Data Driven Ad Attribution Models
Marketing today relies on a variety of metrics to gain insight into its efficacy. Given the variety of online and offline channels available to marketers, understanding the impact and interaction of individual channels has become an onerous task, to say the least. Marketers rely heavily on two methods to obtain data-driven insights into the marketing process, Media Mix Modeling (MMM) and Data-Driven Attribution. MMM provides a “top -down” view into the marketing process in order to generate high-level insights into the efficacy of different marketing channels. For example, by looking at data over months or years, MMM can give marketers insight into consumers’ interaction with different marketing media. Attribution models, on the other hand, take a more “bottom-up” approach to the marketing process. These models look at an individual user’s interaction with different media. Since each user is exposed to a combination of marketing channels, the problem lies in ascertaining how much credit to give each marketing channel towards influencing a user’s choice about making a purchasing decision. Historically, marketers have used common attribution models such as last touch (first touch) attribution. Last touch attribution models assign all credit to the last channel (first channel) a user has been exposed to prior to conversion. The flaw in the last touch (first touch) attribution lies in the fact that channels further from (closer to) the conversion funnel are systematically undervalued. To allocate credit more fairly, algorithm-based methodologies have received significant traction in the past decade. In a series of three blogs will introduce three papers that discuss algorithm-based models for media mix modeling and attribution modeling. The dominance analysis approach for comparing predictors in multiple regression (Budescu, 1993) Regression models have become a common way to explore the interaction between revenue and advertising efforts. Budescu introduces a general framework known as dominance analysis that aims to decompose the coefficient of determination (R2). For the sake of simplicity, we will only deal with linear models in this post. Budescu’s work can be extended to any area of research that tries to deal with variable importance. Review of Legacy Methods Various methods have been developed over time to measure the importance of variables. These methods mostly rely on using the coefficients of independent variables from standard linear models to explain variable importance. Let’s look at a standard linear model defined as the following: y=β1 x1+⋯+βi xi+⋯+βp xp+ϵ Let’s denote the coefficient of determination of this model as R2y,X. The vector β= (β1, β2,…..βx) represents the change in the dependent variable y, associated with a unit change in each independent variable, given the other independent variables are left unchanged. Under these constraints, it is reasonable to conclude that the squared coefficients perfectly partition the coefficient of determination, as described in the equation below: R2y,x = ∑pj=1 p2y,xj = ∑pj=1 β2j While this method of using variable coefficients as importance measures is intuitive and appropriate in the case of no intercorrelations between dependent variables, in most real-world applications, dependent variables (advertising channels in this case) have some level of correlation, making this method inappropriate. Dominance Analysis Dominance Analysis compares coefficients of determination of all nested submodels composed of subsets of independent variables with that of the full model. Too much jargon? Let’s take a look at an example. Let’s say we have a total of ‘p’ independent variables in our linear model. We will build 2p-1 models, since these are the total number of subset models that can be created. We will then compute the incremental R2 contribution of each independent variable to the subset model of all other independent variables. Let’s take a scenario where we have 4 independent variables X1 , X2 , X3 and X4. We will build 24-1 models ie. 15 models. These will be 4 models with only one independent variable, 6 models with 2 independent variables each, 4 models with 3 independent variables each, and finally 1 model with all the independent variables. Thus, the incremental R2 contribution for variable X1 for example, is the increase in R2 value when X1 is added to each subset of the remaining independent variables (i.e., the null subset { . } , { X2 } , { X3 } , { X4 } , { X2 , X3 } , { X2 , X4 } , { X3 , X4 } and { X2 , X3 , X4 } ). Similarly, the incremental R2 contribution for variable X2 is the increase in value when is added to each subset of the remaining independent variables (i.e., the null subset { . } , { X1 } , { X3 } , { X4 } , { X1 , X3 } , { X1 , X4 } , { X3 , X4 } and { X1 , X3 , X4 } ). The beauty behind dominance analysis lies in the fact that the sum of the overall average incremental R2 of all independent variables is equal to the R2 of the model with all independent variables (the complete model). This allows easy partitioning of the total coefficient of determination amongst independent variables. An inherent problem with dominance analysis is the lack of computational efficiency. The need to train 2p – 1 models means that the number of models that would have to be trained increases exponentially as the number of independent variables increases. Relative Weights Analysis Another paper, which can be found here, builds on the concept of relative weights analysis as an alternative to dominance analysis. However, relative weights analysis is a fundamentally flawed method of determining attribution and has been debunked, most famously in this paper. The reason I even bring this up, is to forewarn a reader that the theoretical underpinnings of relative weights analysis is dubious, and to recommend dominance analysis as the superior R2 decomposition method.
