Credit Lending
By: Joel Pruis So we know we need to determine the overall net yield on assets required to cover the cost of funds and the operating expenses but how? In the movie Moneyball, the Oakland A’s develop a strategy to win 99 games by scoring 814 runs and only allowing 645 runs by the opposition. In order to generate the necessary runs, Peter Brand boils down all the stats into one number, on base percentage. By looking at the on-base percentage of all the players in the league, Brand is able to determine the likelihood of generating runs. There are a few key phrases/quotes from this scene that need to be highlighted: “it’s about getting things down to one number” “People are overlooked for a variety of biased reasons and ‘perceived’ flaws.” “Bill James and mathematics cut straight through that [biased reasons and perceived flaws].” Getting things down to one number is the liberating element for the Oakland A’s and for banking. We have already identified the one number for banking – Net Yield on Assets. Let’s define this a bit further though. For this exercise, net yield means the gross yield (interest income plus fee income) on assets less charge offs. We are looking to see what is going to be the consistent return on the assets less what can be expected net charge off related to the assets. When Billy Beane and Peter Brand got it down to the one number “On Base Percentage” it altered the player selection process and highlighted the biases of the scouts such as: Giambi’s brother was “getting a little thick around the waist” “Old Man” Justice Justice will be “lucky if he hits his weight” in July and August Justice’s “legs are gone Hatteberg “can’t throw” Hatteberg’s “best part of his career is over” Hatteberg “walks a lot” None of the above comments used any facts or data to disprove each player’s on base percentage. Can you imagine if they were underwriters or lenders? What type of compliance issues would we have on our hands with the above comments? Biased against disabilities (Hatteberg with nerve damage); Age Discrimination (“Old Man” Justice), Physical Appearance (Giambi’s brother “getting a little thick around the waist”), these scouts would be a compliance liability let alone obstacles in any type of organizational change. But one can readily see how focusing on one number liberates the thinking and removes the old constraints or ways of thinking. One of the scouts commented that Hatteberg had a high on base percentage because he walks a lot, considering a walk as a negative while a hit is a positive but why? Why is getting on base by being walked a negative but getting on base with a hit is positive? The result is the same as the movie points out. How about in commercial lending? If we focus on net yield on the portfolio as the one number, does that do anything to remove biases? I believe that it does. One example is the perception of charge offs in a portfolio. To this day the notion of a charge off in a commercial portfolio, even in the small business portfolio, is frowned upon and can jeopardize one’s career. Similar to the walk, the charge off is not desired but if we focus on the one number, net yield, it actually removes the stigma of the charge off! If we need at minimum a 6% net asset yield and we are able to generate a gross yield of 9% with an expected loss rate of 2%, we actually exceed our “one number” of a targeted net yield of 6% with an expected net yield of 7%. With that change that removes the biases and flawed perception, can we now start to find opportunities that provide us with the ability to step away from the norm; stop competing with the rest; and generate that higher return that is required? What are the potential biases and flawed perceptions that will need to be addressed? “High Risk” Industries? “Undesired” Loan types? Consumer vs. Commercial? Real Estate Secured vs. Unsecured? Loans vs. Treasuries or other earning asset types? But just as in the movie, you need to be prepared for the response you may get from the traditional ‘seasoned’ lenders in your organization. When Billy Beane puts the new strategy into place at the Oakland A’s, the lead scout responds with: “You don’t put a team together with a computer” “Baseball isn’t just numbers, it isn’t science. If it was anybody could do what we do but they can’t.” “They don’t know what we know. They don’t have our experience and they don’t have our intuition.” Ah, just like the traditional baseball scout is the traditional commercial lender with the years of experience, judgment and intuition. I used to be one and used almost word for word the same argument against credit scoring and small business before I truly understood what it was all about. Don’t get me wrong. Experience, judgment and intuition is valuable and necessary. But that type of judgment tends to get into trouble when it stops looking outside for data and only relies on past personal experience to assess the next moves. Experience is always important but it has to continually review, assess and interpret the data. So let’s start looking at the different types of data. On deck – How do we know how many runs the opposition is going to score? The use of external data.
By: Joel Pruis I am going to take some liberties here. Nowhere in the movie Moneyball does Peter Brand tell us how he got to the magic number of winning 99 games to get to the playoffs. My assumption is that given the way that he evaluates the Oakland A’s, he also evaluations the other teams in their conference. Assessing the competitive landscape provides Brand with the estimated runs their opponents will generate. Now we could take the approach that such analysis would correlate to assessing how your competition is going to perform but I am going to take a different approach. I would compare the conference assessment in Moneyball to be similar to an economic forecast/assessment. We need to assess what are the overall conditions in which we must operate that will allow us to generate the net yield on the assets of our financial institution. Some of the things we need to assess to determine what we will be able to generate related to the net yield on assets would be: Gross yield on assets Current interest rate environment (yield on treasuries, federal home loan bank, etc. Interest rate trends (increasing, declining, trends toward fixed rates, variable rates) Industry information General trend of businesses across the nation How are businesses faring? How well are they paying their creditors? Are they relying more or less on credit? Are new businesses being started? Are they succeeding? Are they failing? General trends (same as above) within your financial institution’s market footprint One such source of the industry information is the Small Business Credit Index generated by Experian & Moody’s Analytics. In the recent release of the Small Business Credit Index, small business is indicating stronger from the prior quarter moving from 104.3 to 109. But this is from a national perspective. Depending on your financial institution, it is important to always get an overall view of the economy but more importantly, what is happening in your particular market footprint. Just as the Oakland A’s in Moneyball maintained an overall perspective of Major League Baseball, their focus for success was targeting their specific conference to reach the playoffs. So as we look at information such as the Small Business Credit Index, we are able to see highlights of regional trends (certain states west of the Mississippi are doing better while certain states along the east coast are not) and specific industry trends. From such data we need to drill down into our specific footprint and current portfolio. We need to review such items as: What industry concentrations do we have that are doing well in the economy and how is our portfolio doing compared to the external data? What industries are we not engaging that may provide a good opportunity for our financial institution? What changes are taking place in the general economy that may impact our ability to achieve our expected results? What external factors must we be monitoring that may impact our strategy (such as the impact of Obamacare and how it will impact the hiring for businesses with more than 50 employees?) Just as in Moneyball, Brand continues to monitor the performance of the overall league (and the individual players for future trades), we need to continually monitor the national, state and local economies to determine what adjustments we will need to make to achieve our strategies. So we have assessed the general environment, on to strategies or “How do we win 99 games with a total payroll of $38 million?”
