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Dr. Eduardo Lagonegro

Open banking: the Basel Committee on Banking Supervision has its say

Therefore, increased speed of data transfer through advanced technology will boost the growth of prescriptive security during the forecast period. Prescriptive analytics is designed to solve precisely that problem, allowing every organization to better use their data, providing understanding into the actions they can take based on related insights. As the volume, velocity and variety of data continues to grow, the need for and value of prescriptive analytics will grow along with it. Prescriptive analytics is a discipline in its infancy, but with unlimited potential. In other words, predictive analytics can tell you what might happen next, whereas prescriptive analytics will tell you what to do about it, with very high confidence.

On the other hand, in “rules-based” regulation agencies stipulate in detail what the regulated entity can and cannot do. There is clarity about the compliance process, but the regulatory objectives may be ambiguous¹, providing fertile ground for potential “gaming” of the regulation. She is passionate about helping developers and security professionals navigate emerging threats, regulations and security trends to help organizations and their applications thrive in today’s complex digital world. Before joining Veracode, she worked in various roles at RSA and IBM Security globally with the mission to support customers raise their security posture. The usage of prescriptive security should be extremely useful for businesses.

Managing Prescriptive Content

The risk management projects on which UniCredit is working are tightly related to a broader evolution that’s affecting the data infrastructure, says Ivan Cavinato, head of credit risk methodologies for the Italian bank. “The goal is to replace the old traditional decision-making process by introducing a more agile, flexible and productive technology framework,” he says. Every business and organization generates data as part of its day-to-day operations. Prescriptive analytics goes several steps beyond business analytics, providing decision makers with potential recommended actions to take to achieve the desired results.

The rapid digital transformation in the past few months has significantly affected how cybercriminals operate. These changes will further impact the banking cybersecurity landscape in 2023. Moreover, the continuous change in technologies also implies a parallel shift in cybersecurity in banking.

Advantages of Using Prescriptive Security

It analyzes raw data and allows the user to make conclusions about that information. Hyperlink InfoSystem is one of the leading software development companies based in India and has offices in USA, UK, UAE, France, and Canada. With 10+ years of experience in the industry, Hyperlink InfoSystem served more than 2,300 clients worldwide. The company has a team of 450+ highly skilled developers who works on any custom solutions using the latest technologies.

  • Analysts’ rankings that consider security maturity may be affected; in turn, affecting the refinancing condition of a bank and the cost of risk for insurers.
  • The company has a team of 450+ highly skilled developers who works on any custom solutions using the latest technologies.
  • Banking, credit unions, and financial organizations rounded out the top three with 135 breaches.
  • Big data analytics in finance will continue to evolve and provide more accurate calculations and predictions as more companies use them.
  • Since computer processing power is continuously improving, prescriptive analytics technologies also improve.
  • Prescriptive analytics enables leaders to determine the best potential ideas in a simulation, instead of experimenting in real life.

Amilcar has 10 years of FinTech, blockchain, and crypto startup experience and advises financial institutions, governments, regulators, and startups. Following any serious incident, thoughts will turn to reviewing how the incident occurred, and how to predict and prevent similar attacks in future. 4 min read – IBM Turbonomic optimizes your Kubernetes prescriptive security environment through container rightsizing, pod suspension and provisioning, pod moves and cluster scaling actions. 6 min read – Direct usage of chatbots in an enterprise presents risks and challenges. Whereas previously you may have relied on confidentiality agreements and trust to mitigate insider threats, these are no longer enough.

Open banking: the Basel Committee on Banking Supervision has its say

With prescriptive security, the time it takes to identify a problem shrinks to milliseconds. Information about multiple events is collated into one place and enriched with threat intelligence ready as a single ‘ticket’ for the analyst to analyse and make decisions. In a traditional security environment, the analyst must first log into multiple tools to work out what is happening. The analyst uses each tool to view the necessary logs and data to understand the incident. Whilst the analyst might quickly establish that there is a ‘0 day’ polymorphic virus, the tools may not link the endpoint with the user in order to easily trace the phishing attack. Without this link, actions to update security at the boundary may not happen quickly, if at all; as a result, more users could be affected.

prescriptive security in banking

This type of data analytics tries to ask the question “Why did this happen?” As such, it requires much more diverse data inputs. But there’s a little guesswork involved because businesses use it to find out why certain trends pop up. For instance, it tries to figure out whether there’s a relationship between a certain market force and sales or if a certain ad campaign helped or hurt sales of a particular product. This means businesses shouldn’t use prescriptive analytics to make any long-term ones. Since the advancement of digital payments and digitization of the financial ecosystem, banks have become a primary target of cyber-attacks. The Federal Bureau of Investigation (FBI) has also stated that the instances of cybercrime have jumped by as much as 300% since the end of February 2020.

Prescriptive Security Market Emerges as the Next Frontier in Cyber Defense

As financial firms move to transform their intelligence into action, mathematical optimization is becoming a must-have tool for strategic and operational planning. Portfolio managers and other banking professionals can use IBM technology to explore scenarios in a fraction of the time, accelerating decisions and improving outcomes. The companies providing workplace as a service solution are adopting effective business strategies such as investment in R&D, acquisition, joint venture, collaborations, mergers etc., to enhance their market presence. For instance, in June 2021, Skybox Security launched new vulnerability prioritization capabilities with prescriptive remediation analysis. This will help the companies in reducing the cybersecurity attacks, remediation across complex hybrid environment and automate risk scoring.

Analytics embedded in algorithms can change your life, or at least your business. That’s true for UniCredit, Italy’s largest bank, which is putting a lot of effort into envisioning a model to handle very high volumes of data in its risk management operations. Getting started with prescriptive analytics requires that you either have in-house data analytics expertise, or are working with an outside vendor who can bring that expertise to you.

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However, the DFS rule mandates compliance with specific requirements, increasing regulatory risk for financial institutions. In addition, the annual certification requirement potentially exposes the individual submitting the certification to personal liability, as discussed in a September 2016 PwC post. There is much debate in the compliance community about the virtues and drawbacks of a “principles-based” versus a “rules-based” regulatory approach in ensuring effective compliance with regulatory obligations. On the one hand, in “principles-based” regulation agencies establish broad but well-articulated principles that a business is expected to follow. There is clarity about the regulatory objective, but not how to design and implement a compliance system that accords with it. Firms can’t second guess regulators and may need to institute more robust systems to withstand supervisory scrutiny.

prescriptive security in banking

For example, in a cybersecurity context, a solution based on predictive analytics could be used to analyze network traffic, identify anomalous behavior and send an alert when that behavior matches the pattern of a specific threat. With prescriptive analytics, the software would not only identify a potential threat but would suggest actions to shut it down. Prescriptive analytics, much like predictive analytics, relies on a combination of techniques and tools such as algorithms, machine learning and data modeling. These techniques are applied to the data sets selected by users and data scientists, including historical data, transactional data and real-time data feeds. Depending on the type of algorithm selected, the system will look for specific types of correlations among the data and then perform the desired function. Prescriptive analytics is thought to be the most sophisticated type of data analytics, designed not just to provide data and insights but to suggest a course of action.

What is the difference between prescriptive analytics and predictive analytics?

Prescriptive analytics is a form of data analytics that helps businesses make better and more informed decisions. Its goal is to help answer questions about what should be done to make something happen in the future. It analyzes raw data about past trends and performance through machine learning (so very little human input, if any at all) to determine possible courses of action or new strategies generally for the near term.