Increased Data Privacy for Advertisers and Publishers
Where do we go from here? Privacy complaints made in November 2020 from Europe over the use of IDFA tracking code on iPhones, have pushed the industry to take privacy more seriously. In response, Apple said it would enable privacy control for its iOS users, by allowing them to opt-in to ad tracking. In 2021, consumers are more aware than ever about sharing their data. As regulators continue to step up privacy requirements, many businesses are exploring ways to use data to their advantage without violating industry regulations. In a webinar sponsored by Tavant, Strategies to Enable Advertising, Targeting and Measurement in a Privacy-Regulated World,experts from DISH Media, Integer Group (an Omnicom Group company), Sequent Partners, and Tavant got together to discuss the impact of these regulations on the media, publishing, and advertising industry. Here’s what the Panelists had to say: THE ADVENT OF PRIVACY REGULATIONS Privacy standards (GDPR, CCPA) are separating those that own data and those that do not. Third-party cookies and ad IDs are going away, but multinational companies in Europe (who worked with GDPR) are ready for it. Advertisers will need to offer opt-ins. Publishers need to educate users to outline the opt-in message with information on what data is being collected and how it’s beneficial. The consensus is that we will get smarter about ways to protect data, be compliant, and protect user privacy. Yet, the current state of data quality is messy. Data used for targeting or attribution may have come with different levels of quality, which can introduce bias in the data processing and impact the efficacy in targeting or attribution. Will the increased privacy force the advertisers to put more emphasis on media mix and innovation? WHAT WILL BE THE IMPACT OF STRINGENT PRIVACY REGULATIONS? Targeted advertising may be dampened a bit due to ID loss. Consumers may begin to experience slightly more irrelevant ad content than earlier. Companies that license their data from third parties may be in a tough position as they don’t have a direct relationship with their customers. Advertisers across the globe are still struggling to measure the reach and frequency of their campaigns, particularly across platforms. Will these privacy changes put more pressure on measurement tactics? Who will gain from these changes in data privacy? WINNERS AND LOSERS Many believe that consumers, media companies, and advertisers will all be impacted negatively. Companies that have first-party consumer data will come out the least impacted. Additionally, companies like Verizon and ATT, which have a huge reservoir of valuable first-party data, will be able to leverage it in different ways. The experts noted that everything now done on our smart TVs results in rich digital data for advertisers and publishers. As we begin to see a lot more contextual advertising, there is likely to be more investment by publishers in NLP and video image processing. What other innovations can be expected thanks to increased privacy regulations? FUTURE EXPECTATIONS New players may come into the market with the workaround innovation to capture ID but maintain privacy. Consumers may be offered incentives to opt-in. Loss of IDs will not impact work in deep learning models for attribution and mixed media modeling. Ad companies may hire specialists whose job will be to develop ID graphs which their brands can use. Ultimately, the feeling is positive as change that creates contention often triggers market forces to innovate. As data privacy begins to fall into place, the new issue is data security and effective measurement.
Changing Pace of Business With Digital Assurance
Delivering Customer Delight with Digital Assurance Digital assurance – A Key Enabler for Digital Transformation Success Digital assurance is a significant step forward in quality engineering practice. Its adoption is growing by leaps and bounds and is set to achieve a CAGR of 12.9% by 2026. The end goal of digital assurance is to deliver customer delight and peak performance. DevOps, AI, and automation make digital assurance even more effective. Let us take the example of Guild Mortgage, a leading mortgage lender and advisor in the United States specializing in residential home loans. The company had over 3000 employees. Loan officers and real estate agents delivering in a distributed ecosystem. LOS and POS systems were scattered, making collaboration difficult. Guild Mortgage had to maintain a consistent relationship with community banks and credit unions. Unfulfilled customer needs and underserved segments were an increasing worry that needed immediate attention. The company adopted digital assurance to ensure end customer delight. It was a path to foster better collaboration between loan officers, real estate agents, as well as customers. With digital assurance, Guild Mortgage achieved significant business benefits. They built a mobile application to streamline the collaboration between various moving parts of the lending ecosystem. As part of the digital assurance framework, they tested the app on various devices and operating systems, ensuring platform-agnostic peak performance. Seamless Collaboration and Uninterrupted Customer Experience with Digital Assurance Today, Guild Mortgage real estate agents are collaborating better with loan agents. The organization can customize loan collaterals as per customer needs, thanks to the ability to partner with customers at every step of the journey via the mobile app. Loan agents, too, have a seamless experience with the integration of proprietary and commercial systems. There is zero disruption or downtime at various touchpoints. Customers can access the platform on mobile devices from anywhere without disruptions. This is made possible by leveraging mobile cloud technologies and extensive usability testing. With digital assurance, this seamless collaboration and operation can become a reality for any organization. Bringing Speed in Value Delivery with DevOps and Testing A holistic approach and the right framework accelerate value delivery with digital assurance. Today, the metrics for successful digital assurance are DevOps, automation, and testing. Data security, product performance, and customer experience are all tied together. Various parameters are tested for functionality, performance, and security. Testing of applications, APIs, analytics, big data, and DR takes centerstage in digital assurance. The result? Accelerated value delivery and peak performance. Digital Quality Assured with Tavant’s Four Pillar Strategy Tavant’s digital assurance team is on a quest to innovate for quality. Tavant follows a four-pillar strategy to deliver the highest level of digital assurance for its customers. The