By: Joel Pruis What is it we as bankers are trying to accomplish? If you have been in the industry for 20+ years, this question may sound ridiculous! We do what we do! We are bankers! What do you mean define what are we trying to do? But that is the question, what is it we are trying to do? I am going to propose we boil it down to the basic/fundamental element – Banks aggregate money from various sources and redeploy these funds to earn a return for the shareholders. Ultimately, our objective is to generate an appropriate return for the shareholders Getting back to the movie Moneyball, Billy Beane and Peter Brand define the objective of the Oakland A’s for the season in terms of projecting the number of wins that are needed to assure, with all probability, that the team makes the playoffs (this would be similar to the objective of banking to generate an appropriate return for the shareholders). But Peter Brand quickly moves into very specific targets that are required for the A’s to make it to the playoffs, namely win 99 regular season games. In order to win 99 regular season games, the A’s offense will need to score 814 runs in the season and defensively only allow 645 runs. Plain and simple. Very objective, very measurable and it is all based upon data, data, data. Let’s break this down. Based upon their conference, the teams in their conference along with the overall schedule, Peter Brand projects that 99 wins are necessary to land a spot in the playoffs. No gut check, no darts or crystal ball but rather historical data that when analyzed provides the benchmark of 99 wins to statistically assure the Oakland A’s that they will make the playoffs. So let’s apply this to banking. Our objective is to generate the appropriate return for our shareholders or the old Return on Equity. So, for example, if our targeted return on equity is 20% (making the playoffs) we need to make sure we generate enough net income (99 wins) through producing the necessary gross yield on assets (814 runs generated by the Oakland A’s offense) less the expected charge offs (645 runs allowed by the Oakland A’s defense). For a quick dive into details, our data would provide for a margin of error on the variable to provide for statistical assurance of achieving the objective (Return on Equity). In the movie there is no guaranty that the 814 runs will win the conference but at the same time there is no guaranty that the Oakland A’s opponents will score 645 runs. Never in the movie does the coach, Billy Beane or Peter Brand tell the team, “You only have to score X number of runs this game, don’t score anymore.” Or even crazier, “You are not letting the other team score enough runs, they need to score 645!” No, the strategy is still to generate as many runs as possible while minimizing the number of runs scored by the opposition. Rather it is the review of the total amount of earning assets of the financial institution and the overall credit quality that we must understand and control to determine our ability to generate the net yield on assets required to generate the return on equity that is required. If we assume too much risk in the portfolio in order to generate the required yield it would be similar to having a poor pitching staff projected to allow 10 runs a game requiring the team to produce 11 runs a game in order to win. It just is not realistic. So basically we need to assess at the high level, are we appropriately structured to allow for the generation of enough profit to provide the appropriate return on equity. At this point, we do not need to complicate it any further than that. Now let’s take a look at the constraints. We know we have them in banking, let’s take a look at probably the single biggest constraint imposed on Billy Beane and the Oakland A’s. In the movie, before Billy Beane is even aware of the Moneyball concept, his is given his constraint by the owner. Beane asks for more money to ‘buy players’ and is flat out rejected by the owner. The owner, in fact, cuts Beane off by asking, “is there anything else I can do for you?”. Net result is that the Oakland A’s have $38 million dollars for payroll vs. the New York Yankees at $120 million. Seriously it does not seem fair. How can you attract the needed talent when you cannot pay the type of salary needed to get the necessary players to win a championship? Let’s rephrases this for banking… How can a bank be expected to deploy its assets when such a high rate of return is required? Boiling it down to a specific example, “How can I originate a commercial loan at this rate of interest when the competition is ½ to 1% lower than our rates?” Up next – Why will 99 games get us to the playoffs? How do we assess the environment?
