How Fintech Automation is Changing the Face of the Lending Industry
Understanding the Changing Landscape in the Mortgage Industry The mortgage industry is under enormous pressure to perform in the face of fierce competition, increased due diligence for loans and borrowing (due to the COVID-9 pandemic and its economic ramifications), crunching timeliness, and ever-growing data. According to Gartner, a human error in the financial sector results in 25,000 hours of pointless rework per year, costing up to $878,000. Our only stumbling block, we believe, is fintech automation. The global fintech industry is estimated at $65,88,780mn in 2021 and is projected to reach $1,66,52,680mn by 2028 at a CAGR of 13.9% for the forecasted period. Fintech automation can define even the most unstructured data and support lending process automation to deliver a resource, cost, and time-efficient process. Mortgage and lending have already been reimagined using automated technology such as chatbots and digital assistance. Given the massive amount of data, the need for real-time, data-driven strategies for effective customer UX and UI, and loyalty retention in the mortgage lending industry, this shift is inevitable. Customer onboarding to Know Your Customer (KYC), legal processes, due diligence, credit checks, and form fill-ups have previously been observed to require 50-75% of the onboarding process cost. However, well-integrated lending automation, combined with optical character recognition and natural language processing, assists mortgage lenders in shortening the lending cycle and lowering costs. “Generative AI enables bank CIOs to offer technology solutions to the business in pursuit of revenue growth,” according to Moutusi Sau, VP Analyst at Gartner, “while autonomic systems and privacy-enhancing computation are long-term solutions that provide new options for business transformation in financial services.” We can cite several reasons for the rapid adoption of automated technology as a core business process in lending process automation across verticals. Customer expectations have risen dramatically in terms of complete transparency, customer-centric, highly personalized interactions, and maximum participation. As a result, maximum fintech implementation can be seen in customer relationship management (CRM), accounts payables, mortgage automation, risk management, payment arrears, reconciliation requirements, insurance premium calculations and settlements, back office, and front office, among other areas. Aside from process integrations, the lending industry requires fintech capability to eliminate cyber fraud risks and identity thefts, as well as a digitally secured infrastructure to protect customer data related to mortgage and lending. Customers feel empowered with access to secure omnipresent, omnichannel, digital transactions, and payments when lenders provide mortgage lending automation with simplified tasks. Self-service in CRM with chatbots and instructive guidelines, according to Deloitte’s Finance 2025 report, creates a better customer interface. Furthermore, mortgage lenders can use fintech automation to absorb data from borrower application forms, extract information from borrower payroll applications, and automatically upload loan data into respective portals. More importantly, automated technology enables credit decision-making systems and microdata inspection with low error rates for seamless loan approval and disbursement. Considering this massive shift, organizations have been striving hard to develop deeper hyper-automation processes or at least implement partial automation, machine learning, and artificial intelligence to attain optimum operational efficiency. Categorically, RPA tools have also matured from traditional desktop automation to enterprise solutions. This has profusely helped in managing complex processes like strategic decision-making, cognitive learning capability, user interfaces, and so forth. Fintech automation is undeniably booming, and competition is heating up. Companies are planning both organic (diversification, geographical expansion, etc.) and inorganic (mergers and acquisitions) strategies to gain a competitive advantage and remain sustainable. Gartner estimates that banks and investment firms will spend $623 billion on technology products and services by the end of 2022. The major investments will be in generative AI, autonomic systems, and threat-nullifying technologies. Final Thoughts During our research, we have found that CEOs across the globe believe that cloud-based ERP, cognitive technologies, and hyper-automation will radically simplify lending processes and accelerate the lending industry as a whole and not in silos. In fact, hyper automation is already in its nascent stage of enterprise adoption. Apart from this, the banking and investment services will also witness larger use of generative artificial intelligence, generative adversarial networks (GANs), and natural language generations for fraud detection, predictive analysis, synthetic data generation, artificial intelligence-backed follow-ups, and risk-factor modelling. With the help of algorithm-driven and interactive AI and robots, new service models will emerge. This will not only diversify the financial workforce, but will also link the entire organization into a real-time, digitally connected workplace. What’s Next? Tavant’s consulting-driven approach to automation helps mortgage lenders and banks significantly improve productivity and enhance customer experiences using our deep automation and domain expertise. By combining the power of industry tools and accelerators, we drive organization-wide transformation through RPA, ML, and AI to solve your most important business challenges. To learn more, visit us here or reach out to us at [email protected].
