PREVENTING ACQUISITION FRAUD EXPERT PANEL

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1 PREVENTING ACQUISITION FRAUD EXPERT PANEL JUNE 1, 2018

2 Company Overview Public company, on NASDAQ: MITK HQ in San Diego with offices in Amsterdam, London, and Barcelona Leader in financial services, Mobile Deposit at 95% market share, and global leader in identity verification

3 ID Analytics solves fraud, credit and identity challenges Unique insight into US consumers comes from the ID Network, the nation s first real-time network of cross-industry identity data Contributory Network Traditional & Alternative Industries Event & Performance Data Real-Time Updates Nearly 100% coverage of US adult population Over 2 billion high-value consumer transactions 54M new identity elements / day Over 250 leading US enterprises rely on ID Analytics solutions every day 7 of the top 10 card issuers 6 of the top 10 financial institutions 5 of the top 5 wireless carriers

4 Leading analytic software company, specializing in decision management Founded: 1956 NYSE: FICO Revenues: $943M (2017) 10,000+ clients in 100+ countries Industry focus: Banking, insurance, retail, health care 20+ offices worldwide, HQ in San Jose, California 2,900+ employees FICO technology introduced in early 90s Fraud Prevention and Detection It s what we do 5 Fraud Losses 65% 9, B 90% 10ms Percentage of global payment card traffic covered by FICO fraud solutions Percent of US credit/debit cards Banks participating in FICO s fraud data consortium driving insight and analytic innovation Active financial accounts protected by FICO worldwide providing a global perspective Average response time for fraud decisions rendered by FICO s low-latency real-time engine

5 Who is PointPredictive? AI Built To Stop Fraud Using Our Auto Lending Data Consortium

6 Health & Risk Metrics about Dealerships and their Inventory For Auto Finance Companies Digital Surveillance Technology Monitor Dealer Behavior Powerbook detection Dealer Marketing & Risk Scores

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8 Mitek s estimate of fraud s size Recent research by Javelin, current estimates for overall lending fraud losses are over $1 billion

9 Synthetic ID Fraud: 1 in 50 use fake SSN s Potentially Randomized SSNs Comparing expected and observed new account application rates 7% 6% 5% 4% 3% Observed Volume of Potentially Randomized SSNs Expected Volume of Potentially Randomized SSNs 5.8% 3.6% 2.2% of all apps 2% 1% 0%

10 FICO estimates that fraud is 10-20% of Bad Debt (Allowance for Doubtful Accounts) $7 billion

11 What is the size of losses? $8 $6 $5 $3 $2 In Billions $6 Billion Estimate 2018 $

12 Estimate of Dealer Fraud? Fraud Risk from Dealerships is driven by: Need to get customers funded Need for operating cash Wanting to make more money 5% of Franchise dealers & 26% of Independents raise the sale price more than $1,000 on average when selling to sub-prime customers Independents 30% 25% 20% 15% 10% 5% 0% Independent 23% 21% 14% 8% 6% 4% 2% 3% Franchise 25% 20% 17% 18% 10% 9% 9% 5% 3% 2% > k-3k 1k-2k up to 1k Same up to 1k 1k-2k 2k-3k > 3000 Mark down from advertised price Price Mark up from advertised price 26% Franchise 5%

13 How Mitek defines fraud Fraud generally is a misrepresentation of facts in order to deceive. Specific to identity, both use of true name (impersonation) and synthetic identity. Identity theft is not so much stealing someone s identity but misrepresenting identity to defraud.

14 How ID Analytics defines fraud First Party Fraud Fraudster uses own identity Third Party Fraud Fraudster steals a victim s identity Synthetic Fraud Fraudster establishes fictitious identity AKAs: Muling / Gaming Fraud Diabolical Fraud AKAs: Identity Theft Identity Fraud AKAs: Frankenstein

15 How FICO defines fraud FIRST PARTY THIRD PARTY Fraudulent obtaining of credit (often by falsifying information) without intending to pay it back Involves identity theft Refers to fraud that is committed without the knowledge of a person whose identity is used to commit the fraud

16 What is the definition of fraud? Intentional and material misrepresentation by the borrower, dealer or fraud ring such that it impacts the decision to lend, or performance of loan. *As defined by the Auto Lending Fraud Consortium 2017