By: Joel Pruis Times are definitely different in the banking world today. Regulations, competition from other areas, specialized lenders, different lending methods resulting in the competitive landscape we have today. One area that is significantly different today, and for the better, is the availability of data. Data from our core accounting systems, data from our loan origination systems, data from the credit bureaus for consumer and for business. You name it, there is likely a data source that at least touches on the area if not provides full coverage. But what are we doing with all this data? How are we using it to improve our business model in the banking environment? Does it even factor into the equation when we are making tactical or strategic decisions affecting our business? Unfortunately, I see too often where business decisions are being made based upon anecdotal evidence and not considering the actual data. Let’s take, for example, Major League Baseball. How much statistics have been gathered on baseball? I remember as a boy keeping the stats while attending a Detroit Tigers game, writing down the line up, what happened when each player was up to bat, strikes, balls, hits, outs, etc. A lot of stats but were they the right stats? How did these stats correlate to whether the team won or lost, does the performance in one game translate into predictable performance of an entire season for a player or a team? Obviously one game does not determine an entire season but how often do we reference a single event as the basis for a strategic decision? How often do we make decisions based upon traditional methods without questioning why? Do we even reference traditional stats when making strategic decisions? Or do we make decisions based upon other factors as the scouts of the Oakland A’s were doing in the movie Moneyball? In one scene of the Movie, Billy Beane, general manager of the A’s, is asking his team of scouts to define the problem they are trying to solve. The responses are all very subjective in nature and only correlate to how to replace “talented” players that were lost due to contract negotiations, etc. Nowhere in this scene do any of the scouts provide any true stats for who they want to pursue to replace the players they just lost. Everything that the scouts are talking about relates to singular assessments of traits that have not been demonstrated to correlate to a team making the playoffs let alone win a single game. The scouts with all of their experience focus on the player’s swing, ability to throw, running speed, etc. At one point the scouts even talk about the appearance of the player’s girlfriends! But what if we changed how we looked at the sport of baseball? What if we modified the stats used to compile a team; determine how much to pay for an individual player? The movie Moneyball highlights this assessment of the conventional stats and their impact or correlation to a team actually winning games and more importantly the overall regular season. Bill James is given the credit in the movie for developing the methodology ultimately used by the Oakland A’s in the movie. This methodology is also referred to as Sabermetrics. In another scene, Peter Brand, explains how baseball is stuck in the old style of thinking. The traditional perspective is to buy ‘players’. In viewing baseball as buying players, the traditional baseball industry has created a model/profile of what is a successful or valuable player. Buy the right talent and then hopefully the team will win. Instead, Brand changes the buy from players to buying wins. Buying wins which require buying runs, in other words, buy enough average runs per game and you should outscore your opponent and win enough games to win your conference. But why does that mean we would have to change the way that we look at the individual players? Doesn’t a high batting average have some correlation to the number of runs scored? Don’t RBI’s (runs batted in) have some level of correlation to runs? I’m sure there is some correlation but as you start to look at the entire team or development of the line up for any give game, do these stats/metrics have the best correlation to lead to greater predictability of a win or more specifically the predictability of a winning season? Similarly, regardless of how we as bankers have made strategic decisions in the past, it is clear that we have to first figure out what it is exactly we are trying to solve, what we are trying to accomplish. We have the buzz words, the traditional responses, the non-specific high level descriptions that ultimately leave us with no specific direction. Ultimately it allows us to just continue the business as usual approach and hope for the best. In the next few upcoming blogs, we will continue to use the movie Moneyball as the back drop for how we need to stir things up, identify exactly what it is we are trying to solve and figure out how to best approach the solution.
By: Maria Moynihan Cybersecurity, identity management and fraud are common and prevalent challenges across both the public sector and private sector. Industries as diverse as credit card issuers, retail banking, telecom service providers and eCommerce merchants are faced with fraud threats ranging from first party fraud, commercial fraud to identity theft. If you think that the problem isn\'t as bad as it seems, the statistics speak for themselves: Fraud accounts for 19% of the $600 billion to $800 billion in waste in the U.S. healthcare system annually Medical identity theft makes up about 3% of 8.3 million overall victims of identity theft In 2011, there were 431 million adult victims of cybercrime in 24 countries In fiscal year 2012, the IRS’ specialized identity theft unit saw a 78% spike from last year in the number of ID theft cases submitted The public sector can easily apply the same best practices found in the private sector for ID verification, fraud detection and risk mitigation. Here are four sure fire ways to get ahead of the problem: Implement a risk-based authentication process in citizen enrollment and account management programs Include the right depth and breadth of data through public and private sources to best identity proof businesses or citizens Offer real-time identity verification while ensuring security and privacy of information Provide a Knowledge Based Authentication (KBA) software solution that asks applicants approved random questions based on “out-of-wallet” data What fraud protection tactics has your organization implemented? See what industry experts suggest as best practices for fraud protection and stay tuned as I share more on this topic in future posts. You can view past Public Sector blog posts here.
By: Maria Moynihan State and Federal agencies are tasked with overseeing the integration of new Health Insurance Exchanges and with that responsibility, comes the effort of managing information updates, ensuring smooth data transfer, and implementing proper security measures. The migration process for HIEs is no simple undertaking, but with these three easy steps, agencies can plan for a smooth transition: Step 1: Ensure all current contact information is accurate with the aid of a back-end cleansing tool. Back-end tools clean and enhance existing address records and can help agencies to maintain the validity of records over time. Step 2: Duplicate identification is a critical component of any successful database migration - by identifying and removing existing duplicate records, and preventing future creation of duplicates, constituents are prevented from opening multiple cases, thereby reducing the probability for fraud. Step 3: Validate contact data as it is captured. This step is extremely important, especially as information gets captured across multiple touch points and portals. Contact record validation and authentication is a best practice for any database or system gateway. Agencies and those particularly responsible for the successful launches of HIEs are expected to leverage advanced technology, data and sophisticated tools to improve efficiencies, quality of care and patient safety. Without accurate, standard and verified contact information, none of that is possible. Access the full Health Insurance Exchange Toolkit by clicking here.