Realizing the Goal of Fully Automated Lending
Borrower expectations are still not being met by the mortgage industry. While many lenders have provided a seamless mortgage application experience by digitizing the front-end platform, the industry’s digitization remains incomplete. Many origination and servicing processes remain slow, manual, labor-intensive, and fragmented, making them vulnerable to disruption—mortgages close in 51 days on average, which is far too long in today’s fast-paced world. Underwriters and processors do not have the tools to complete their tasks efficiently and effectively. The mortgage industry has been embracing technology to streamline the mortgage application process to make the consumer experience smoother and faster. Touchless lendingTM is quickly becoming the industry’s standard operating system for large-scale automation of mid and back-office mortgage operations. How does Touchless LendingTM change the game? Despite the amalgamation of multiple technologies into the mortgage origination process, the cost of originating a loan has steadily increased over the years, reaching a peak north of $10,000. Tavant wanted to create a product that was completely, directly, and only focused on solving this problem. The vision of Touchless LendingTM is to eliminate the many humans-in-the-loop embedded in the mortgage process, to phase out the rivers of paper that flow through each loan in the application intake and decisioning process, and to knock out the need for multiple thrashes and iterations between the borrower, loan officer, processors, and underwriters, which result in an increased cycle time of anywhere from 45 to 60 days to close a loan. Touchless LendingTM targets these underserved middle and back-office associates, allowing them to make a clear-to-close decision in as little as five days, handle five times as many mortgages at once, and save more than 75% on processing and underwriting costs per mortgage. To solve the complex problem of using a machine to do the work of a senior processor and an expert underwriter, the Touchless LendingTM platform prudently employs AI and Machine Learning techniques. We combine computer vision and natural language processing with procedural rules processing to provide the best technical solution for straight-through processing, automated loan decisioning, automated loan processing and automated underwriting. The automated lending platform is LOS-independent and will work with any CRM and POS platform in the mortgage industry. The platform employs Digital Ledger Technologies to ensure that all operations on loan are immutable and can be tracked from its inception to its closure/funding, reducing repurchase risk and allowing investors to perform their due diligence when purchasing the loan more efficiently. Delivering an Exceptional Mortgage Customer Experience Touchless LendingTM is an AI-powered lending-as-a-service platform that offers straight-through mortgage processing and automated underwriting as part of the mortgage manufacturing pipeline from start to finish. Instead of relying on physical documentation and manual data entry, loan officers, processors, and underwriters use Touchless Lending’s optimized workflows to engage with data and make decisions faster. This one-of-a-kind automated mortgage software solution enables lenders to originate more mortgages more quickly while lowering costs and repurchasing risks. Touchless Lending seamlessly integrates with your existing systems, such as CRM, POS, and LOS, and automates the loan production process. Each service provided by the Touchless LendingTM platform is unique in that it includes embedded innovation that provides a true business and operational lift to that service. Touchless Documents, for example, uses a multi-OCR strategy to extract the best possible classification and data extraction from a paper document via an intelligent selection among a network of best-of-breed OCR providers. From Chaos to Order: A Perfect Mortgage CX Strategy and a Boon for Lenders First, lenders do not need to purchase the entire end-to-end platform to gain and lift their mortgage manufacturing pipeline. Individual service endpoints for Document, Income, Credit, Collateral, Asset, Title, Multi-Investor, and Fraud Analysis can be consumed independently through the platform’s API Store. Second, Touchless LendingTM services can be integrated into the Lender’s ecosystem in days or weeks rather than months, resulting in immediate benefits and an impact on the Lender’s cost and cycle times. Third, Touchless LendingTM provides: A 77% cost savings for underwriting and processing. A 4.5-fold increase in underwriting to handle more mortgages at once. Clear-to-Close decisions in as little as five days to a week. Touchless LendingTM has resulted in an 11% increase in total annual gains for lenders and significant savings in operational costs. Touchless LendingTM can accomplish this by reducing process time due to improved quality and digital loan files, lowering document processing costs, gaining warehouse line interest savings, gaining GSE interest rate arbitrage, and maximizing appraisal waiver utilization. Reinventing the mortgage customer experience: now more than ever, mortgage lenders need to focus on delivering a superior online customer experience. Lenders value the quicker time to product deployment and the seamless/intuitive integration into their existing workflows and business processes. The ROI is immediately observable and tangible and can be demonstrated through multiple real-world deployments of Touchless LendingTM services. The Touchless LendingTM platform includes an optional Underwriter’s Workstation, the most user-friendly and advanced workstation for underwriters