Industry: Fraud

Podcast: The Fintech Diaries Podcast

Written by provenirmulti on December 2, 2024. Posted in Resource. No Comments on Podcast: The Fintech Diaries Podcast

podcast

The Fintech Diaries Podcast:
Fighting Fraud with Provenir

How AI is Securing Finance

Check out this exciting episode of The Fintech Diaries Podcast, featuring Jason Abbott, Provenir’s Director of Fraud Solutions. In this episode, Jack Tyrrell dives deep with Jason to explore the transformative power of AI and cutting-edge technology in fraud prevention. Get insights into Provenir’s innovative fraud detection tools, the role of data and AI, and a behind-the-scenes look at the tech and talent driving change in the fight against financial crime. Listen Now!

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Three Steps to Fight Telco Fraud

Written by Allison Karavos on November 25, 2024. Posted in Blog.

BLOG

Minimize Risk, Maximize Activations:
Three Steps to Fighting Telco Fraud

Do you have billions of dollars to spare?
If not, keep reading.

Telecommunications (telco) operators lose an estimated $40 billion to fraudsters each year, and it’s getting worse.

Last year, telco fraud increased 12%, worth an additional $38.95 billion lost and with the rising cost of handsets, fraudsters are getting away with higher value products and services. It’s becoming harder than ever to identify fraudulent behavior as it becomes more complex – there are more than 200 types of fraud within the telco industry alone. The problem clearly isn’t going away any time soon.

SIM swapping:

Where attackers manipulate providers’ security protocols to hijack users’ phone numbers, allowing unauthorized access to sensitive personal data and financial accounts.

But don’t throw up your hands in defeat just yet! Telcos can fight back with three highly effective tactics that together can reduce bad debt up to 69%. Just use the three As:

Access
Analyze
Action

At the core of it all? Another A: alternative data. Feeding alternative data into each step of the fraud mitigation process is the key to recapturing billions in annual losses.

Access

The first step to fighting fraud is Access – accessing data, including alternative data, provides more thorough information for fraud and KYC checks during the activation processes.

A common kind of fraud at this stage of the customer lifecycle is subscription fraud, which can be very costly. Fraudsters use stolen IDs and credit card information to create accounts, buy expensive handsets, and either pocket the free merchandise or resell it. If the criminal is purchasing a state-of-the-art smartphone, that’s potentially thousands in lost revenue from a single scheme.

Access to a deep well of traditional and alternative data sources empowers you to identify even the most subtle abnormalities during fraud and KYC checks at onboarding. For example, synthetic IDs are commonly used by fraudsters to open accounts, which can be difficult to catch, since synthetic IDs use some legitimate elements to fly under the radar. Alternative data can give you the clues you need to spot fraud, even in cases like this. Check the email to see if there are any minor changes or see if the geolocation matches social media activity.
Analyze

Step two is Analyze: accurately analyze all the data you’ve accessed. And don’t just analyze it the old fashioned way – integrate embedded intelligence like machine learning and AI into your analytics.

Say a phishing victim has had their phone breached and the criminal has text forwarding activated so they can receive a security code. AI/ML analysis of mobile data could alert a risk team that texts are being forwarded, and suggest further checks be performed.

Tactics like account takeover can cause damage even after onboarding. Imagine having to catch tiny inconsistencies for hundreds of thousands of subscribers throughout the entire lifecycle all on your own. It can be a challenge for legacy decisioning solutions to identify complex fraud indicators.

Having smart, automated technology that can pick out unusual data and analyze it quickly and accurately will make the difference for both new and active subscribers. Machine learning and AI gets smarter as it analyzes data and behavior, getting better at recognizing fraudulent patterns that would have otherwise been overlooked.

Optimize your fraud process with machine learning and AI technology that can analyze any kind of data and improves its accuracy with each analysis.
Action

The final step to help you stop fraud is Action: when you have accessed all the traditional and alternative data you need and AI/ML has analyzed it, you are ready to decision.

If the first layer of checks don’t yet paint a clear picture of the legitimacy of a subscriber, your decisioning solution can look deeper into the data for further analysis. Depending on your model, you might instead offer them a plan for high-risk subscribers, or reject them outright. If everything checks out, on the other hand, your decisioning engine would then approve and onboard.

Advanced decisioning uses all of the data you’ve gathered to make the most accurate decisions- that protect you against fraud. It improves efficiency and saves you money by performing only necessary checks – you never have to take a one-size-fits-all approach.

Once decisions are made, the outcomes are fed back into the platform, adding even more valuable data and analysis to help the AI/ML technology guide your decisioning to more accurate decisions in the future.

International Revenue Share Fund (IRSF):

Involves the exploitation of premium-rate numbers to generate large call volumes and siphon profits – with impacts extended beyond financial losses to include damaged customer trust and brand reputation, and increased operational costs.