Big news [last week], with Chase entering in to a 10 year expanded partnership with Visa to create a ‘differentiated experience’ for its merchants and consumers. I would warn anyone thinking “offers and deals” when they hear “differentiated experience” – because I believe we are running low on merchants who have a perennial interest in offering endless discounts to its clientele. I cringe every time someone waxes poetic about offers and deals driving mobile payment adoption – because I am yet to meet a merchant who wanted to offer a discount to everyone who shopped. There is an art and a science to discounting and merchants want to identify customers who are price sensitive and develop appropriate strategies to increase stickiness and build incremental value. It’s like everyone everywhere is throwing everything and the kitchen sink at making things stick. On one end, there is the payments worshippers, where the art of payment is the centre piece – the tap, the wave, the scan. We pore over the customer experience at the till, that if we make it easier for customers to redeem coupons, they will choose us over the swipe. But what about the majority of transactions where a coupon is not presented, where we swipe because its simply the easiest, safest and the boring thing to do. Look at the Braintree/Venmo model, where payment is but a necessary evil. Which means, the payment is pushed so far behind the curtain – that the customer spends nary a thought on her funding source of choice. Consumers are issuer agnostic to a fault – a model propounded by Square’s Wallet. Afterall, when the interaction is tokenized, when a name or an image could stand in for a piece of plastic, then what use is there for an issuer’s brand? So what are issuers doing? Those that have a processing and acquiring arm are increasingly looking at creative transaction routing strategies, in transactions where the issuer finds that it has a direct relationship with both the merchant and the consumer. This type of selective routing enables the issuer to conveniently negotiate pricing with the merchant – thereby encouraging the merchant to incent their customers to pay using the card issued by the same issuer. For this strategy to succeed, issuers need to both signup merchants directly, as well as encourage their customers to spend at these merchants using their credit and debit cards. FI’s continue to believe that they can channel customers to their chosen brands, but “transactional data doth not maketh the man” – and I continue to be underwhelmed by issuer efforts in this space. Visa ending its ban on retailer discounts for specific issuer cards this week must be viewed in context with this bit – as it fuels rumors that other issuers are looking at the private payment network option – with merchants preferring their cards over competitors explicitly. The wild wild west, indeed. This drives processors to either cut deals directly with issuers or drives them far deeper in to the merchant hands. This is where the Braintree/Venmo model can come in to play – where the merchant – aided by an innovative processor who can scale – can replicate the same model in the physical world. We have already seen what Chase Paymentech plans to do. There aren’t many that can pull off something similar. Finally, What about Affirm, the new startup by Max Levchin? I have my reservations about the viability of a Klarna type approach in the US – where there is a high level of credit card penetration among the US customers. Since Affirm will require customers to choose that as a payment option, over other funding sources – Paypal, CC and others, there has to be a compelling reason for a customer to choose Affirm. And atleast in the US, where we are card-entrenched, and everyday we make it easier for customers to use their cards (look at Braintree or Stripe) – it’s a tough value proposition for Affirm. Share your opinions below. This is a re-post from Cherian's personal blog at DropLabs.
Last January, I published an article in the Credit Union Journal covering the trend among banks to return to portfolio growth. Over the year, the desire to return to portfolio growth and maximize customer relationships continues to be a strong focus, especially in mature credit markets, such as the US and Canada. Let’s revisit this topic, and start to dive deeper into the challenges we’ve seen, explore the core fundamentals for setting customer lending limits, and share a few best practices for creating successful cross-sell lending strategies. Historically, credit unions and banks have driven portfolio growth with aggressive out-bound marketing offers designed to attract new customers and members through loan acquisitions. These offers were typically aligned to a particular product with no strategy alignment between multiple divisions within the organization. Further, when existing customers submitted a new request for credit, they were treated the same as incoming new customers with no reference to the overall value of the existing relationship. Today, however, financial institutions are looking to create more value from existing customer relationships to drive sustained portfolio growth by increasing customer retention, loyalty and wallet share. Let’s consider this idea further. By identifying the needs of existing customers and matching them to individual credit risk and affordability, effective cross-sell strategies that link the needs of the individual to risk and affordability can ensure that portfolio growth can be achieved while simultaneously increasing customer satisfaction and promoting loyalty. The need to optimize customer touch-points and provide the best possible customer experience is paramount to future performance, as measured by market share and long-term customer profitability. By also responding rapidly to changing customer credit needs, you can further build trust, increase wallet share and profitably grow your loan portfolios. In the simplest sense, the more of your products a customer uses, the less likely the customer is to leave you for the competition. With these objectives in mind, financial organizations are turning towards the practice of setting holistic, customer-level credit lending parameters. These parameters often referred to as umbrella, or customer lending, limits. The challenges Although the benefits for enhancing existing relationships are clear, there are a number of challenges that bear to mind some important questions: How do you balance the competing objectives of portfolio loan growth while managing future losses? How do you know how much your customer can afford? How do you ensure that customers have access to the products they need when they need them What is the appropriate communication method to position the offer? Few credit unions or banks have lending strategies that differentiate between new and existing customers. In the most cases, new credit requests are processed identically for both customer groups. The problem with this approach is that it fails to capture and use the power of existing customer data, which will inevitably lead to suboptimal decisions. Similarly, financial institutions frequently provide inconsistent lending messages to their clients. The following scenarios can potentially arise when institutions fail to look across all relationships to support their core lending and collections processes: Customer is refused for additional credit on the facility of their choice, whilst simultaneously offered an increase in their credit line on another. Customer is extended credit on a new facility whilst being seriously delinquent on another. Customer receives marketing solicitation for three different products from the same institution, in the same week, through three different channels. Essentials for customer lending limits and successful cross-selling By evaluating existing customers on a periodic (monthly) basis, financial institutions can holistically assess the customer’s existing exposure, risk and affordability. By setting customer level lending limits in accordance with these parameters, core lending processes can be rendered more efficient, with superior results and enhanced customer satisfaction. This approach can be extended to consider a fast-track application process for existing relationships with high value, low risk customers. Traditionally, business processes have not identified loan applications from such individuals to provide preferential treatment. The core fundamentals of the approach necessary for the setting of holistic customer lending (umbrella) limits include: The accurate evaluation of credit and default rise The calculation of additional lending capacity and affordability Appropriate product offerings for cross-sell Operational deployment Follow my blog series over the next few months as we explore the core fundamentals for setting customer lending limits, and share a few best practices for creating successful cross-sell lending strategies.