17 How we define the Fraud problem For managing dealerships, we suggest a focus on suspicious activity whether or not it is fraud. Dealership Suspicious activity includes: Abusing what the lender or consumer expects Behavior that seems underhanded (e.g. might be illegal or fraud) Doing this repeatedly or in a systematic way Much easier! Fraud is too strict. When fraud is the criteria, lots of borderline stuff gets through. Focus on suspicious activity to protect your business and run a clean operation

18 The biggest gaps in the industry today Understanding what is normal loss vs. fraud loss.

19 The biggest gaps in the industry today Accurate Fraud Measurement Income Verification Aligned Incentives

20 The biggest gaps in the industry today Layered Controls Are Essential to Stop Brute Force Attacks Rapidly, Agilely, and Efficiently Data Aggregation and Orchestration: Access and decision with a coordinated approach across critical internal and external data including device, geolocation, reputation, and more Fuzzy matching: Give your fraud team control to manage strategies across key indicators such as shared personally identifying information and application metadata Investigate Smarter: Compare records-side by-side with automatic match highlighting, add fraud elements to Hotlists and Fraud Files with one-click, and visualize connections and patterns across multiple degrees of separation Dashboards and Reporting: See trends of growing cases and fraud types, operational indicators including applications processed by channel, and heat map the problem geographies

21 What are the biggest gaps? The Gaps Are Large in Auto 1 No Shared Industry Fraud Data 2 3 No Holistic Application Fraud Scoring Limited collaboration on stopping serial fraudsters

22 What is the biggest gap? Anticipating which dealerships will still be here tomorrow. Too much focus is on loan level issues. However predicting dealership business risk is important too. There is great data to facilitate this, easily accessible. But only a few companies are doing it.

23 What is preventing the industry from moving forward? Cost change is expensive Complacency status quo is easier Incentives are not always aligned

24 What is preventing the industry from moving forward? Regulatory Focus Focus on Market Share Fraud Fighting is Collaborative

25 What is preventing the industry from moving forward? 1 CALL TO ACTION 2 INDUSTRY COLLABORATION

26 What prevents industry from moving forward? Only 33% of auto fraud is known 67% of fraud is Hidden below the surface.

27 What prevents the industry from moving forward? 2 issues: a) Profitability. The industry is not getting hammered yet. This will change when volumes level off in the coming years especially as dealers struggle. b) Hunger for volume. Lenders may not be interested in scrutinizing too closely, knowing they have a good repo strategy if the deal fails.

28 How has interest in fraud prevention changed over time? What is driving the change? More and more interest in combating fraud. Terrorist organizations and organized crime have increased the stakes. EMV, data breaches, and increased usage of digital channels are creating gaps and driving change.

29 How has interest in fraud prevention changed over time? What is driving the change? Economic Cycle Remote Originations Data Proliferation

30 How has interest in fraud prevention changed over time? What is driving the change? The Growing Need for Improved Application Fraud Controls Explosion of new products and channels How to monitor all of these, in real-time? Risk management complexities: fraud and compliance monitoring How to get a complete view of customer with limited information? Rising cost of fraud and compliance monitoring How to improve a company s ability to prevent bad people from entering the books and to know when a good customer goes bad? 30

31 How has interest in fraud prevention changed? 80% of lenders 20% Spending same have increased their anti-fraud 80% Spending more spending year over year for last 2 years *PointPredictive Auto Lending Fraud Survey 2017

32 How has interest in fraud prevention changed over time? What is driving the change? Companies are now experienced getting burned by rogue dealers. So now we have interest in learning how to anticipate that. Also lenders are seeing how badly priced loan contracts hurt both the consumer and lender. Only the dealer benefits.

33 How does Mitek see the industry evolving digitally to address fraud? Elimination of knowledge-based authentication. Multi-factor identity techniques combining verification of identity documents and devices combined with biometrics.