available in any offering on the market today. Data visualization techniques, combined with AI and Machine Learning-driven insights from the borrower’s and property’s profile and characteristics, provide the quickest path to comprehending a loan’s story and thus the quickest path to loan decisioning. Although the Touchless LendingTM platform initially focuses on automating the mortgage processing and underwriting lifecycles, the platform’s goal is to automate anything and everything that can be automated in the path from the borrower’s post-application submission all the way to its destination of becoming a closed or funded loan, including post-closing activities. What’s Next To know more about Touchless LendingTM, reach out to us at [email protected] or visit us here. FAQs – Tavant Solutions How does Tavant enable fully automated touchless lending?Their AI-powered platform processes applications, verifies documents, assesses credit, and makes decisions without human intervention, integrating with multiple data sources to complete the lending process digitally. What percentage of loans can be processed through Tavant touchless lending platform?The platform can process 80-90% of standard applications without intervention, flagging only exceptional cases for manual review. What is touchless lending?A fully automated loan process using AI, machine learning, and automated workflows to process applications,
CI/CD and Security Testing Integration
Introduction CI and CD = Continuous integration & Continuous delivery OR Continuous deployment. CI/CD is the modern-day software development process in which we can release updates at any time in a sustainable way. The code changes are made frequently and dependably based on customer requests and the sprint life cycle. A CI/CD pipeline, popularly known as the DevOps pipeline, builds up code, executes tests (CI), and wisely deploys an updated application version into the following environment. It also ensures that code changes being merged into the repository are efficient to deploy into the live environment to meet the final goal, i.e., ship software with swiftness and effectiveness. The Pros CICD is a low-risk option – as the process is completely automated. There are no manual interventions for setup or even config changes. Releases can occur in defined frequencies and with the client’s feedback. So, this ought to be a faster & optimum way. Smaller, more recurrent software releases are less disruptive and are easier to troubleshoot or roll back in case of any problem. The process with a structured manner increases productivity; a product will be released independently of other objects, and in the case of multiple series of code- we can release changes independently. This will increase development effort with productivity. A CI/CD pipeline allows teams to analyze builds and test results in detail, leaving little room for last-minute bug surprises. The Cons Team dependencies – Infrastructure, including servers, could be managed by different teams, and when the need arises to access those, it can cause unnecessary delays. Thus, all groups need to be well coordinated with each other all the time. Procedure orientation delay– If defined for any pre-approval process in a project, like no direct access to the infrastructure, it can sometimes delay troubleshooting. New skill sets must be learned – Multiple tools to be used and vendor dependency on those require people with a different skillset in your team. This demands a severe intellectual investment to learn these tools. Why do we need to infuse security validation in our CI/CD pipeline? Continuous integration and Continuous delivery are about speed, repetition, and automation. Development and QA teams are constantly under pressure to deliver releases as fast as possible – provide any new feature(s) or fix the critical bug(s) or an enhancement. But the need for speed repeatedly ignores the importance of security testing, which leaves you at risk of failing to secure your application. Vulnerabilities or flaws found in the live version of an application can cause a breach of confidentiality and expose the software to malicious activity, which costs time, money, and resources to fix and eventually will delay future releases. Integrated security testing makes life simpler for software development teams. That is why DevOps teams habitually embrace the concept known as DevSecOps, which promotes security integration into core DevOps practices. To lessen the chances of vulnerabilities going unobserved during the SDLC, all organizations must add security testing to their existing CI/CD pipeline. Undoubtedly, adding security checks will initially slow down your development cycle. Still, we all need to understand that these steps will improve the security of your organization’s CI/CD pipeline and adds another layer of oversight to ensure security for the end-users. Velocity is the key for every business, where security testing integration is a terrific cream over CI-CD. Thus, it is important to introduce security best practices throughout the build/release pipeline. Conclusion: It is not a secret that security is hard to get right. Still, security is the key in this technologically fast-moving world; therefore, performing security testing is no longer a preference. It should be performed frequently, especially with all critical releases, and should be added to the build/release pipeline for top results. With strong CI/CD security in place, teams can find and fix security issues without notably slowing down the pipeline flow or having to delay/roll back releases. Securing your CI/CD pipelines at every stage and environment that comprise the pipeline should be a priority for any organization that embraces DevOps.