First, it aims to drastically reduce payment acceptance costs through any and all means and Secondly – keep merchant data firmly within their purview. MCX – MerChants reduX: The post that follows is a collection of thoughts around MCX, why it deserves respect, and yet how it is indeed mortal and bleeds like all others. For those who are not familiar with MCX – it’s a consortium of over 30 leading national retailers with a singular purpose – that is, to create a seamlessly integrated mobile commerce platform. The website for MCX is http://www.mcx.com. The consortium is led by merchants like Walmart, Target, CVS, BestBuy, Gap, Sears etc. By 2012, the mobile payments space was fragmented as it is, which itself may have precipitated the launch of MCX. And to a number of solutions looking for traction, things ground to a halt when MCX conceptualized to the merchants a solution that needed no costly upgrades and a promise to route the transaction over low cost routing options. My friends on the issuer side privately confide that MCX has infact succeeded in throwing a monkey wrench in their mobile payment plans – and merchant acceptance looks to be ambiguous around incumbent initiatives such as Isis and GoogleWallet, as well as for alternative payment initiatives. It had been easy to call it mere posturing and ignore it in the early days, but of late there is a lot of hand wringing behind the scenes and too many furrowed brows, as if the realization finally struck that merchants were indeed once again crucial to mobile payment adoption. MCX – It’s raison d’etre Meanwhile, the stakeholders behind MCX have been religious in their affirmation that MCX lives by two core tenets: First, it aims to drastically reduce payment acceptance costs through any and all means and Secondly – keep merchant data firmly within their purview. I can’t seem to think that the latter was any more than an after thought, because merchants individually can choose to decide if they wish to share customer preferences or Level III data with third parties, but they need all the collective clout they can muster to push networks and issuers to agree to reduce card acceptance costs. So if one distils MCX down to its raison d’etre, then it looks that it is aimed squarely at No.1. Which is fair when you consider that the merchants believe card fees are one of their biggest operating expenses. In 2007, 146,000 convenience stores and gas stations nationwide made a total of $3.4B in profits, yet they paid out $7.6B in card acceptance costs(Link). And MCX is smart to talk about the value of merchant data, the need to control it, yada yada yada. But if that were indeed more important, Isis could have been the partner of choice – someone who would treat customer and transaction data as sacrosanct and leave it behind for the merchants to fiddle with(vs. GoogleWallet’s mine..mine..mine.. strategy). But the same way HomeDepot was disappointed when they first saw GoogleWallet – no interchange relief, incremental benefits at the point-of-sale, and swoops all their data in return, Isis also offers little relief to MCX or its merchants, even without requiring any transaction or SKU level data in return. Does it mean that Carriers have no meaningful role to play in commerce? Au contraire. They do. But its around fraud and authentication. Its around Identity. And creating a platform for merchants to deliver coupons, alerts to opted-in customers. But they seem to be stuck imitating Google in figuring out a play at the front end of the purchase funnel, to become a consumer brand. The last thing they want to do is leave it to Apple to figure out the “Identity management” question, which the latter seems best equipped to answer by way of scale, the control it exerts in the ecosystem, its vertical integration strategy that allows it to fold in biometrics meaningfully in to its lineup, and to start with its own services to offer customer value. Did we say Apple? Its a bit early to play fast and loose with Apple predictions, but its Authentec acquisition should rear its head sometime in the near future (2013 – considering Apple’s manufacturing lead times), that a biometric solution packaged neatly with an NFC chip and secure element could address three factors that has held back customer adoption of biometrics: Ubiquity of readers, Issues around secure local storage and retrieval of biometric data, Standardization in accessing and communicating said data. An on-chip secure solution to store biometric data – in the phone’s secure element can address qualms around a central database of biometric data open to all sorts of malicious attacks. Standard methods to store and retrieve credentials stored in the SE will apply here as well. Why NFC? If NFC was originally meant to seamlessly and securely share content, what better way to sign that content, to have it be attributable to its original author, or to enforce one’s rights to said content – than to sign it with one’s digital signature. Identity is key, not just when enforcing digital rights management on shared content, but also to secure commerce and address payment/fraud risk. Back to MCX. The more I read the more it seems MCX is trying to imitate Isis in competing for the customer mindshare, in attempting to become a consumer brand – than simply trying to be a cheaper platform for payment transactions. As commerce evolved beyond being able to be cleanly classified under “Card Present” and “Card Not Present” – as transactions originate online but get fulfilled in stores, merchants expect rules to evolve alongside reality. For example, when customers are able to order online, but pick up in-store after showing a picture ID, why would merchants have to pay “Card not Present” rates when risk is what we attribute higher CNP rates to, and why is there an expectation of the same amount of risk even in this changed scenario? And beyond, as technology innovation blurs the lines that neatly categorized commerce, where we replace “Card Present” with “Mobile Present”, and mobile carry a significant amount of additional context that could be scored to address or quantify risk, why shouldn’t it be?. It’s a given that networks will have to accommodate for reduced risk in transactions where mobile plays a role, where the merchant or the platform enabling the transaction can meaningfully use that context to validate customer presence at the point-of-sale – and that they will expect appropriate interchange reduction in those scenarios. MCX – A brand like Isis or a platform? But when reading portions of the linked NRF blog, and elsewhere – it reflects a misplaced desire on MCX’s part to become a consumer facing solution – an app that all MCX partners will embrace for payment. This is so much like the Isis solution of today – that I have written about – and why it flies in the face of reason. Isis – the nexus between Carriers and FI’s – is a powerful notion, if one considers the role it could play in enabling an open platform – around provisioning, authentication and marketing. But for that future to materialize, Isis has to stop competing with Google, and must accept that it has little role to play by itself at the front end of the funnel, and must recede to its role of an enabler – one that puts its partner FI brands front and center, allows Chase’s customers to pay using Chase’s mobile app instead of Isis, and drives down the fraud risk at the point of sale by meaningfully authenticating the customer via his location and mobile assets Carriers control, and further – the historical data they have on the customer. It’s those three points of data and the scale Isis can bring, that puts them credibly in the payments value chain – not the evaporating control around the Secure Element. In the same vein, the value MCX brings to merchants – is the collective negotiating power of over 30 national merchants. But is it a new consumer brand, or is it a platform focused on routing the transaction over the least cost