strategy is designed with customer focus at its core to deliver end-to-end benefits of digital transformation. Customer experience testing, omnichannel testing, performance, and security testing contribute to customer satisfaction. The second pillar is testing various aspects of business processes. It includes the functionality of platforms, big data, analytics, and cloud components. The third and fourth pillars combine innovation and delivery. Test automation and DevOps build agility and innovation in businesses. Application delivery management, release management, and enterprise application management accelerate value delivery. This holistic approach supports customers’ digital journey by optimizing digital practices. What Next in Digital Assurance? Digital transformation is no longer a choice for businesses that want to deliver a great customer experience. It is a requisite, further enabled by quality assurance practices. Digital assurance is paving the way for enterprises to deliver delightful customer experiences in a device-agnostic, omnichannel world. With digital assurance, businesses are engaging their customers and speeding up product deliveries across devices and platforms. However, digital assurance is not a one-time activity. Digital assurance is a continuous practice aligned to larger business goals. The future of digital assurance is smart and automated testing, and the practice is evolving at a rapid pace as new technologies enter the ecosystem. One thing is certain. As the business landscape moves towards omnichannel, device- and platform-agnostic 4IR models, only a relentless focus on digital assurance can help organizations realize the true benefits of digital transformations. Organizations can now maintain and sustain the pace of change in today’s digital-enabled business world. Watch the webinar to gain insights. Want to learn more about Digital Assurance? Reach out to us at [email protected] or visit us here to understand how we can help your business navigate next. FAQs – Tavant Solutions How does Tavant provide digital assurance for rapidly changing business environments?Tavant offers comprehensive digital assurance through automated testing, continuous monitoring, performance analytics, and quality engineering services. Their platforms provide real-time system health monitoring, predictive maintenance capabilities, and agile testing frameworks that ensure digital systems perform reliably despite rapid business changes. What digital assurance capabilities does Tavant offer for financial services?Tavant provides automated testing suites, security assessment tools, performance monitoring systems, compliance validation platforms, and continuous integration frameworks. Their digital assurance services ensure financial systems maintain reliability, security, and compliance while enabling rapid innovation and deployment cycles. What is digital assurance in business?Digital assurance in business encompasses testing, monitoring, and validation processes that ensure digital systems, applications, and platforms perform reliably, securely, and efficiently. It includes quality engineering, performance testing, security validation, and continuous monitoring of digital assets. Why is digital assurance critical for modern businesses?Digital assurance is critical because businesses rely heavily on digital systems for operations, customer service, and competitive advantage. It prevents costly system failures, ensures customer satisfaction, maintains compliance, protects against security threats, and enables confident digital transformation initiatives. How does digital assurance support business agility?Digital assurance supports business agility by enabling rapid, confident deployment of new features, ensuring system reliability during scaling, providing quick feedback on system performance, and maintaining quality standards while accelerating development cycles and innovation initiatives.
Closing the Lending Gap with AI and ML- Adjusting to the Neo-Normal
Prior to the Covid-19 pandemic, the financial industry was already evolving at a rapid pace, mainly driven by evolving customer expectations, advancement in technology, and heightened competition from incumbents and new entrants. However, in just a few months, the crisis brought about years of change in the way companies in various sectors perform business. According to a recent McKinsey Global Survey of executives, most companies have accelerated their supply-chain digitation by 3-4 years. The cumbersome and time-consuming Loan origination process Many lenders still use manual and paper-based procedures, which is often a time-consuming process, making it extremely difficult for lending companies to meet their customers’ demands for ever-shorter response times. According to November 2020 Ellie Mae Origination Insight Report Data, the time to close loans has increased to 55 days, up from 54 days in October, which is the biggest concern for companies to satisfy consumers’ evolving demand of expecting much quicker turnaround times in the digital era. Fragmented lending Supply-chain: An age-old need for Digitization Furthermore, financial institutions have many potentials to increase their efficiency and streamline complex processes by digitizing the lending supply chain. Embedding Artificial Intelligence in the ecosystem can subsequently help companies to enhance their overall supply chain performance. It can also help lenders with possible implications across various scenarios regarding time, cost, and ROI. Tackling fragmentation with Digitization Digitization resolves issues arising from fragmentation of delivery as well as sluggishness caused due to legacy loan origination. Moreover, COVID-19 has forced “a change of mindset” from the historically slow pace in digitizing supply-chain activities. Lenders are forced to develop truly end-to-end digital capabilities, from onboarding and application through approval and execution to improve servicing, capacity, and ability to automate underwriting and risk management. AI can be used in various ways in the credit process to make it more agile and efficient. Right from legitimizing a new customer who applies for credit to choosing a suitable credit product or optimizing the credit check, the credit sector’s scope of intelligent data analytics is wide. Not only that, by leveraging AI and ML applications, lending companies can tap into customer experience at the right time with the right offer and can deliver a delightful customer experience. The Road to Business Value – Digital Lending It takes advanced next-gen technology to successfully process mountains of applications to ensure same-day approvals come to fruition. Automation and AI can reduce the time and cost of closing a mortgage and can effectively speed