Pinch me… Dreamforce 2022 is back!
Is it just me, or does this year’s Dreamforce feel like a much-anticipated reunion? Part tech conference, part homecoming is how Salesforce describes one of the most anticipated technology conferences this year. And after three years of online interactions, it’s no surprise that Dreamforce 2022 is generating tremendous excitement amongst the technology crowds. But enough about everyone else! Here are my Top 5 reasons I’m looking forward to Dreamforce 2022: Everyone who’s anyone will be there. Like on a summer beach after the exams, the crowds are expected to be everywhere. Three days of networking opportunities with over 30000 people – meeting new leaders and connecting with old friends. That’s a lot of handshaking, so don’t forget the sanitizer. In-depth sessions, larger-than-life speakers. Do you know those cinematic flash-forward sequences where the team describes how they will break into a super secure location? Everything time-coordinated and moving to peppy music.? That’s how I imagine my approach will be to attending keynote sessions this year. I know we must pick our favorites, but frankly, between celebrities, activists, and athletes, it’s hard to decide. We are talking about over 1000 potentially thought-breaking sessions. Planning, my friend. It takes planning (and the agenda builder on the Dreamforce webpage is just what you need). Boring Demos? No, it’s a Demo Battle An epic game show theme where Salesforce partners get a mere three minutes to showcase their tech. It’s going to be fast and exciting. And the best part? The audience gets to vote. I don’t know about you, but I’ll carry a poster saying I WANT TAVANT! Dreamfest Fundraiser Every year, Dreamforce organizes a fundraising event which is also a chance for Dreamforce attendees to chill. This year’s concert will benefit the UCSF Benioff Children’s Hospitals. Dreamfest will take place on Wednesday, the 21st of September, at Oracle Park in San Francisco. And this year, we will be rocking to… The Red Hot Chilli Peppers!!! That’s right; the Red Hot Chili Peppers are performing at Dreamfest! And by the way, all proceeds will benefit the UCSF Benioff Children’s Hospital. See what I did there? Dreamforce will take place in San Francisco at the Moscone Center from September 20–22, 2022, and is slated as the largest Salesforce conference of the year. Appropriately, this year’s theme is ‘Go big and come home.’ I can’t wait! ABOUT THE AUTHOR: I am Simran Tayal, Director Marketing at Tavant and I’ll be at Dreamforce with my team at Hotel Zetta, 55 5th St, San Francisco. For more information, click here.
The Rise of Streaming Analytics in the Media Industry
Compared to a decade ago, the increase in devices and quality of connectivity have transformed how we consume media. Streaming services made it possible for us to consume content continuously without the need to upload or download an entire file. Additionally, the sudden boom in OTT applications during and post-pandemic has expanded the use of media streaming platforms worldwide. This explosion in the volume of streaming content data fueled the need to understand customer consumption faster, resulting in the need for real-time analytics or streaming analytics. For example, providing recommendations in near real-time is now required, and the ability to analyze advertising data gives providers an advantage. The Evolution of Streaming Analytics In time-sensitive scenarios, real-time analytics uses newly generated data to make predictions, ask questions, and automate decision-making in the application. While previous analytical systems could run periodically (say every 24 hours), this was insufficient for time-sensitive data. In the case of streaming information, periodic analytics would be outdated by the time it is processed. Also, as data streams have no beginning or end, they cannot be broken into batches. This continuous flow of data also requires a different processing and data architecture. Streaming Analytics Processes Data Differently Streaming analytics is the processing and analysis of data flowing continuously, and it relies on real-time data. Real-time data can be streamed from transactional databases using change data capture (CDC) or from applications using an event streaming platform such as Amazon Kinesis and Kafka to data sinks. Stream processing engines are runtime libraries that help developers write code to process streaming data without dealing with lower-level streaming mechanics. It uses event stream processing, which analyses large-scale real-time information and in-motion data. Some of the most widely used stream processing engines are Apache Spark, Apache Flink, Apache Kafka, Apache Storm, Apache Samza, AWS Kinesis Streams, and Apache Flume. Real-Time Analytics Made Real Streaming analytics aims to offer up-to-date information and keep the state of data updated with very low latency. It provides real-time insights to enable more responsive decision-making. With media and entertainment companies generating vast volumes of data