We’ve seen some examples of how alternative data can fuel a decisioning engine to fight fraud, but what is it exactly? Check out the top three things telcos should know about this powerful tool.

Part 2:
Three Things Telcos Should Know About Alternative Data

The financial landscape is vast, especially at a global scale. Telco spans that landscape, as wireless services and products like handsets and modems are in high-demand among people from all financial backgrounds. To reach them, you can’t only rely on traditional data like credit scores to determine risk of default. Collecting and using alternative data can help you impact countless lives, tapping into an enormous worldwide market.

1. What is alt data?

It’s not data that wears eyeliner and plays guitar – it’s a powerful tool for financial inclusion.

Simply put, alternative data is all the information not maintained by credit bureaus that can paint a more holistic picture of a person’s financial health and overall risk. It can include financial information like rent, utility, or even telco payments, but also analyzes other information like social media activity, geolocation, and property records.

Alternative data can tell a more complete story than traditional data alone. There are nearly 30 million “credit invisibles” in the US and close to another 10 million in Canada, joined by 70% of Latin America’s population, 70% of Southeast Asia’s, and almost one quarter of the entire world – there are nearly 1.4 billion people without banking or credit history. That’s an awful lot of people who wouldn’t be qualified to open a telco account via traditional methods alone.

And while credit scores have proven to be strong indicators of whether someone will pay their bills on time, doesn’t it make sense to actually take into consideration utility and other recurring payment patterns to predict the same behavior for telco? Over 90% of Americans make payments on financed mobile phones, but only 2.5% of consumer credit bureau files contain telco payment information. While you might have the payment records for your own subscribers, being able to access that information for those looking to switch operators would be a reliable way to determine risk. Layering in utility data on top of credit scores gives you highly relevant insights to provide even stronger indicators of risk.

Telco, utility, and lease/property information is often highly indicative of credit trustworthiness but just isn’t considered by credit bureaus. That’s why alternative data is so powerful.
2. How to pull alt data?

Telcos can access alternative data through public records, along with any data partners you might have integrated into your decisioning solution. These data partners could share social media activity, employment information, and more – what you can access all dependent on your region’s compliance rules and regulations around credit decisioning.

While this information may not have as direct a correlation with credit trustworthiness, it can give you a fuller picture of someone’s lifestyle. Social media, for instance, can be a very enlightening source of alternative data, giving you insight into activities and habits that may be relevant. As more social media companies begin to offer embedded payment options on their platforms, someone’s Instagram profile could provide you with a look into their transactional behavior. Understanding how often a person shops on Instagram, how expensive the items they buy are, and if these purchases relate to the timeliness of their bill payments could be helpful ways to analyze this behavior.

Make sure you have access to data integrations and partners that will offer you the widest lens within the required parameters to look at subscribers in order to get the best results from alternative data. Choosing technology that can accelerate partner integration and alternative data access will guarantee rapid ROI, connecting you with more subscribers, faster.
3. Does alt data work?

Yes! Credit scores may not necessarily reflect a person’s current financial health, as the score heavily weighs past credit behavior in addition to current behavior. Even if someone is very responsible in the present, bad decisions from their past could still negatively affect their credit. If you ran that person’s profile through your traditional decisioning process, they might get flagged as high risk, leading to an inaccurate assessment. The same would be true of someone who never had access to credit due to past financial status or discriminatory lending practices. Alternative data solves that problem.

And there’s evidence to support it: 64% of lenders/credit providers that use alternative data see improved risk assessment, 48% have an increase in offer acceptance, and 64% see tangible benefits within one year of implementation. Other benefits include improved decisioning accuracy, better fraud protection, greater financial inclusion, faster speed-to-market, rapid onboarding, and overall maximized value.

We’re living in an era where information is as accessible as it’s ever been – it’s time to use it. The telco industry is at the forefront of innovation, so why keep assessing creditworthiness the same way we did decades ago? When you integrate alternative data into your decisioning, you’re making the world even bigger for millions of people who need telco services and inviting in low-risk subscribers that will accelerate your growth.

Where does intelligent risk decisioning come in?

Intelligent, holistic risk decisioning solutions can play a pivotal role in empowering telco providers to combat fraud effectively. By leveraging real-time data integration (ahem, the three As already covered) and machine learning, these advanced fraud solutions can analyze vast amounts of data from multiple sources at every stage of the customer journey. This enables you to ensure that fraudulent activities are detected and prevented before they escalate, enhancing speed, accuracy in decision-making, and improving the subscriber experience. Provenir customer MTN was able to stop an additional 135% of high-risk transactions via fraud mitigation solutions, without adding friction to the application process. Implementing intelligent risk decisioning not only mitigates fraud but also improves operational efficiency and enhances the overall customer experience. Ready to fight back?