up the time-consuming tasks of gathering, reviewing, and verifying mortgage documents. As a result, AI-backed automation can cut out the mundanity of manual tasks but augment processing with Machine learning can further reduce human interaction. This subsequently reduces time to process and cuts down the probability of errors. AI has moved beyond experimentation to become a competitive differentiator in financial services — delivering a hyper-personalized customer experience, improving decision-making, and boosting operational efficiency. As a result, Financial services companies have no choice but to implement AI and automate the credit value chains. Act now – Change is here! AI has begun to create a tangible impact on the mortgage industry. However, looking beyond the mortgage industry offers a glimpse into the actual magnitude of the AI-enabled disruption still to come. AI technology holds the potential to fundamentally redefine the industry on all levels – challenging traditional cost structures, enabling novel relationships with end customers, and much more. For those, who are yet to embark on their journey towards an artificially intelligent future, the time to act is now. What Next? Tavant recently sponsored Chief Data and Analytics Officers, Financial Services 2021 virtually. Tavant’s leaders Dr. Atul Varshneya, VP – AI, and Vaibhav Sharma, Head – Banktech, discussed ‘Adjusting To The Neo-Normal: Evolving the Art of Credit Decisioning with AI and ML.’ Watch the video here to gain more insights. Reach out to us at [email protected] or visit us here. FAQs – Tavant Solutions How does Tavant use AI and ML to address lending gaps in the new normal?Tavant leverages AI and ML to expand credit access through alternative data analysis, remote verification processes, and adaptive risk models that account for changing economic conditions, helping lenders serve previously underserved markets safely. What lending gap solutions does Tavant offer for the post-pandemic landscape?Tavant provides digital-first lending platforms, contactless verification systems, flexible underwriting models, and real-time economic adjustment algorithms that help lenders adapt to new market realities while maintaining responsible lending practices. What is the lending gap and why does it exist?The lending gap refers to qualified borrowers who can’t access credit due to traditional underwriting limitations, lack of credit history, or geographic constraints. It exists due to rigid criteria, limited data sources, and risk-averse lending practices. How has COVID-19 changed lending practices?COVID-19 accelerated digital lending adoption, increased focus on remote verification, emphasized the need for flexible underwriting, and highlighted the importance of real-time data in assessing borrower creditworthiness. What is alternative credit scoring?Alternative credit scoring uses non-traditional data sources like utility payments, rent history, bank transaction patterns, and employment records to assess creditworthiness for borrowers with limited traditional credit history.
Leveraging MuleSoft to Mitigate Traditional Connectivity Challenges
Digital transformation does not end with buying the latest software. In the digital-everything ecosystem, success significantly depends on how quickly and effectively businesses can integrate their data and devices and applications for faster and more seamless delivery. This seamless delivery and low time to market require seamless connectivity. But traditional connectivity approaches can get in the way. Traditional connectivity approaches like point-to-point and ESB integration are not the best options for business scalability and delivering at speed due to their many limitations. These approaches lack agility and are also incapable of integration in a cloud set-up. MuleSoft, with its API-led connectivity approach, can help mitigate the challenges and enhance scalability. Top challenges with traditional connectivity approaches Point to point (P2P) approach The P2P approach is suitable only when the infrastructure has a few components, and the organization is not expecting significant growth in the near future. This approach does not help as it forms a “tightly coupled” connection between components, limiting instant expansion opportunities. P2P integration permits lower agility, high operational risk, difficulty in maintenance, and longer time to market. End to End Approach using ESB This approach is much more advanced than the P2P approach as it uses a single pluggable system. It also focuses on centralizing and reusing components. However, it has certain limitations in terms of implementation time and maintenance cost. Time to market is longer and not suitable for today’s fast-paced business environments. How MuleSoft can help mitigate traditional connectivity challenges MuleSoft has facilitated organizations to deliver projects three to five times faster and enhanced team productivity by 300%. It also provides scope for innovation and equips organizations to cope with change. MuleSoft’s Anypoint platform enables organizations to unleash the full potential of their data and applications with its API-led connectivity approach, both on-premises and in cloud environment. The API-led connectivity approach produces reusable assets and provides speed and agility to business operations. As per MuleSoft’s Connectivity Benchmark Report 2018, by leveraging its APIs, enterprises have been able to increase employee engagement and collaboration by 43%, meet business demands faster by 35%, increase IT self-service by 35% and decrease operational costs by 34%. MuleSoft makes it easy to define, write, test, and deploy APIs across multiple environments. The API management tools manage the API Lifecycle and speed up integration. It allows organizations to import specifications into development tools and to auto-generate the baseline code from just those specifications. This further reduces time to market. What Next? Integration solutions by Tavant and MuleSoft allow enterprises to efficiently design, build, and manage their APIs, applications, and products. Tavant has a robust MuleSoft COE with core practice areas in Manufacturing, Media, AgTech, and Financial Services. Tavant’s domain experience coupled with MuleSoft’s Anypoint Platform allows organizations to realize business transformation through API-led connectivity. Tavant provides flexible solutions that can simplify your overall architecture by removing point-to-point integrations and application silos to achieve business agility. Are you looking forward to improve business agility with seamless integration and connectivity? Get in touch with Tavant to unleash the benefits of MuleSoft’s integration platform. Reach out to us at [email protected] or visit our MuleSoft page.
