Machine Learning Times
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By: Mousami Kshirsaga, Head of Pre-sales, Fundtech
Originally published at 


Transaction banking has made huge strides in recent years. The easy availability of new technologies has improved operating efficiencies and accuracy. Apart from this, the speed of transactions has also increased remarkably. The volume of transaction banking data generated has grown in tandem with the emergence of “predictive analytics” that helps to interpret data patterns to predict future behavior and thereby arrive at better decisions.

Corporates need to be constantly ahead of the game to manage a multitude of challenges—rising transaction costs, managing shrinking margins and higher liquidity requirements to name just a few. The analysis of the information will be capable of anticipating disruptive events and forecasting customer behavior patterns.

According to Aberdeen Group’s Financial Planning, Budgeting and Forecasting (FPBF) study, corporates using business analytics are able to reduce their time-to-decision making by 13%, compared to 10% for corporates who do not have such an analytical solution in place. Corporates having business analytics in place were able to provide 74% of their stakeholders with access to financial performance data, compared to the 62% by corporates without business analytics.

Predictive analysis can also produce Key Performance Indicators (KPIs) and Key Performance Predictors (KPPs) that can assist management to review the functioning of various businesses and operations and arrive at suitable decisions to ensure better control and governance. Suitable triggers will ensure that there is proper oversight for key performance targets.

The facts generated by the use of powerful and versatile data mining and modeling tools are what help better decision-making by the corporate. Real-time predictive analytics will provide suggested outcomes, and it will be left to the management to make decisions and execute required solutions.

The predictive analytics technology solution should allow filters and other several metrices to be displayed on a single screen. Dashboards with visuals, charts and dials, should allow users to interact with information and drill-down to detailed data. This will allow business users to manipulate and explore information freely in near real time.

The scope of predictive analysis in transaction banking helps to improve decisions not only in the areas of risk, fraud mitigation, but also around liquidity and collateral management, making it an indispensable tool for the business. A better understanding of challenges and an ability to identify opportunity can be a game changer for any business.

By: Mousami Kshirsaga, Head of Pre-sales, Fundtech
Originally published at

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