routing option. If its the latter, then it has a strong parallel in Paypal. And as we may see Paypal pop-up as legal tender in many a retailer’s mobile apps and checkout aisles going forward, MCX is likely to succeed by emulating that retailer aligned strategy than follow a brand of its own. Further, If MCX wants customers to pay using less costly means – whether they be private label, prepaid or ACH – then it and its partners must do everything they can to shift the customer focus away from preferred payment methods and focus on the customer experience and resulting value around loyalty. MCX must build its value proposition elsewhere, and make their preferred payment methods the bridge to get the customer there. Another example where the retailer focused too much on the payment, and less so on the customer experience is the Safeway Fast Forward program. The value proposition is clear for the customer – Pay using your Safeway Fast Forward card number and a self assigned PIN for simpler checkout. However to set up your account, the customer must provide a State issued ID (Drivers License) and on top of it – his Social Security Number(Safeway Fast Forward Requirements Here). What customer would, for the incremental convenience of paying via his Fast Forward Card and PIN, be willing to entrust Safeway with his Social Security Number? Clearly Safeway’s Risk team had a say in this and instead of coming up with better ways to answer questions around Risk and Fraud, they introduced a non-starter, which killed any opportunity for meaningful adoption. MCX & adoption So where does that leave MCX? Why will I use it? How will it address questions around adoption? It’s a given that it will have to answer the same questions around fraud and authentication during customer on-boarding or at a transactional level. Further, its not enough these days to simply answer questions pertaining to the customer. Further, one must address questions relating to the integrity and reputation of the device the customer use – whether that be a mobile device or a Laptop PC. But beyond fraud and auth, there are difficult questions around what would compel a techno-luddite who has historically paid using a credit instrument to opt for an ACH driven(i am guessing) MCX payment scheme. Well, for one: MCX and its retail partners can control the purchasing power parity of MCX credits. If they so wish, and after aggregating customer profiles across retailers, MCX determines that the Addams family spends a collective $400 on average per month between all the MCX retailers. MCX could propose that if instead, the Addams family were to commit to buy $450 in MCX credits each month, they could increase their purchasing power an additional $45 credits that could be used on specific retail categories (or flat out across all merchandise)? Would Morticia be interested? If she did, what does that mean to MCX? It eliminated having to pay interchange on approx $500, and further it enabled its partners to capture an incremental spend of 10% that did not exist before. Only merchants will be able to pull this off – by leveraging past trends, close relationships with CPG manufacturers and giving Morticia new reasons to spend in the manner they want her to. But then again, where does MCX stop in providing a level playing field for its partners, and step back – so that merchants can start to compete for their customers and their spend? And finally, can it survive the natural conflicts that will arise, and limit its scope to areas that all can agree – for long enough for it to take root? Should MCX become the next Isis or the next Paypal? Which makes most sense? What do you think? Please leave your opinions below... (This blog post is an adaptation of its original post found - http://www.droplabs.co/?p=662)
By: Maria Moynihan Fact: In fiscal year 2011, the federal government allocated ~$608M to investigate and prosecute cases of alleged fraud in health care programs Fact: Medicare and Medicaid related scams cost taxpayers more than $60B a year These statistics are profound, especially when so many truly need–and rightfully deserve–access to health benefits. To make the facts a bit more tangible, how would you feel if you heard that neighbors of yours were submitting claims to Medicare for treatments that were never provided? In essence, you’ve got thieves for neighbors, don’t you? Thankfully, government agencies are responding. Even while being challenged with reduced budgets and limited resources; they are investing in efficient processes, advanced data, analytics and decisioning tools to improve their visibility into individuals at the point of application. By simply making adjustments to one or all of these areas, agencies can pinpoint whether or not individuals are who they say they are. Only with precision, relevancy, and efficiency of information, can fraud and abuse be curtailed. Below are a few examples of how to improve your eligibility systems or processes today. Or, simply download the Issue Brief, Beyond Traditional Eligibility Verification, for more detail. Use scores, models, and screening questions to assess a beneficiary’s true identity or level of identity fraud risk. Use income and asset estimation models to compare to stated income as a validation step in determination of benefits eligibility. Create a single system for automatic identification and verification of beneficiaries and businesses applying for service. Tighten controls around business identity to weed out fraud rings, syndicates and other forms of business fraud. The Bottom Line: Only with process, information, or system improvements, can government agencies move the needle on the growing and pressing issue of fraud and abuse.
Research shows that investing in superior customer management easily can exceed returns of 20 percent in the first year of implementation. A return that compounds in subsequent years as a results of customer-centric strategies that drive customer's loyalty, new customer referrals, and increased revenue opportunities. Customer loyalty is a key driver that differentiates retail banks when trying to retain existing and attract new customers. And cited by customers themselves as the way to win their business today. Achieving superior customer management, however, can be expensive and operationally prohibitive; and let's not to forget to mention there are a number of different approaches that aim to meet such a standard, but fail because critical qualitative insights are not captured in back-end systems of record (SOR). These "black-box" strategies struggle to be widely adopted across the enterprise and die a slow, internal political death - with wasted resources left on the floor. It also leaves the customer feeling frustrated and dissatisfied, maybe even ready to flee. One such example was recently illustrated in an article in Credit Union Times. Changing the retail bank's approach to adopt best practices in developing holistic customer-centric strategies is paramount to the improvement of the customer experiences, and the bottom line. Quantitative data alone can represent only a partial view of reality whereas holistic customer strategies exploit the full value of the enterprise by synthesizing customer knowledge from SOR with external off-your firm financial information and critical qualitative input from customer-facing staff. Customer-facing staff are critical in the adoption of such strategies and need to be actively engaged to extract customer learnings that will lead to the modification and alignment of customer-level treatement strategy designs and predictive models with the real world. A collaborative approach, blending art and science, ensures complete adoption across the enterprise and measurable customer experience improvements that can be monetized for shareholders through improved customer retention and new customer acquisitions. Get access to details on the framework to design and deploy such customer-centric strategies.