Building a Successful Customer Experience in Today’s Banking
Delivering similar experiences to Neobanks and Fintechs is not as challenging for traditional banks as some in the industry believe. The race is intensifying between Banks, Neos, and Fintechs vying for the customer’s attention and wallet! I’ve always been passionate about leveraging technology in building better products and witnessing how more and more financial brands are using technology today to carve their own digital journeys and enrich their customers’ experiences. Conducting Financial Transactions with Unprecedented Ease and Speed My enterprise sales career in Fintech and Digital Banking is mainly fueled by a desire to impact both consumers’ and businesses’ approach to banking and how so many of us in this industry are making it safer, clearer, faster, and easier to conduct financial transactions today. Selling across the financial verticals, I’ve had both the pleasure and honor to interact with some of the most fascinating and bold decision-makers who are shaping tomorrow’s financial services industry as we know it. Meeting the Expectation of the Digital Customer: Now And in the Future Recently, while reading through what some of our favorite Neobanks are up to these days, I came across a phrase that I often hear but sometimes don’t really attribute the focus and truth that stands behind that simple statement… “The priority is to build a successful customer service brand that offers banking and financial services, then the other way around.” I couldn’t agree more. And the current pandemic, still surging amongst so many of us only strengthens the notion where we must accelerate within our digital transformation process to achieve those journeys that our customers so much rely on. As many of us in the financial services sector are focused on mapping our digital journeys, some believe that those who are “digital to the core” have been able to successfully carve their own winning strategies and steadily acquire an increasing market share. And then there are the non-digital at the core. The overwhelming majority, from community-focused to household brands, most of these banks and credit unions share one commonality between them. Being around for much longer and focusing on both their physical and digital consumer experiences, they all gained, over time, the ultimate trust and confidence of the customer. But if we break it down, being “digital to the core” simply means having access to all the building blocks that help create offerings that are fundamentally digital, faster to market, and provide an engaging, yet the simplified journey to our customers. Breaking it down even further, it is not extremely challenging for a traditional bank to create digital products and journeys. An example where banks of all sizes and budgets can launch new products and experiences would be to implement the following strategy. 1. Launch a DAO (digital account opening) process through automation, where new accounts can be launched within minutes without manual review. 2. But don’t stop there. The next natural step is the implementation of DLO (digital lending origination) process, allowing banks to digitize current lending programs and launch profitable products such as instant, unsecured small personal, and SME loans. 3. Third-party integration – the essential plugin that most Neobanks rely on to extend third-party Fintechs into their own platform as part of their digital value proposition. It is a lot less cumbersome than many believe for traditional banks to emulate a similar experience. 4. Integration with the core of choice and existing third-party service providers who providing essential banking services to-date. Choosing an off-the-shelf tech stack will not deliver the transformation banks expect, may delay launch deadlines, and increase the initially forecasted budget. What Next? To make this work, banks should consider choosing those technology partners who can add professional services to their product stack offerings. A consultative approach combining product stacks with the outsourced talent to digital transformation is a must for any bank when considering a cost-conscious approach and time to market. At Tavant, we focus on helping traditional banks carve their own digital journeys and enrich the experiences offered to their consumer-facing channels by implementing the technology mentioned above stacks while adding a consultative approach strategy. Our partners at Tavant happen to be some of the most renowned brands in financial services and small banks who are quietly enabling their digital transformation. We take pride in being a mid-size and super-focused technology provider by approaching transformation projects; we have in-depth knowledge, passion, and proven industry results. To learn more, reach out to us at [email protected] or visit us at www.tavant.com. FAQs – Tavant Solutions How does Tavant help banks build successful customer experiences?Tavant provides customer experience platforms with omnichannel integration, personalization engines, real-time analytics, and customer journey optimization tools. Their solutions enable banks to deliver consistent, personalized experiences across all touchpoints while gathering insights to continuously improve customer satisfaction and engagement. What customer experience technologies does Tavant offer for modern banking?Tavant offers AI-powered chatbots, predictive customer service, personalized product recommendations, mobile-first interfaces, real-time notification systems, and comprehensive analytics dashboards. These technologies help banks understand customer behavior, anticipate needs, and deliver proactive, personalized service. What makes a successful customer experience in banking?Successful banking customer experience includes seamless omnichannel interactions, personalized service, fast problem resolution, transparent communication, intuitive digital interfaces, proactive support, and consistent service quality across all touchpoints and channels. How has customer experience changed in modern banking?Modern banking customer experience has shifted toward digital-first interactions, real-time services, personalized offerings, mobile accessibility, self-service options, and proactive communication. Customers expect instant access, transparent processes, and personalized financial guidance. What technologies improve banking customer experience?Technologies improving banking customer experience include AI-powered chatbots, mobile banking apps, predictive analytics, personalization engines, biometric authentication, real-time notifications, video banking, and integrated omnichannel platforms that provide consistent service across all channels.
