Top five customer-centric strategies to combat fraud and reduce false positives
The global pandemic is affecting consumers and businesses alike. Limited in-person interaction means less visits to brick-and-mortar branches, thus driving shift toward the online economy. Fraud attacks are reportedly on the rise with more transactions shifting online. Staying ahead of new fraud schemes is critical as is awareness and monitoring of organisations’ increased risk exposure. The push towards digital requires heightened protection for all organisations.
Experian’s Identity and Fraud Report for Asia-Pacific* found that 71% of consumers in the Asia-Pacific region have security as the most important element of their online experience. This is understandable given that the same report revealed that 50% of the businesses have suffered fraud losses; and more than two-thirds have reported increased concern related to fraud losses since 2018. This means security is key in driving customer-centricity for your business. To achieve great customer experience, it is important to understand their needs and concerns.
Achieving the perfect balance
Businesses must walk a tightrope for fraud detection and management: shut out the fraudsters, without deterring legitimate customers.
Incorporating too many steps into a customer experience journey (e.g. for account creation or authentication) in hopes of detecting fraud or reducing false positives will end up deterring genuine customers. This eventually leads to poor customer experience and reduced sales for the business.
In fraud detection and management, it is essential that a business takes on a proactive and reactive stance, and leverage customer data and cutting-edge technologies to achieve fast and accurate detection. Here are five of the best customer-centric strategies to detect fraud and reduce false positives.
1. Adopt a data-driven approach to Know Your Customer (KYC)
KYC is exactly as its name indicates. For financial institutions, it is the compliance-driven process of verifying customers’ identities as well as possible risks of taking them on.
While KYC is part of anti-money laundering (AML) initiatives, implementing it in your business is just the beginning of your anti-fraud efforts. KYC requires big data so you can identify them at both the general and transactional levels. This means that your customer data not only has to be accurate and current; but also include historical and industry data, online behaviour, biometrics, and even device intelligence.
With this extensive customer knowledge, you can respond to fraud threats more effectively, reduce false positives, and most importantly, maintain a good customer experience. This will also grow your business and ensure your data remains updated. As fraudsters apply the broad strategy of knowing what your customers like and don’t like (and how and where they spend), so should you.
2. Apply right-sized fraud solutions to reduce unnecessary customer disruption and better manage risk
One downside of going after fraudsters is that inevitably, there will be disruptions in how customers normally use and interact with your business.
To some extent, your customers will be accepting of this disruption if they know it’s for their own benefit. However, if they encounter issues even at the point of logging in or early in the transaction process, you’d have the opposite effect: the very customers you want to service will not feel welcome at all, much less served.
As of 2017, there is a whopping 30:1 ratio for disrupted legitimate customer traffic versus actual fraud attempts. This means 30 of your true customers are being hassled to stop just one fraudster. In layman’s terms, this can be called an ‘overkill.’
When we say you need ‘right-sized’ fraud solutions, we mean giving an appropriate response to a certain fraud attempt. So if fraud comprises, say, 1% to 2% of your transactions, you should have the appetite for only 4% to 6% of it to be possible fraud attempts. This strategy minimises disruptions and allows you to continue to deliver a good customer experience.
3. Leverage machine learning and real-time data aggregation
Unlike companies, fraud doesn’t follow a work schedule, nor is it a simple 1:1 effort. There are countless account origination or takeover attempts done worldwide per minute using sophisticated methods—in the United States alone, data breaches in 2019 went up 17% from 2018 figures, and exposed more than 164 million consumer records.
With rapid digitalisation and globalisation, the numbers will only go up. Experian’s 2020 Global Identity and Fraud Report states there is a predicted “excess of 79.5 zettabytes (or 79.5 billion terabytes) of generated data by 2025” and this will rise alongside the number of connected consumer devices. That’s a gold mine for fraudsters — and more than what entire digital-security teams are equipped to handle.
Fraud detection and management is a behemoth task which cannot be accomplished manually. New technologies such as machine learning and real-time data aggregation must be employed to allow businesses to keep up with (and then get ahead of) fraudsters.
Aside from lowering the number of false positives and keeping up with the speed of fraud (no matter how small the transaction), using the latest technologies increases financial institutions’ regulatory compliance and consistency across departments and subsidiaries.
A 2017 McKinsey article notes that banks that invested in machine learning, data aggregation, and process automation saw compliance-error rates go from 30% to <5%. False positive alerts can also decrease from >90% to <50%. That is a lot of manual review work saved and losses averted.
4. Future-proof your fraud detection and management systems
The only constant in fraud is that it is ever-changing. Therefore, the key isn’t just for business leaders to implement a one-time fraud detection and management system that carries the latest features and innovations. Your system must also be future-proof and agile enough to adapt to any change in tools or landscape.
By adopting an open Application Programming Interface (API) platform model, businesses have the ability to respond to these changes promptly. For example, Experian’s CrossCore™ is the first open API platform that gathers all of your fraud and identity services into one place — even those not made by Experian. Here, you can build a highly scalable fraud management system that’s fully customised for your business needs. Since it is an open platform, it will be fast and nimble enough to face any new fraud threat head-on, and 100% compliant with current regulations.
5. Prioritise customer experience
Last but not the least, all the above strategies ultimately serve to enrich customer experience to deliver greater business success.
Much has been written about customers abandoning their transactions when presented with too many choices or steps in account creation or authentication process—this is prevalent in industries such as e-commerce. Experian’s earlier Fraud and Identity Reports* agree on one more factor for transaction abandonment: customer distrust.
Specifically, 27% of customers will ditch a transaction if they don’t see any visible security measures. It can get worse; a business can damage its reputation by distrust alone.
What if customers see a transaction till the end, only to be declined by your business? 83% of them will feel “frustrated, upset, or even betrayed.” And that negative sentiment from false declines has actual measured costs — again, in the United States, it’s to the tune of US$331 billion back in 2018.
Not only does your multi-layer fraud detection system have to cover all bases from the fraudsters’ point of view, it must also maintain a positive customer experience throughout. Afterall, customers are the backbone of all businesses.
Customer-centricity is a key ingredient for success
Modern fraud is done with speed and creativity that businesses might find difficult to pinpoint and block as it happens. The fraud detection and management solutions employed are either still too slow to keep up, or partly involve manual review by in-house human teams. Both options result in financial losses and reputational damage for any business.
Instead of staying with a slow and reactive approach, you must be quick and proactive in fighting fraud.
This proactiveness relies on two aspects: putting your customers first, and capitalising on the power of big data. Knowing exactly who your customers are and what they need enables you to use strategies that reduce both false positives and overall business costs, while keeping you competitive and profitable in the long run.
*Prior Identity and Fraud Reports:
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