It helps organizations to meet their most critical challenge of managing high false positives and provides a holistic view of investigating an alert. AMLOCK Analytics uses various statistical methods and machine learning algorithms to derive analyses and predictions based on institution specific historical data. One of the important features of 3i Infotech's AMLOCK Analytics is the reduction of false positives using risk profiling, through predictive analytics that identifies potential risk and thereby enhances decision making. The solution also provides an insight on the trends followed by customers, based on seasonality and identifies the anomalies based on deviation from these trends, where machine learning helps in customer segmentation. This enables users to investigate effectively by working closely on those groups which are risky or deemed outliers. Ravikanth Sama, Global Head- AML Practice, 3i Infotech said, "AMLOCK Analytics blends both the traditional rule-based system and the power of Analytics to bring better efficiency & risk focus.

This enables banks and financial institutions to identify complex and hidden AML patterns. It helps organizations to meet their most critical challenge of managing high false positives and provides a holistic view of investigating an alert. AMLOCK Analytics uses various statistical methods and machine learning algorithms to derive analyses and predictions based on institution specific historical data. Ravikanth Sama, Global Head- AML Practice, 3i Infotech said, "AMLOCK Analytics blends both the traditional rule-based system and the power of Analytics to bring better efficiency & risk focus. It can be hosted both on-premise and on cloud infrastructure. The solution provides a probability score indicating the chances of closing an alert based on the past actions taken by the users on similar alerts. AMLOCK Analytics improves the conversion rate of Suspicious Transaction Report (STR) or Suspicious Activity Report (SAR), as it dynamically correlates between the alerts in which suspicious transaction reports have been generated and those that have been tagged as false positives by the investigators."

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According to a recent Indian jobs study, data science is one of the topmost and fastest growing fields in India and its relevance is increasing in almost every sector. Reports from NASSCOM suggests that India's data industry would reach $16 billion by 2025 from the present level of $2 billion. At the core of it, data science is the science of examining raw data and applying statistical techniques for the purpose of drawing business related conclusions and predicting business outcomes. In every organization, there are opportunities to implement data science and transform the way business is carried out. Leading analysts like Gartner and Forrester have quoted 2018 as a milestone year for organizations, with over 70% of them expected to leverage data science for Business Optimization.

The Fourth Industrial Revolution -- a global transitioning to a new set of systems and the integration of digital and physical technologies -- is upon us. Processing is rising exponentially, knowledge is becoming accessible to more people and information gathering is at an all-time high. Over the years, we've seen information technology have an increased role in the furtherance of humanity's cause for innovation and digital evolution. With new technologies such as artificial intelligence, the Internet of Things, energy storage and quantum computing, the future holds even greater potential for human development. The ubiquitous nature of information technology and its integration into virtually every facet of daily living has brought it within proximity of otherwise personal data.

As organisations attempt to peer into the crystal ball, trying to understand what the future holds in store for them, a few predictions strongly indicate the shape of things to come. According to the IDC FutureScape: Worldwide Intelligent ERP 2017 Predictions, 35% of businesses in 2018 will be looking at intelligent ERP systems for optimal utilisation of resources and to improve processes. In other words, one out of three entities will be looking at assistive and conversational interfaces in ERP applications, given the present levels of AI. Industry specific applications will see AI playing a greater frontline role, enabling automation of processes and to uncover insightful information from data residing in ERP systems. Predictive management of inventories, forecasting of achievable targets and assistance in pricing strategies are just a few of the areas where AI will play a more dominant role.