Decoding the CX Paradox in the Mortgage Industry
The Journey So Far The clock is ticking as more and more customers have started expecting the mortgage companies to offer advanced digital capabilities. Customer expectations for speed, agility, transparency, convenience, and personalization are getting elevated by their delightful digital experiences outside lending. Customer expectations are at an all-time high in every other area of their lives, whether listening to Pandora or hailing an Uber or watching Netflix on their smart TVs. Digital mortgage players have been on the rise, and direct-to-consumer (DTC) originations account for a growing share (more than 25 percent) of the market. While the mortgage loan process continues to be a time-consuming and expensive endeavor for mortgage companies, which are not just witnessing the challenges of meeting escalating regulatory requirements but also increased demand from their customers for a quick, painless process. Most mortgage companies have also been striving to compete profitably in a rapidly transforming competitive landscape. FinTech has also greatly improved the mortgage process; however, traditional lenders are still dominating the industry. A look at the challenges that lenders need to overcome Firstly, buying a home mortgage is the largest financial transaction of most people’s lives. For many, it is also the most cumbersome financial transaction to endure. What adds to it is ‘not so digital’ borrower engagement approach of today’s lenders. Most lenders continue to provide fragmented collaboration solutions that are heavily call-center-based. They still prefer to follow the traditional methods where document collection and borrower information is obtained via channels such as call contact, e-mail, portal connections, etc. Suffice to say; there is massive room for improvement. The mortgage companies need to embrace next-gen technologies to revamp their loan application process and, subsequently, the CX. Secondly, mortgage lending is a collaborative venture. Lenders partner with an array of service providers, including credit, flood protection, fraud prevention, compliance, appraisal, title, and insurance providers, along with income, employment, and asset verification providers. Each delivers a vital element to create a loan that can be closed and sold into the secondary market. This has been paper-based work with information passed between partners in documents and forms before, which created significant time delays and errors that led to inaccurate and inconsistent data resulting in poor quality data and higher loan origination costs. Thirdly, disparate systems are often poorly connected, impacting data quality negatively while increasing the risk of security breaches. Lending companies consider system integrations a pretty daunting, expensive, and time-consuming process to implement and maintain. Lenders need a road map to success that will guide them through the process of digital transformation while remodeling the lending process. When lenders partner with third-party providers to complete the loan process, the data moving through third-party systems must flow into the lender’s LOS. To sum up, lenders must connect the blocks and retrospect their current redundant processes, system integrations issues, and borrower satisfaction. Solving the mortgage riddle Ask any prospective or recent borrower what matters most in choosing a lender, the answer will be ‘loan-to-value’ while the other important element consistently remains as ‘Customer Experience’. These are the twin pillars for most borrowers that drive their decision to go with one lender instead of others. But how do prospective borrowers figure out which lender has the best prices or provides superior CX or the speediest approval or the most reliable closing? The 3 Secret Ingredients for the Ultimate Mortgage Customer Experience Borrowers are consistently looking for connected digital customer experiences that can be accessed wherever they are, whenever they want. Lenders must leverage digital technologies to tap into new business opportunities to streamline processes and exceed borrower expectations and create a holistic ecosystem around the lending experience. 1. Digital Innovation- A bridge to the future To provide a truly delightful borrower experience and take a customer-centric approach, which drives revenue growth, lenders should evaluate what the primary focus of digital technology is. Besides empowering borrowers with next-gen customer-facing technologies, lenders must also consider measuring the sensitive points in each borrower’s loan journey that end up making or breaking their delightful experience. Reassurance, simplicity, transparency, as well as speed, are extremely critical during the entire mortgage journey. 2. Borrower Data- A Secret Sauce to the Customer Journey Delightful CX begins with understanding what customers want, which is only possible by analyzing borrower data. Leveraging data helps them understand the customer and build the proper customer journey view. Needless to say, the power of data insight is undeniable, and with a data visualization platform that can provide a 360-degree view of all data—no matter where it resides—lenders should create scalable and relevant omnichannel experiences for their customers. Understanding customer behavior, as well as their preferences, can help lenders prioritize investments in CX. It is crucial to gather feedback across all channels to explore opportunities for improvement. Lending companies should map out their customer’s journeys to identify all touchpoints across all channels and then leverage it to engage effectively with them. Data analytics can subsequently help lenders deliver superior customer experience at a fraction of the cost. 3. AI, Automation and Analytics – 3A Solution The right lending solution should emphasize on UX and delivers an unparalleled digital experience for consumers. It should provide a seamless and superior user experience across the value chain of the loan origination process for everyone involved, including the borrower, MLO, and the operations staff. Providing an optimized user experience from the initial borrower portal interaction until the loan is closed and funded not only delights customers but also assists in hiring and retaining key talent within the organization. This can be done using: Real-time expert assistance from experienced live loan originators, chatbots, and self-service tools. Data aggregation and workflow automation to quickly qualify and complete the application accurately to ensure the loan is approved and closed faster once submitted; Robust, rule-driven loan scenario loan calculators to play out different loan scenarios and for accurate decision making Looking Ahead: The use of technology in the mortgage industry will always be at a vital inflection point. Technology capabilities