34 How does ID Analytics see the industry evolving digitally to address fraud? Consumer Convenience Judgmental Lending Data Science Connected Technologies

35 How does FICO see the industry evolving digitally to address fraud? 1 2 Converge controls across products, channels, and threats for a holistic fraud program Free data from silos 3 4 Invest in analytics Leverage cross-industry expertise, experience, and lessons learned

36 How will fraud technology evolve Bank Statements Employment Identity Drivers License Income Utility Bills SSN digitally? 100% of Verifications Move To Mobile

37 Evolving digitally to address fraud Use digital surveillance to: Monitor and measure dealers via their website. It s more affordable than on site audits, usually can replace them It reveals how much the dealer invests in advertising It reveals how many cars they move in a month It predicts a dealer s business health It estimates the volume you can expect to receive from a dealer Digital surveillance is done via web crawling, just like Google.

38 How are companies using the Mitek solutions successfully? Three primary adoption paradigms: Front-end of process, identity verification as part of application/onboarding Back-end of process, identity verification a point of transaction or ahead of final funding Yellow-path, failure of primary mechanism, waterfall to IDV

39 % of Population Bad Rate How are companies using ID Analytics solutions successfully? ID Score identifies a portion of the population with an 11% credit bad rate (overall credit bad rate is 3.4%) 8% 7% 6% 5% 4% 3% 2% 1% 0% 0% ID Score 12% 10% 8% 6% 4% 2% Note: 45,000 credit bads Overall Population Bad Rate

40 How are companies using the FICO solutions successfully? Challenge: Check each airline passenger against a series of watch lists, no fly data, and white lists to determine whether they can fly, in order to keep terrorists off airplanes Solution: FICO Identity Resolution Engine technology Results: Performs 5+ million searches per day with burst rates of over 500 per second Searches in real time through data spread across dozens of departments and locations

41 How are companies using PointPredictive successfully? Reduce EPD Loss by 50% Accelerate dealer detection up to 120 days Streamline 20% of low risk applications

42 How companies use us successfully Reducing contracts submitted with large markup Faster review on questionable deals, faster funding Calling out dealers on bad behavior, improving overall behavior Floor plan lenders track how their inventory is marketed online 16% 14% 12% 10% 8% 6% 4% 2% 0% Loan Apps Marked up > $2k and finding the best dealers to target

43 What is the role of emerging technologies like AI and biometrics in fraud prevention? AI, specifically machine learning, and biometrics are enabling automated and real-time experiences that outperform human identity verification tasks.

44 What is the role of emerging technologies like AI and biometrics in fraud prevention? Artificial Intelligence Machine Learning

45 What is the role of emerging technologies like AI and biometrics in fraud prevention? Advanced threat detection using machine learning Continuous risk scoring of devices and users through proven streaming behavioral analytics Broad detection coverage of threat types: malware, stolen credentials, data exfiltration, and insider threat A standard, trustworthy measure of enterprise security risk Assess and monitor network risk introduced by vendors and partners Cloud-based platform continually monitors Internet-scale data for changes in security indicators

46 What is the role of emerging technologies AI and Biometrics? The sole role of these technologies is to enable lenders to achieve the perfect, frictionless balance between fraud and sales

47 What emerging technologies will help To control dealership fraud, Digital Surveillance is the future. Digital surveillance is monitoring and measuring a dealer via their website. It scales better than on site audits and usually replaces them. Digital surveillance is done via web crawling, just like Google

48 What is the future of fraud? More fraud! As some companies adopt stricter practices, fraud will shift to other companies that maintain relaxed policies In auto finance, 10 years from now the concept of car ownership will change. Autonomous vehicles, alternative financing models, and sharing economy will drive competition in this space.

49 What is the future of fraud?

50 What is the future of fraud? CNP Fraud ATO Emerging/ Evolving Internal RTP App Fraud Threat Environment Control Set Relative to Peers Payment Trends Regulation Counterfeit Existing Stolen DDA Merchant

51 What is the future of auto lending fraud? Shared Intelligence AI enabled detection Mobile enabled verifications STIP Streamlining

52 What is the future of fraud? Fraudster dealers seek the path of least resistance. They can either steal from lenders or consumers. If lenders protect themselves effectively, the fraudsters will go after consumers. Therefore, the future of fraud is in protecting consumers from illicit schemes

53 Contact Steve Craig Director, Product Mitek Systems Or follow on LinkedIn

54 Contact Criag Stokum Sales Director, Auto Finance (858) Garient Evans VP, Client Services (858)

55 Contact Fernando Lopez

56 More Information? Frank McKenna Chief Fraud Strategist Website: Blog:

57 Contact Josh Wortman

58 Joel Kennedy Director