By: Maria Moynihan The public sector is not unlike the private sector when it comes to data. Both require accuracy and relevancy for optimized processes and decision-making. For government agencies, maintaining a holistic view of constituents is more important than ever. By linking data across department systems, governments improve operations, citizen profiling and overall record management. No longer do agencies have to muddle through records of Maria Moynihan, Mari Moynihan, M Moynihan, and other variations of name or contact information when they all are truly one in the same. Unfortunately, without the right tools and know how, database maintenance, record deduplication, and account validation can be a daunting process. Below are five critical steps to helping government agencies execute successful linkage of database records: Step 1: Engage stakeholders Data stewards are not mind readers. They work with finite data and rely on stakeholders to provide insight. Seek input from users across departments and functions. Step 2: Identify impacts and priorities Data errors and disparate data prevent stewards from amalgamating records and defining a master database. Focus on areas of strategic priority. Step 3: Create success criteria Look for and set quantifiable metrics for matching. Consider what data needs to be linked and what thresholds are acceptable given objectives. Step 4: Define new standards Create established workflows and guidelines for evaluating, merging and purging records. Step 5: Leverage matching technology Integrate robust deduplication tools to design multiple workflows and handle a variety of matching challenges. In short, without data stewards seeking input from commercial stakeholders, an understanding of the data impacts, and establishing a clear process including defined methodologies and technology for deduplication, government agencies will remain challenged in trying to figure out if Maria, Mari, and M are the same person in databases. Click here to see the full guide to Creating a Single View.
By: Joel Pruis The commercial lending - traditional C&I, CRE and other - segment is one of the last areas to be “automated” or captured within an automated lending platform. Many of us talk about the need to automate this segment but the discussion needs to start with the question of “What does it mean to automate originations in the commercial segment? Let’s start to break this down and define it. Previously, we have covered how to define small business for your respective financial institution. If you use that as a measurement of what is small business, the remaining segment would by default be your commercial segment. It seems obvious but good to re-iterate to keep the context on commercial. What we are not planning to cover is the small business segment where there is relatively high application volume and low total dollar production. If we compare small business and commercial across two major characteristics, we the distinction becomes more clear. The above chart represents the typical situation – the probable not the possible scenario. For example, there are situations where the sales lead time is days not months for a commercial lending opportunity or a small business application can sometimes take over a year to get the application. I like analogies so let’s compare mass produced furniture vs. custom furniture to small business vs. commercial. Mass produced furniture is high volume but low dollar per unit (small business) while the custom furniture is the low volume but high dollar per unit production (commercial). Basically, the furniture being mass produced has a low need for any customization with high demand and a low cost of production on a per unit basis. Conversely, the custom furniture production has relatively low volume but a higher cost of production on a per unit basis. The custom furniture maker has no set designs, no set product line but rather examples of past work that has been done. There are no set materials that are to be used and no set prescribed method for manufacturing any particular item. While one customer may want a dining room table that has leaves to expand the seating as needed, another may want a drop-leaf table or simply a static table top. It is up to the customer to decide what the criteria is to best suit the need. The talented furniture maker will provide his/her expertise to provide the best product/solution for the customer but the end result is ultimately up to the customer. Such a design will be worked and potentially reworked multiple times before the right design in actually approved by the customer. Once the design is approved, the work begins on creating the piece of furniture. The creation may follow a standard set of procedures or may not. The key is that there is no set way that must be followed in the creation. The furniture maker will not wait until all material is available but rather can start on portions of the furniture (turning the legs, rough cutting the wood for the table top). While there is likely an agreed upon delivery date, the success is dependent upon completing the furniture by that date, not following a set prescribed path to completion. It is possible to design and capture the small business origination process with its defined roles and responsibilities in a detailed process map. The small business origination process can measure and monitor service level agreements and set expectations with the client around the entire process before the application is even taken. Prescribed order and dependency around the activity and/or task-level process mapping can be accomplished in the small business origination process with a high degree of accuracy and consistency from one application to the next. The commercial loan origination process, however, cannot be captured with a high degree of accuracy and/or consistency. Individual efforts can certainly be captured and specific service level agreements can be established. For example, the spreading of financial statements can follow a prescribed methodology and service level agreements can be established. However, attempts to establish service level agreements that when combined could adequately set expectations of total turnaround times, estimated completion times and prescribed methodologies would result in much lower compliance with such prescribed processes rendering it meaningless. Joel Pruis is a senior business consultant with Experian\'s Global Consulting Practice. To learn more about strategy consulting and access more thought-leadership from our team, please visit www.experian.com/consultingservices.