Discover how Provenir can help you maximize subscriber value, minimize risk, and enhance customer satisfaction.

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Blog: The Growing Threat of Fraud in Auto Lending and How to Combat It

Written by Allison Karavos on November 20, 2024. Posted in Blog. No Comments on Blog: The Growing Threat of Fraud in Auto Lending and How to Combat It

The Growing Threat of Fraud in Auto Lending and
How to Combat It

How intelligent decisioning can keep you ahead of fraudsters

As fraud continues to increase in the automotive industry, the impact it has on financial services providers and vehicle buyers is significant. Thanks to the high-value transaction of car buying, and a growing shift towards digital loan applications, fraudsters are finding increasingly sophisticated ways to exploit vulnerabilities in the system. And it’s working for them – automotive fraud is up by more than 50% this year versus last year. Auto lenders are caught in a high-stakes environment, forced to balance the need for instant loan approvals and seamless customer experiences with robust risk management and fraud prevention measures.

This need-for-speed in application processing, driven by consumer expectations and mounting competitive pressure, can create gaps that fraudsters are ready to exploit – putting your financial stability, profitability, and industry reputation at risk. So we’re looking at common fraud schemes, the impact fraud has on the auto industry, and actionable insights for technology-driven solutions that can help you combat fraud in an increasingly digital, high-risk world.

Why is fraud so prevalent in auto lending? There are several factors that make auto financing an appealing target for fraudsters:

High-Value:

Auto loans tend to be high-volume and high-value, meaning successful scams can yield substantial financial rewards.
Consumer Demands:

Today’s digitally-savvy consumers have high expectations of fast loan approvals and frictionless experiences. When same-day decisions are expected, lenders face pressure to prioritize speed over robust risk mitigation measures, creating gaps for fraudsters to slip through.
Digital Transformation:

Further to consumer demands, the ongoing shift to online/digital applications exposes lenders to more sophisticated (and very rapidly evolving) digital fraud schemes, including identity theft and synthetic IDs.
Economic Uncertainty:

Fluctuations in vehicle prices, interest rates, inflation, and economic instability often results in desperation and opportunism, prompting both professional fraudsters (including organized crime rings) and financially strained individuals to engage in fraudulent activities.

It’s a perfect storm, making the automotive industry as a whole, and in particular lenders/financial services providers, increasingly vulnerable to fraud.

The Many Faces of Auto Lending Fraud – And Their Impacts

Fraud in the industry takes on many forms, each posing unique challenges to lenders – and requiring unique tactics to fight it. But what these schemes show is that the complexity and evolving nature of fraud requires advanced detection and prevention measures.

Application/First-Party Fraud: Where individuals use false identities or fabricate employment/income info to qualify for loans they wouldn’t otherwise be approved for. Fraudsters might fabricate pay stubs or employers, making it challenging for lenders to verify legitimacy of loan applications. Nearly 80% of all auto fraud cases involve first-party fraud.
Synthetic Identity Fraud: Even more insidious (and on the rise – there was a 400% increase in synthetic ID fraud in the automotive industry this past year), synthetic ID fraud involves creating entirely new identities, combining real and fictional info (i.e. mixing a real Social Insurance/Social Security number with fake personal details). Synthetic IDs often have clean credit histories, making them difficult to flag and enabling fraudsters to secure significant loans before disappearing.
Dealer Fraud: Dishonest car dealers can collaborate with fraudsters, inflating the price of vehicles or falsifying loan documents to secure higher financing amounts, leaving lenders at risk when the loan defaults
Title Washing: This involves the alteration of a vehicle’s title to hide its history of accidents or salvage status – misleading both lenders and potential buyers and making a car appear more valuable than it actually is.
Re-Vinning: Involves removing the original Vehicle Identification Number (VIN) from a stolen vehicle and replacing it with a counterfeit VIN from a legally registered vehicle; disguising the stolen vehicle’s true identity and allowing fraudsters to sell/register it without suspicion.
Loan Stacking: When individuals apply for multiple auto loans simultaneously, often across different lenders. Securing multiple loans before credit bureaus or financial services providers have time to update records means that fraudsters can walk away with several financed vehicles, leaving lenders on the hook to recover losses.

