Predictions for the Data Breach Industry in 2018

by Michael Bruemmer 2 min read December 11, 2017

Data breach industry predictions

High-profile data breaches dominated the headlines in 2017, and unfortunately, these attacks are anticipated to only increase in frequency and magnitude in 2018. Breaches like those that affected LinkedIn, Dropbox and Yahoo, serve as a wake-up call for organizations to implement processes for safeguarding sensitive data and defending against attacks. However, for every advancement in cybersecurity, cybercriminals become more sophisticated in their techniques. Just when it seems like we have learned our lesson from one breach, another, more significant one occurs.

As cybercriminals continue changing the rules mid-game, it has become clear that while they’re playing chess, we’re still playing checkers. To help better prepare you and your organization for potential cyber threats, our team has put together its yearly data breach industry predictions on the issues and trends surrounding data security in 2018.

Here are our five predictions for 2018:

  1. The U.S. may experience its first large-scale attack on critical infrastructure, disrupting governments, companies and private citizens.
  2. Failure to comply with new EU regulations will result in large penalties for U.S. companies.
  3. Perpetrators of cyber-attacks will continue to zero in on governments – this could lead to a shift in world power.
  4. Attackers will use artificial intelligence (AI) to render traditional multifactor authentication methods useless.
  5. Vulnerabilities in Internet of Things (IoT) devices will create mass confusion, leading to new security regulations.

Download our complimentary reportto learn more about how these trends will shape the coming year, see how we scored against our 2017 predictions, and check out our new section revisiting predictions dating back to our inaugural 2014 report.

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When a credit view and a fraud view are generated separately, they must be reconciled instead of read together in the same instant. Every handoff is a place where a decision slows down and a signal gets missed. It's why a fraud pattern that would be obvious next to the credit file often surfaces only after the funds are already gone. Fragmentation also makes it harder to optimize lending strategies over time. When data, analytics and decisioning are disconnected, credit unions have less visibility into what's working, what's changing and where strategies need to be adjusted. An integrated decisioning ecosystem closes those seams by design, with credit, fraud and lending strategy running on one platform and accessed through a single Application Programming Interface (API). Identity and compliance capabilities can be an integrated decisioning flow. The data doesn't need to be reconciled after the fact because it was never separated in the first place. Stop overengineering, start removing friction When decisioning underperforms, the instinct is to build something more custom: a proprietary model, tighter segmentation, more configuration.  Custom modeling has its place for institutions with the scale and data to justify it. But often, for small or mid-sized credit unions, the bigger opportunity is a flexible decisioning strategy that uses a strong, continuously refreshed model. This shouldn't be either/or. The right approach gives credit unions a strong decisioning strategy today, with the ability to introduce more customized analytics and modeling as their needs evolve.  The same principle applies to strategy management: credit unions can gain greater control through self-service capabilities as they build a more sophisticated data science team.   That kind of flexibility is important as credit unions modernize their decisioning infrastructure. Research surveying more than 2,000 senior credit risk and fraud decision-makers across 11 countries found that organizations investing in unified platforms and modern infrastructure are moving faster and realizing the greatest Return on Investment (ROI).   As their needs evolve, credit unions can adjust decisioning strategies without introducing another layer of technology or relying on third parties to make every change. Until self-service is the right fit, choose a partner that understands what makes your credit union’s membership and risk appetite different from others.  Same member, same afternoon, faster answer Consider a credit union growing its auto and personal loan originations.  A member applies for an auto loan on Saturday afternoon. Credit data, identity and fraud signals are read together in a single real-time pass instead of separate reviews:  Most applications resolve immediately, approved or declined based on a more comprehensive view of the applicant. A smaller number are flagged for quick step-up verification and cleared within minutes. Only genuinely ambiguous cases reach an underwriter, who is working from one complete picture instead of reconciling multiple signals. The member has an answer before the weekend is over. The credit union books the loan before competitors even open on Monday. Built to scale This kind of process holds up today. However, the better test is whether it holds up eighteen months from now when application volume has grown, new products are live and the data flowing through the system looks nothing like it does right now. Future-proofing isn't only about handling more volume. It's about having room to be nimbler and make adjustments as quickly as the market changes. A credit union that relies on standard models within a decisioning strategy may want more customized analytics and greater control over its strategies tomorrow. Connect with us With more than three decades of credit expertise and one of the industry's largest data footprints, Experian helps credit unions do more than solve this year's friction. We're helping to build a decisioning foundation that scales, so growth becomes something the system absorbs, rather than something it must be rebuilt around. Explore More

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