Contributed by: David Daukus As the economy recovers from the recession, consumers are becoming more responsible with their credit card usage; credit card debts have not increased and delinquency rates have declined. Delinquency rates as a percentage of balances continue to decline with the short term 30-59 DPD period, now at 0.9%. With mixed results, where is the profit opportunity? Further studies from Experian-Oliver Wyman state that the average bankcard balance per consumer remained relatively flat at $4,170, but the highest credit tiers (using VantageScore A and B segments) saw average balances increase to $2,422 and $3,208, respectively. It\'s time to focus on what you have—your current portfolio—and specifically how to: Increase credit card usage in the prime segments Assign the right lines to your cardholders Understand who has the ‘right’ spend Risk score alone doesn\'t provide the most accurate insight into consumer accounts. You need to dig deeper into individual accounts to uncover behavioral trends to get the critical information needed to grow your portfolio: Leading financial institutions are looking at consumer payment history, such as balance and utilization changes. These capture a consumer’s credit situation more accurately than a point in time view. When basic principles are applied to credit data, different consumer behaviors become evident and can be integrated into client strategies. For example, if two consumers have the same VantageScore credit score, credit card balances, and payment status, does that mean they have the same current credit status? Not necessarily so. By looking at their payment history, you can determine which direction each is heading. Are they increasing their debt or are they paying down their debt? These differences reveal their riskiness and credit needs. Therefore, with payment history added to the mix, you can more accurately allocate credit lines between consumers and simultaneously reduce risk exposure. Spend is another important metric to evaluate to help grow your portfolio. How do you know if a consumer uses primary a credit card when making purchases? Wouldn’t you want to know the right amount of credit to provide based on the consumer’s need? Insight into consumer spending levels provides a unique understanding of a consumer’s credit needs. Knowing spend allows lenders to provide necessary high lines to the limited population of very high spenders, while reducing overall exposure by providing lower lines to low spenders. Spend data also reveals wallet share—knowing the total spend of your cardholder allows you to calculate their external spend. With wallet share data, you can capture more spend by adjusting credit lines or rewards that will entice consumers to spend more using your card. Once you have a more complete picture of a consumer, adjusting lines of credit and making the right offer is much easier. Take some of the risk out of managing your existing customers and finding new ones. What behavioral data have you found most beneficial in making lending decisions? Source: Experian-Oliver Wyman Market Intelligence Reports
I'm here in Vegas at the Mobile2020 conference and I am fascinated by my room key. This is not the usual “insert in to the slot, wait for it turn green or hear it chime” key cards, these are “tap and hold to a door scanner till the door opens” RFID key card. It is befitting the event I am about to attend – Money2020 – the largest of its kind bringing together over 2000 mobile money aficionados, strategists and technologists from world over for a couple of days to talk about how payment modalities are shifting and the impact of these shifts to existing and emerging players. Away from all the excitement of product launches, I hope some will be talking about one of the major barriers for consumer adoption towards alternate payment modalities such as mobile – security and fraud. I was in Costa Mesa last week and in the process of buying something for my wife with my credit card, triggered the card fraud alert. My card was declined and I had to use a different card to complete my transaction. As I was walking out, my smartphone registers a text alert from the card issuer – asking me to confirm that it was actually I who attempted the transaction. And If so, Respond by texting 1 – if Yes Or 2 – if No. All good and proper up till this point. If someone had stolen my card or my identity, this would have been enough to stop fraud from re-occurring. In this scenario the payment instrument and the communication device were separate – my plastic credit card and my Verizon smartphone. In the next couple of years, these two will converge, as my payment instrument and my smartphone will become one. At that point, will the card issuer continue to send me text alerts asking for confirmation? If instead of my wallet, my phone was stolen – what good will a text alert to that phone be of any use to prevent the re-occurrence of fraud? Further if one card was shut down, the thief could move to other cards with in the wallet – if, just as today, there are no frameworks for fraud warnings to permeate across other cards with in the wallet. Further, fraud liability is about to shift to the merchant with the 2013 EMV Mandate. In the recent years, there has been significant innovation in payments – to the extent that we have a number of OTT (Over the Top) players, unencumbered by regulation, who has been able to sidestep existing players – issuers and card networks, in positioning mobile as the next stage in the evolution of payments. Google, PayPal, Square, Isis (a Carrier consortium formed by Verizon, T-Mobile and AT&T), and a number of others have competing solutions vying for customer mind share in this emerging space. But when it comes to security, they all revert to a 4 digit PIN – what I call as the proverbial fig leaf in security. Here we have a device that offers a real-time context – whether it be temporal, social or geo-spatial – all inherently valuable in determining customer intent and fraud, and yet we feel its adequate to stay with the PIN, a relic as old as the payment rails these newer solutions are attempting to displace. Imagine what could have been – in the previous scenario where instead of reaching for my card, I reach for my mobile wallet. Upon launching it, the wallet, leveraging the device context, determines that it is thousands of miles away from the customer’s home and should score the fraud risk and appropriately ask the customer to answer one or more “out-of-wallet” questions that must be correctly answered. If the customer fails, or prefers not to, the wallet can suggest alternate ways to authenticate – including IVR. Based on the likelihood of fraud, the challenge/response scenario could include questions about open trade lines or simply the color of her car. Will the customer appreciate this level of pro-activeness on the issuer’s part to verify the legality of the transaction? Absolutely. Merchants, who so far has been on the sidelines of the mobile payment euphoria, but for whom fraud is a real issue affecting their bottom-line, will also see the value. The race to mobile payments has been all about quickly shifting spend from plastic to mobile, and incenting that by enabling smartphones to store and deliver loyalty cards and coupons. The focus need to shift, or to include, how smartphones can be leveraged to address and reduce fraud at the point-of-sale – by bringing together context of the device and a real-time channel for multi-factor authentication. It’s relevant to talk about Google Wallet (in its revised form) and Fraud in this context. Issuers have been up in arms privately and publicly, in how Google displaces the issuer from the transaction by inserting itself in the middle and settles with the merchant prior to firing off an authorization request to the issuer on the merchant’s behalf. Issuers are worried that this could wreak havoc with their inbuilt fraud measures as the authorization request will be masked by Google and could potentially result in issuer failing to catch fraudulent transactions. Google has been assuaging issuer’s fears on this front, but has yet to offer something substantial – as it clearly does not intent to revert to where it was prior – having no visibility in to the payment transaction (read my post here). This is clearly shaping up to be an interesting showdown – would issuers start declining transactions where Google is the merchant of record? And how much more risk is Google willing to take, to become the entity in the middle? This content is a re-post from Cherian's personal blog: http://www.droplabs.co/?p=625
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