Tapping Digital to Deliver Exceptional Mortgage Experience
Though the COVID-19 outbreak has affected all sectors of the economy, it has particularly exposed glaring needs within the mortgage industry. These changes will undoubtedly rewrite many of the industry’s “traditional” practices moving forward into the rest of 2021 and establish a “neo-normal” standard going into 2022. Among the battery of revelations, digital transformation and customer experience have become industry-wide focal points caused by the pandemic. According to a recent Forbes Report: Nearly 90% of lending executives stated that the pandemic is proving a powerful catalyst for digitizing their firm’s mortgage processes, and 85% described their efforts for mortgage process digitization before COVID-19 as aggressive. As a former Loan Officer, I was forced to use dozens of workarounds due to inherent flaws within the systems that I – and the majority of LO’s in the industry – were forced to use. Developments in recent years have addressed those limitations to a certain extent, but at a fundamental level – things need to change. Looking back at the early 2000s and then fast-forwarding to today, it’s amazing to witness all the functionality that helps automate the mortgage lending process. Back in 2003, the average loan closing time was somewhere between 30-45 days. Although technology has changed much of the world since 2000, it is astonishing that the most important metric has stayed roughly the same. Today, it takes just 2 hours to walk in and out of a Maserati dealership with a $150,000 car financed and ready to go. Why does it still take 30-45 days to finance a $150,000 mortgage? Let’s rephrase that question – why has the “time-to-close” mortgage stayed the same after all this time? In an era where customer expectations have never been higher for next-gen digital solutions, the mortgage loan process remains highly dependent on disparate systems. The size and complexity of mortgage applications make it nearly impossible to eliminate manual work. The need for process automation is great, not just to provide more satisfying mortgage experiences, but also to significantly increase productivity, reduce operational costs and minimize the impact of human error. It’s a win-win for both mortgage providers and borrowers. Lenders can automate the mortgage origination process and upgrade their “traditional” methods of processing with “neo-normal” digital solutions. A sophisticated process solution will allow lenders to simplify the application cycle. Furthermore, enabling real-time integrations of all associated parties by using loan origination systems (LOS) to exchange data between applications can significantly bring down the loan-processing time from weeks to days. Put simply, an efficient automation process can lead to shorter loan processing and overall better customer experiences. Sometimes, in order to make forward progress, you must be willing to let go of what’s holding you back. Indeed, automation has vast potential in the mortgage industry, just waiting to be tapped. Adapt, Survive and Thrive What should mortgage companies focus on in this new technology-enabled environment? What are the benefits that really matter? What technological capabilities should they pursue? Disruptive technology closes the gap and helps lenders create positive customer experiences, for both borrowers and loan officers. Tavant is able to turbo-charge this process, creating unforgettably satisfying customer experiences. We welcome you to contact us at [email protected] and/or learn more about Tavant VΞLOX, the industry’s leading AI-powered digital lending platform. FAQs – Tavant Solutions How does Tavant help mortgage lenders tap digital technologies for exceptional customer experiences?Tavant provides comprehensive digital mortgage platforms with AI-powered automation, intuitive user interfaces, real-time communication tools, and seamless integration capabilities. Their technology enables lenders to deliver fast, transparent, and convenient mortgage experiences that exceed customer expectations and drive competitive advantage. What digital capabilities does Tavant offer to enhance mortgage customer experience?Tavant offers mobile-first applications, automated document processing, real-time status tracking, AI-powered chatbots, personalized loan recommendations, and digital closing capabilities. These features create seamless, efficient mortgage journeys that improve customer satisfaction and accelerate loan processing. What digital technologies are transforming mortgage experiences?Key digital technologies include AI and machine learning, mobile applications, automated underwriting, digital document processing, blockchain verification, cloud computing, API integrations, and real-time communication platforms. These technologies enable faster, more convenient, and more transparent mortgage processes. How do digital mortgage experiences benefit borrowers?Digital mortgage experiences benefit borrowers through faster processing times, 24/7 accessibility, transparent communication, reduced paperwork, real-time status updates, mobile convenience, and simplified application processes. These improvements reduce stress and uncertainty while accelerating homeownership goals. What makes a mortgage experience exceptional?Exceptional mortgage experiences feature fast processing, clear communication, transparent pricing, personalized service, convenient digital tools, proactive updates, and smooth closing processes. They combine efficiency with personal attention to create positive, memorable customer interactions.