with every click, analytical speed is crucial. Real-time analytics or streaming analytics can help the media industry gain an advantage over competitors in the following ways: 360-Degree Customer View Streaming analytics enables businesses to measure data usage across multiple media platforms accurately. As a result, media providers can now aggregate data sets to develop a clear 360-degree customer view. These analytical data points can even include user viewing and engagement for companies to know how long, when, and where their viewers consume their content. Apache Flink is an open-source platform that can ingest massive amounts of continuous streaming data from multiple sources, which is processed in a distributed manner on multiple machines. Apache Flink is used by King (the creator of Candy Crush Saga) to analyze their 300 million monthly users who generate more than 30 billion events every day from different games and systems. Flink offers processing models for both streaming and batch data, enabling data scientists to access these massive data streams while retaining maximum flexibility. Anticipating Viewer Churn According to Interpret’s Video Churn Today in 2021 report, SVOD subscribers increased by 14% in the second half of 2020. During the same time period, the cancelation rate increased from 15% to 20%, and nearly 20% of subscribers switched services to gain access to exclusive content. In such a volatile and highly competitive market, streaming analytics provides operators with more accurate churn prediction models. Streaming analytics brings together both real-time and historical users (including user behavior and engagement) to identify subscriber clusters with a high churn risk. Impacting Customer Experience Media companies must be able to introduce user activation, reactivation, and engagement campaigns that get their users to continue consuming content on their platforms. Streaming analytics uses click records from various source platforms and enriches the data with demographic information to serve more relevant content to the targeted audience. Europe’s leading media and communications company, Sky, provides TV, streaming, mobile TV, broadband, talk, and line rental services to millions of customers in seven countries, and relies on the Google Cloud Streaming analytics services to deliver customer service at scale. Sky collects diagnostic data from its millions of TV boxes. By combining this set-top box diagnostic and viewing data with streamed and batched information from reference feeds, Google Cloud Streaming analytics created a data warehouse on BigQuery, to help ensure the best possible user experience. Real-time Recommendations Today’s media consumers demand personalized, relevant, and contextual content. But with an increase in streaming services, competition for viewership is intense. Recommendation engines driven by streaming analytics can offer more customization and personalization to keep viewers coming back for more. Based on the real-time analysis of this big data, media companies can make better decisions on content dissemination. Content Usage Insights Deep big data streaming analytics is also giving media companies deeper content insights. It helps uncover which genres are in high demand, what content is preferred at which time of the day, when they pause, or what they skip. By analyzing this live data in real-time, businesses can detect and act on strategic content opportunities. Apache Spark is an example of a streaming analytics tool that makes use of a big data processing engine to provide scalable, high-throughput, and fault-tolerant live data stream processing. Online news provider Yahoo uses Apache Spark for personalizing its news. It uses Apache Spark’s streaming analytics processing to find out what kind of news users are interested in and the kind of users who would be interested in reading each news category. Troubleshooting apps, devices, and more According to video analytics solution provider NPAW, 4.9% of video-on-demand views experience some error; for live views, the number is 7.6%. While media houses offer the same service across different devices, the understanding is that the approach cannot be the same. Netflix uses the Amazon Kinesis streaming analytics solution to monitor the communications between its applications so it can detect and fix
HELOC – The Bright Side of our Turbulent Times
