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    Home > Technology > MAKING BUSINESS INTELLIGENCE WORK FOR YOU
    Technology

    MAKING BUSINESS INTELLIGENCE WORK FOR YOU

    Published by Gbaf News

    Posted on August 17, 2015

    4 min read

    Last updated: January 22, 2026

    A group of professionals engaged in a business meeting focusing on implementing business intelligence in banking. This image illustrates the collaborative effort to enhance decision-making and risk management through data analytics.
    Business meeting with professionals discussing business intelligence strategies - Global Banking & Finance Review
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    By Karl Pardoe, Regional Sales Manager UK & Ireland at March Networks

    Business intelligence technology enables banks to derive meaningful information from masses of raw data, allowing more effective risk and customer service strategies to be developed. The major advantages include enhancements to tactical and operational insight and more informed decision-making. As a result, business intelligence (BI) and analytics are growing in importance, with 29% of banks citing the two as a top IT theme[i].

    With the technology predicted to continue growing by 4-5% per year for the next 3 or 4 years, BI and analytics deliver a solid proposition for banks as purpose built orgeneric devices or via vertically oriented reporting tools that leverage analytics.

    Karl Pardoe, Regional Sales Manager UK & Ireland at March Networks

    Karl Pardoe, Regional Sales Manager UK & Ireland at March Networks

    Why is this important to banks? The banking community facesmany threats including fraud, ATM skimming and cash harvesting, cyber attacks and online hacking. Although ATM related fraud incidents fell 26% in 2014, related losses were up 13%, and losses through skimming and ATM physical attacks increased by 18% and 17% respectively[ii].So banks need to reduce these losses and one of the most effective methods is by harnessing the power of big data, BI and video analytics.

    If a branch suspects that a skimming device has been installed in one of the ATMs, it can take hours to review and identify the right evidence from when the skimmer was installed. Video analytics, however, can narrow the options beyond just time and date. Transaction records, for example, a credit card being used, or a person detected at the ATM when no transaction was made can help to pinpoint the crime being committed.Video cannot possibly help to prevent physical attacks, but what it can do very effectively is identify the moment of the crime, reduce investigation times and help banks to locate ATMs that are more at risk.

    BI can analyse the history of fraudulent situations and develop useful fraud prevention business rules. These include models for predicting a card holder’s behaviour and alerts that can be set up if the average number of daily transactions suddenly increases.

    Fighting fraud is the primary use of BI and video analytics but it can also deliver insights that assist in increasing customer satisfaction. These include an overview of branch and staff performance, so changes can be made to reduce waiting times, and analysis of the influence and effectiveness of in-branch marketing activities.

    For banks, business performance analytics help to measure employee performance, to automate marketing and sales and innovate products; analytics can assess customer profitability and regulatory compliance whilst providing feedback on risk management.

    Analysing average daily withdrawals from an ATM assists in decisions about how much money to load into the machine. If the maximum amount is rarely needed, loading it to capacity will only prove to be a risk, given the high incidence of ATM physical attacks. Equally, BI algorithms can optimise cash management by anticipating time, place, and amounts of cash to be loaded, taking into account weekly, monthly and seasonal trends. A good reporting tool can help operators predict branch by branch, ATM by ATM, what the trends will be during the week and, in time, during the seasons.

    Making the transition from a product-oriented business model to a customer-oriented one is not easy for the banking industry. It requiresextensive monitoring of client relations, the ability to identify the most profitable customers, and which products those profits are typically drawn from, and monitor new product and market opportunities and the trends in customer behaviour.

    Banks can help themselves by turning daily transactional data into complex analysis involving customer and risk management, customer relationships, customer profitability, product and channel profitability, level of customer loyalty, evaluation of marketing campaigns, efficiency of operations, and market trends. The mechanism to achieve this goal is business intelligence and analytics.

    [i]Informa Telecoms & Media Research (Ovum) & Nucleus Search September 2014

    [ii]Source:  EAST, European ATM Crime Report, April 2015

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