial officers do more than analyzing big data and making sound financial decisions for the organization. They prepare reports and present them to board members, investors, and stakeholders.

    The reports should highlight transparent and accurate recommendations that stakeholders should know. Simple as the task sounds, chief financial officers have a hard time making reports that present important information in an easy-to-understand format.

    Overcoming the Challenge

    With the right tools like ClicData, reporting to shareholders, partners, and board members is an easy-peasy task.

    The financial dashboard presents data in neat graphs and charts, giving shareholders interest in reading.

    With the neat, easy-to-understand reporting, ClicData’s visualization tool will:

    • Keep stakeholders informed about your business’ progress
    • Build confidence
    • Promote open communication
    • Positively influence stakeholder decisions
    • Increase the likelihood of project success

    Get the Right Tools to Overcome Data Challenges in Financial Services

    With businesses collecting terabytes of data daily, it has become necessary to ditch old data management methods like spreadsheets for newer ones like BI. Otherwise, your company will keep losing up to 76 percent of possibly valuable data.

    ClicData is a business intelligence tool designed to help companies get the most value out of the data collected. It speeds up data management processes like collecting, visualizing, analyzing, and sharing data. Start your free trial now.