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10 data science considerations for financial institutions

Advanced data science promises numerous benefits to financial institutions in a wide variety of areas, including marketing, sales, operations, consumer intelligence, portfolio management, risk and compliance. Here are 10 significant areas of concern that financial institutions should consider as they evaluate their technology priorities: Artificial intelligence (AI) – AI can …

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5 ways to benefit from Big Data

FinTech businesses have turned Big Data into big money through greater process efficiencies and more consumer conveniences. Here are 5 ways financial institutions can use Big Data to their advantage: Analyze consumer opinions and moods – monitoring and analyzing online reactions to products, services and brands help financial institutions better …

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Embracing data-driven analytics and the future of business

By capturing and leveraging massive volumes of data, financial institutions can capitalize on new data-driven business opportunities. In fact, financial institutions are already well on their way to doing so in four main ways: improving consumer experiences, optimizing risk controls, automating business processes, improving operational efficiency. These are accomplished using …

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How financial marketers can best interact with data

You don’t need to be an expert at artificial intelligence (AI) or machine learning to use data analytics effectively. In fact, the most sophisticated form of machine learning is the one that resides between our ears. Given that humanity is expected to produce 40 zettabytes (a zettabyte is a 1 …

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Good data governance is just as important as having good data

Data now rules our lives. But when data is of poor quality and/or not handled properly, both businesses and consumers can suffer. This makes good data governance of the utmost importance for financial institutions. Ultimately, good data governance should have the goal of achieving and maintaining coherence and consistency across …

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Video: 3 important ways financial institutions are leveraging Big Data

Our friends at Pepperdata examine 3 important ways leading financial institutions are leveraging Big Data and analytics to improve their bottom line in this quick but informative video.  Traditional banks increasingly embracing Fintech Where financial institutions need to look for personalization data The pros and cons of internet banks

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5 ways financial institutions are improving anti-money laundering measures

Money laundering is a serious global problem, and financial institutions are under increasing pressure from regulators to help put a halt increasingly-sophisticated criminal laundering attempts. One of the primary tools used to combat money laundering is customer risk-rating models. As currently implemented, however, these models are proving inadequate. Now, regulators …

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Leveraging the advantages of data science

Advances in data science have now reached the point where they allow for a more comprehensive and accurate picture of growth opportunities and potential performance improvements to be developed. Specifically, data science helps an institution answer the following questions: What is your positioning related to that of your competitors? Are …

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Top 10 data breaches to impact the financial services industry

Consumers expect financial institutions to provide an expert level of security when it comes to sensitive data. Over the years, however, some of the biggest data breaches have involved, in some way or another, financial institutions. Here’s a quick look at ten of the biggest data breaches impacting the financial …

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Study finds consumers willing to share personal data for benefits

According to an Accenture Plc study, most consumers around the world would be willing to share more personal data with financial institutions if it meant that they received better services. Specifically, the study, which surveyed 47,000 consumers across 28 countries found that 60% of consumers are willing to share lifestyle …

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Personal data leaks: the disease of the digital world

With all the recent news about cyberattacks and data leaks, one might sometimes wonder if he/she is really a target. After all, why would someone be interested in the data of an ordinary, maybe even unremarkable person. But the reality is that hackers are interested in whatever personal data they …

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Why data analytics goes beyond just more data

It has become obvious to most business that data is a necessary part of doing business; however, businesses must go beyond simply collecting data for it to be useful. Here are the top 10 reasons why analytics-driven digital transformation requires businesses to go beyond just generating more data: Data empowers …

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Research indicates data quality and control are growth drivers

In an environment where financial institutions are facing the regulatory need for increased transparency alongside a continued increase in data volume and velocity, the “ability to leverage data to analyze product and customer profitability, market opportunity and product suitability is critical to survival and success – and the time horizon …

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Navigating the open waters of data

With the rise of Big Data also comes the concept of a data lake – a repository of information so large it is somewhat like a vast body of water in that it can “hide” interesting and valuable bits of data by its sheer size. This is evidenced by the …

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Financial institutions turning to alternative data

Financial institutions have long used data as a way to minimize risks. This data, however, typically comes from traditional sources (credit bureaus, SEC filings, etc.). But many (79% according to a Dataminr survey) are now turning to alternative data sources such as social media, cell phone data and product reviews …

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Where financial institutions need to look for personalization data

Despite the progress personalization has made in other sectors, financial institutions are falling short. The trouble is that personalization can’t be bought; it can only be built through data. And until recently, financial institutions — and consumers and small business owners, for that matter — had little reason to share …

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3 fundamental pillars of developing a data strategy

Data is the hottest new commodity around the world. For financial institutions, much data is already readily available to them (e.g. basic client information, client transaction histories, etc.); however, digitalization also allows financial institutions to tap into various sources of external data such as mobile operators, geospatial data, credit bureaus …

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