Volatility is the Norm It’s been a crazy two years, for many reasons. Between February 2020 and January 2022, the mortgage industry witnessed something we never thought we’d see: 30-year fixed-rate mortgages below 3.5 percent. These rates attracted a record number of refinances, with cash-out refinances reaching $1.2 trillion by 2021. Then, in what seemed like an instant, mortgage rates skyrocketed in Q1 2022, effectively ending the refi boom. Home Buyers are getting nervous; refinances are drying up and Lenders are scrambling. As interest rates and mortgage interest rates rise, consumers are turning to home equity lines of credit (HELOCs) to access a portion of the equity they have. I mean we all still want our updated bathrooms, kitchen remodels and for the lucky few backyard pools. Why Homeowners are Seeking HELOCs? HELOCs offer flexibility. Consumers are showing a growing interest in home equity loans and home equity lines of credit as a means to access more affordable capital and take advantage of rising home values. For example, where I live in Carlsbad, CA, home sale prices have increased by 64% in the past two years – That is a lot of “equity.” Homeowners don’t have to borrow the entire credit line with a HELOC and are only be charged interest on the amount they do borrow. Borrowing no more than you absolutely need during times of interest rate volatility can help keep their payments more manageable. A home equity line of credit, or HELOC, is one of the best options on the market right now for homeowners looking to tap into their home equity. Lenders Need to Navigate and Embrace Change Whether you are a lender who is seeing a flood of HELOC consumers and wish to deliver a seamless borrowing experience or a lender who is planning to add HELOC to your portfolio to seek growth in a declining refinance market and cross-sell opportunities to their existing customer base- you need to be proactive. Enter a Delightful Lending Experience with Tavant FinXperience – Advancing the Future of Lending Technology with AI-Powered Digitization Tavant’s FinXperience provides personalized and configurable journeys for HELOCs and home equity installment loans through a suite of user-friendly portals and mobile companion apps. It offers: Accelerated deployment – Standard integrations with LOSs, CRMs, PP&Es, document generation, and other third-party systems enable solutions to be deployed in 6 weeks or less. Fast approval – Getting a home equity line is often cumbersome for consumers and requires lots of paperwork. However, Tavant’s FinXperience makes the process for lenders much easier, and they can offer funds in just a few days. It can just take 5-minutes to decisioning and 5-days to funding. Touchless Lending™️– How AI-powered Touchless Lending™ Simplifies, Streamlines & Saves $$ Tavant offers a seamless loan manufacturing pipeline for HELOCs through Touchless Lending™️. Touchless Lending™️ focuses on these underutilized middle and back-office associates, allowing them to make a clear-to-close decision in as little as five days, handle five times as many mortgages at once, and save over 75 percent on processing and underwriting costs per mortgage. The Touchless Lending™️ platform judiciously utilizes AI and machine learning techniques to solve the complex problem of using a machine to do the work of a senior processor and an expert underwriter. The Bottom Line: HELOC has come back as people seek alternative ways to access the equity in their homes. The rest of 2022 could be a record year for HELOCs, just as 2021 was a record year for refinancing. Understanding the dynamics of the home equity market can help mortgage lenders identify homeowners in the market for home equity. For more information on how next-gen solutions can help Fintech companies transform their businesses, visit here or mail us at [email protected]. FAQs – Tavant Solutions How does Tavant help lenders capitalize on HELOC opportunities during uncertain economic times?Tavant provides specialized HELOC platforms with real-time property valuation, flexible credit line management, and automated risk assessment capabilities. Their systems enable lenders to offer competitive HELOC products quickly, manage portfolio risk effectively, and provide borrowers with accessible credit during economic volatility. What HELOC-specific features does Tavant offer for turbulent market conditions?Tavant offers dynamic credit limit adjustments, real-time market monitoring, automated compliance management, and flexible repayment options within their HELOC platforms. These features help lenders manage risk while providing borrowers with needed financial flexibility during uncertain times. Why are HELOCs attractive during economic uncertainty?HELOCs are attractive during economic uncertainty because they provide flexible access to funds, typically offer lower interest rates than credit cards or personal loans, use home equity as collateral, and allow borrowers to access credit only when needed while paying interest only on amounts used. How do HELOCs work during turbulent economic times?During turbulent times, HELOCs provide a financial safety net by allowing homeowners to access their equity for emergencies, debt consolidation, or investment opportunities. Lenders may adjust credit limits based on current property values and market conditions to manage risk. What are the risks and benefits of HELOCs in uncertain markets?HELOC benefits include flexible access to funds, potential tax advantages, and lower interest rates. Risks include variable interest rates, potential property value fluctuations, the possibility of owing more than the home’s value, and the risk of foreclosure if payments cannot be made.