Quality Engineering Trends in 2021
The new consumer demands nothing less than instant gratification. Need a cab? It’ll reach your location in 5 minutes. Hungry? Give the food tech app 24 minutes. Maybe less. Besides, digital services are seeing a large-scale adoption from consumers around the world, and COVID-19 has further accelerated this pace of adoption. These trends leave no room for error or software failure anymore. Volume and accuracy drive business. Naturally, organizations commit to quality at scale and are therefore rendering software testing and engineering an essential enabler of their operations. This has ensured that quality engineering becomes an even more critical part of the development process, going from a standalone vertical to a horizontal enabler. In this blog post, we discuss the trends that will further drive the rise of quality engineering in 2021. 1. The need for speed will be the key driver for quality Test automation has become a major area of focus in QA in recent years. Automation enables high speeds in the testing process, thus powering lower time to market. This calls for higher agility and DevOps across organizations. Software changes fast now. New feature enablement, enhanced user experience demand this. DevTestOps will drive the faster deployment of these changes in software, once again reducing the time to market for enhanced features and UX improvements. 2. Connected devices will call for higher instances of IoT testing Connected, smart appliances are on the rise and will continue to be so in the coming years. In fact, by 2025, it is expected that there will be more than 30 billion IoT connections, averaging almost four IoT devices per person. The proliferation of connected devices is driving the rise of IoT testing, with its cutting-edge technologies that test software in-built IoT devices. Beyond hardware challenges, IoT testing will also include compliance requirements, access management, hardware issues, among others, to test the seamless performance of connected devices. 3. New AI, ML RPA led testing skills will need to be acquired With saving time, enhanced collaboration high on organizational agendas, AI, ML, RPA will no longer be good-to-have in testing processes. They will become mainstream and will be used to build entire QA environments and help enterprises scale with sustainability and stability. New skills will have to be acquired for these new standards of testing. 4. Testing for UX across devices 90% of consumers around the world use more than one device – from smartphones to smart TV, tablets to laptops. Naturally, apps and services will need to be tested across devices for performance. Interoperability will become a must-have, and organizations will further scale their multi-device, interoperability testing rapidly in 2021. 5. More cybersecurity testing in the face of increasing cyber threats Cyber-attacks are costing organizations and consumers significant amounts of money. 68% of business leaders globally feel that their cybersecurity risks are increasing. Naturally, cybersecurity testing is gaining momentum in the quality engineering space in order to ensure minimal costs and downtime in the occurrence of a threat event. Cybersecurity testing includes penetration testing and provides an in-depth understanding of an organization’s security posture. It identifies points of weakness that could invite threats into the system. Therefore, in the face of increasing cybersecurity incidents around the world, cybersecurity testing will gain even more prominence in 2021. 6. Performance Engineering will become part of organizational cultures Performance engineering enables continuous, proactive testing of application performance. With loads increasing and UX demands on an all-time high, organizations will have no choice but to take on performance engineering head-on. Performance engineering enables QE teams to build accurate and effective performance metrics. In 2021, we foresee performance engineering becoming a matter of corporate culture. It will allow checking every section of systems and software and delivering business value through quality. Which trends do you foresee driving QE in your organization? Reach out to us at [email protected] or visit here to learn more.
Tavant Sponsors CDAO FS Live 2021
Tavant is participating at CDAO FS as a Gold Sponsor. Join us as we lead the conversation on data-driven transformation in financial services and discuss AI, Data Monetization, DataOps, Data Protection, Cloud Migration, and more at this 3-day virtual summit from March 2-4, 2021. Hear our experts at CDAO FS Tavant leaders Dr. Atul Varshneya (VP of Artificial Intelligence) and Vaibhav Sharma (BankTech Practice Head) will be speaking on “Adjusting to the Neo-normal: Evolving the Art of Credit Decisioning with AI & ML” at CDAO FS. The session is scheduled at 03:15 pm, EST on March 3. The session will focus on – Automating information capture and flow for STP (straight-through processing) Multi-parametric assessment for more accurate risk prediction Opportunity to engage in customer’s journey and value for the institution Atul and Vaibhav bring over two decades of experience in AI and BankTech leadership, respectively. They will share deep insights about industry needs and solutions as the Financial Services industry goes through unprecedented churn and change. Why you should take the time to meet Tavant at CDAO FS The global population generates up to 2.5 quintillion bytes of data every day. This opens up a world of possibilities for visionary businesses to become truly data-centric in their decision-making. The Financial Services industry is no different. At Tavant, we believe that this data explosion opens up brand new opportunities for the industry to begin the process of AI and ML adoption. Technological advances have led to more mature AI tools, and there is an increased awareness of AI applications in the industry. Needless to say, the ability to constantly learn and adapt to changing circumstances is what separates AI from other technologies. At CDAO FS, we are taking it up a notch. We look forward to sharing our latest innovations in AI ML applications in the new normal and how Tavant can enable you to navigate your business to the digital next. We look forward to seeing you there! For more information or to register for the event, click here.