The impacts of fraud affect financial institutions and the broader automotive industry with significant consequences for both lenders and consumers, including:

Financial Losses: Auto lenders and financial services providers collectively lose billions of dollars annually (estimated at nearly $8 billion in 2024) thanks to fraudulent activities. This affects profitability of course, but also creates a ripple effect with higher interest rates and less favorable loan terms for consumers as lenders try to offset their risk.
Operational Strain: Detecting, investigating, and managing fraud cases can require substantial resources (human and financial) and a large time investment. This can lead to inefficiencies in day-to-day operations of your business, diverting attention from core business functions.
Reputational Damage: Fraud incidents can erode consumer trust and loyalty, and expose lenders to regulatory scrutiny, tarnishing brand image and leading to further financial and operational repercussions.
Market Impact: Widespread fraud can contribute to inflated vehicle prices and exacerbate loan risk concerns, deterring both lenders and buyers, leading to declining car sales and impeding market growth.

Combating these challenges requires a concerted effort from the industry as a whole to implement proactive, efficient fraud prevention measures – and ensure the integrity and profitability of your business.

Staying Ahead of Auto Fraud: Best Practices and Solutions

A multi-pronged approach that combines advanced technology, collaboration, and strategic best practices is key to effectively combat the threat of fraud while still balancing operational efficiency and customer satisfaction.

Advanced Data Analytics:

Leveraging data-driven insights is essential in early detection of fraud. Advanced data analytics tools can flag unusual application behaviors (discrepancies in reported income, recurring patterns linked to synthetic IDs, etc.). Analyzing vast datasets allows lenders to identify even the must subtle indicators of fraud that would be difficult to catch through manual reviews, enabling you to more effectively minimize potential losses.
Identity Verification Tools:

Modern IDV tech plays a crucial role in authenticating applicant info. Tools that use biometrics, document verification, and cross-reference with government databases help ensure applicants really are who they say they are. These tools help auto lenders avoid false positives, improving the accuracy of fraud detection and maintaining a frictionless approval process for genuine customers. This allows you to significantly reduce fraud risks, while still supporting a satisfying customer experience.
Fraud Detection Software:

Integrated fraud risk decisioning software helps you streamline and strengthen fraud prevention measures through automation. Incorporating real-time decisioning and machine learning models that can adapt to evolving fraud tactics allows you to detect anomalies instantly and automate repetitive tasks, helping lenders save time and resources. This boosts overall operational efficiency, allowing your teams to focus on higher-value, more strategic tasks while maintaining compliance with relevant regulations.
Cross-Industry Collaboration:

Sharing fraud intelligence and best practices with other lenders and financial organizations in a variety of verticals can help everyone stay informed of new fraud schemes and threats. Cooperation greatly strengthens defenses and ensures a proactive approach to emerging fraud tactics, allowing you to stay one step ahead.
Continuous Monitoring:

Effective fraud prevention doesn’t stop at the application stage. Continuous monitoring of loan portfolios and borrower behavior can help you detect fraudulent activity across the customer journey before it escalates. Monitoring tools that use AI to analyze account patterns and identify signs of fraud helps you protect your business, maintain customer trust, and ensure longer-term financial health.

Key Capabilities to Consider in Fraud Solutions

When selecting fraud detection tools, look at prioritizing the following capabilities:

Real-Time Decisioning:
Instant assessments to flag potential fraud before loan approvals and minimize false positives
Machine Learning:
Adaptive models that learn from fraud attempts to refine detection methods
Automation:
Tools that streamline application processing and fraud checks to improve efficiency and reduce manual workload, while ensuring compliance with relevant regulations
Seamless Integration:
Software solutions that work seamlessly with existing systems to enhance your current fraud prevention methods – and ensure a frictionless customer experience

Future-Proofing Your Fraud Strategy With Provenir

Investment in the right technology is key to a successful, proactive approach to fraud and risk management. The foundation of future-proofing lies in adopting scalable, cloud-based solutions that are capable of adapting to changing fraud threats. Cloud-based platforms offer you flexibility and real-time updates, while AI-driven tech enhances fraud detection by rapidly and accurately analyzing large datasets to identify subtle, complex patterns that can otherwise slip through the cracks. And advanced AI tools will continuously learn from your fraud decisions, allowing you to refine fraud detection processes and stay ahead of fraudsters.

Provenir’s AI-powered fraud solutions offer you:

Data Orchestration

Bring your own data or connect to one of our market leading partners using Marketplace integrations

Decisioning

Real-time assessments, advanced analytics tools, and machine learning models to deliver intelligent fraud decisioning flows

Case Management

Streamlined referral handling and frictionless investigations

Decision Intelligence

AI-powered insights to understand and optimize strategy performance

Striking a balance between fast loan approvals and thorough fraud checks is essential. Integrating automated systems for real-time decisioning while maintaining robust case management for complex cases is key, alongside orchestrating data effectively and leveraging intelligent insights for faster, more accurate fraud decisions. By embracing advanced, scalable decisioning technology, you can fortify yourself against both current and future fraud threats – boosting operational efficiency, ensuring security and compliance, and delivering your customers a seamless, secure experience in their automotive journey.