Cracking the Intelligent Automation Fintech Code
Financial services organizations operate in a dynamic and complex ecosystem where new threats and opportunities emerge. They are under pressure to automate processes, cut costs, and become more agile to remain competitive. Customers expect these organizations to provide hyper-personalized services in all places, consistently. Agile Fintech companies that bring niche services offer better customer intimacy than traditional financial services organizations. Today, businesses need to react quickly to market changes and customer expectations. Being nimble is critical at the moment. Unleashing the Power of People + Next-gen technology (RPA, Machine Learning, and AI) with Intelligent Automation Automation methods have gone hand in hand with the changing nature of work. RPA, artificial intelligence, and machine learning have the potential to make business processes more innovative and efficient. A recent survey by McKinsey reveals that companies that experimented with intelligent automation could automate up to 70% of the repetitive tasks that their employees were handling. Still, they could also see a 20–35 percent run-rate of cost efficiencies. AI collects data from multiple sources and feeds it to tools to enhance the value of their interactions. RPA adds value by automating structured, data-driven processes that previously required manual intervention. Each provides value on its own. Bringing the two together (i.e., IA) adds enormous value in developing solutions that use a technological knowledge base to modernize processes as well as interactions between applications. The resulting solutions are faster and more accurate, contributing to the four significant efficiencies: Better productivity: More efficient planning cycles can be achieved through the real-time integration of multiple sources of structured and unstructured data, automation of applications and processes, and decision-making and prediction. Increased precision: The combination of structured and unstructured data can ensure better decision-making; it also helps automate repetitive, manual processes and requires less human intervention, leading to more precise results. Cost savings: According to Deloitte, businesses anticipate an average cost reduction of 22% from intelligent automation. They realized, however, that organizations ramping up intelligent automation have already realized an average cost savings of 27% from their implementations thus far. Enhanced CX: Businesses that leverage digital technology can comprehend their customers’ needs, communicate more effectively, and produce higher-quality products. Final Thoughts Intelligent automation does not refer to a single technology. In its place, it indicates various sets of automation tools that can resolve complex problems. Intelligent automation does more than automate isolated processes; it also catalyzes the actual process and workflow transformation. The payoff can be pretty substantial in terms of increased productivity, streamlined processes, and exceptional customer service. Over the last decade, the evolution of RPA (robotic process automation) has propelled us to the forefront of workforce unification through people + intelligent automation. At this stage of development, digital robots not only automate back-office processes but also complement, augment, and interact with your human workforce via human-in-the-loop capabilities such as AI, machine learning, and optical character recognition. Thus, how can businesses move from basic RPA to enterprise intelligent automation while ensuring the long-term viability of their legacy systems? What’s Next? Reality check: There’s no time for “cookie-cutter” monotony Break it with Tavant’s Intelligent Process Automation Tavant’s consulting-driven approach to automation helps mortgage lenders, banks and real estate companies improve productivity and enhance customer experience with our deep automation and domain expertise. By combining the power of industry tools and accelerators, we drive organization-wide transformation through RPA, ML, and AI to solve your most important business challenges. Key steps on the journey include: A Phase of Discovery and Planning: We begin with a maturity assessment to develop a comprehensive digital blueprint of all process activities that align with your business priorities. A Quick Automation Assessment: A quick assessment can help you understand immediate automation priorities, cost-saving opportunities, and the best-integrated automation framework for your needs. Assess and Build: Organizations must evaluate various technology, architecture, security, and governance solutions to determine which options are available to automate. We can help you decide how to use it, which technologies to leverage, and how to ensure that it is widely used throughout your organization. Optimize and Manage: By establishing a new human/digital partnership, we can simplify, standardize, transform, automate, and optimize business processes. For more information on how intelligent automation can help Fintech companies transform their businesses, visit here or mail us at [email protected].
Why Cloud and Data Analytics go hand in hand?
As per Gartner, adoption of data and analytics will increase from 35% to 50% in 2023, driven by industry vertical and domain-specific augmented analytics solutions. By 2024, 75% of organizations will have deployed multiple data hubs to drive mission-critical data and analytics sharing and governance. The research also highlights that nearly 70% of enterprises will use cloud and cloud-based AI infrastructure to operationalize AI systems for their businesses over the next two years. Cloud adoption has significantly accelerated post-pandemic, with enterprises increasingly focusing on the digital transformation across their business functions. One of the critical drivers in cloud adoption is the onset of data-driven strategy across industries. Cloud has helped in the paradigm shift to implementing data and analytics solutions and fast-tracked the time to market for data analytics solutions. A recent survey by IDG Research and Tavant indicates that data analytics is a key focus area for organizations across industry verticals in the USA, where enterprises are looking at leveraging the cloud to implement data-driven systems. More than 80% of C-level survey respondents plan to leverage the cloud to drive enterprise data analytics. Thus, it is evident that cloud technology is pivotal in driving faster data analytics adoption, the emergence of next-gen SaaS products, and modern-day cCloud data platforms. Role of Cloud in Data Analytics: With the wide range of solutions focused on infrastructure and data analytics-specific services, the cloud has acted as a catalyst in driving the adoption of Data analytics. Today, Cloud Service Providers (CSPs) are accelerating the data analytics adoption with broadly two service offerings; Infrastructure services – The fundamental cloud Compute and Storage solutions help organizations implement custom solutions faster and address scalability challenges. The mere availability of computing and storage faster elasticity has enabled enterprises to adapt quickly. Modern data platforms also leveraged infrastructure services in providing cloud-agnostic services. Data Analytics services – CSPs are leading cloud providers to provide data-specific services to build Cloud-native data solutions. Examples are Hadoop on Cloud as PAAS – AWS EMR, Azure HDInsight, GCP Dataproc, and the related services to create a complete data solution. The CSPs will glue these cloud components together to build custom solutions for future enterprises. Cloud-enabled Data Analytics solutions As organizations embark on building complex data solutions, the cloud becomes an integral component of the data architecture. Understanding the various alternatives helps select the right technology based on business context. Below is the broad category of cloud-driven solutions. Cloud infrastructure-focused data solution The solution leverages cloud infrastructure services to deploy data analytics solutions faster. These solutions are most suited for companies that need to rehost existing data solutions from an on-premises environment to the cloud or build a custom solution from scratch. Examples include AWS S3/Azure ADLS/GCP cloud storage as the data lake and various computing services by AWS/Azure/GCP Cloud-specific data solutions These solutions leverage cloud-native data services to build data analytics solutions. The data services and pre-built integrations across different cloud services are helpful for enterprises and CSPs to co-create custom solutions faster with data privacy and security needs. Examples include EMR, Kinesis, S3, from AWS, HDInsight, ADLS, NoSQL databases, Stream Analytics from Azure, and Dataproc, Storage, NoSQL DBs, Pub/Sub from GCP. Cloud Datawarehouse Cloud-native Datawarehouse solutions by CSPs help to deploy enterprise-grade Datawarehouse faster. Examples include AWS Redshift, GCP BigQuery, and Azure Synapse analytics, which have pParallel processing, pre-built integrations for ingesting data, and AI/ML capabilities. Modern data platform on cloud -Modern Cloud-native data platforms like Databricks and Snowflake focus on building a single platform addressing the needs of Data Analytics. As cloud and data analytics drive the adoption of each other, it is imperative to understand the mutual dependence and leverage it while planning for cloud adoption or data analytics solutions within the organizations.
Is It Essential for Lenders and Banks to Embrace Quality Engineering to Achieve Speed and Agility?
Why is good quality engineering important in financial services? Lenders, banks, and insurance companies are increasingly replacing legacy systems and adopting improved technologies across the enterprise, which requires the highest quality engineering and software testing capabilities. Unsurprisingly, their development initiatives are centered on the need to improve efficiencies, add new functionality, and reduce operating costs. It may offer, develop, and bring products to market or incrementally replace existing platforms and solutions while minimizing any business disruption during major or minor release cycles. Quality Engineering must be part of any effective change program to proactively prevent software errors, misfires, malfunctions, and defects that can cause outages, negative client impacts, and regulatory fines. Today’s business demands are numerous and complicated. What do lenders and banks want? A faster time-to-market, including a shorter turnaround time for application rollouts and updates that can keep up with rapidly changing market trends. To reduce costs, as they face increasing pressure to reduce the cost of IT projects and seek intelligent alternatives to reduce project costs. To keep up with technological advancements and the demands of integrated applications that support multiple operating systems and devices. Application stability, which can significantly facilitate an increase in clients and support online exposure demands with zero application downtime. This is where Quality Engineering enters the picture! As stated, “Assurance neither improves nor guarantees quality. It is too late to assure. Quality, good or bad, is already present in the product. To truly meet your customers’ expectations, you must implement a quality engineering approach that instills quality at every stage of the SDLC”. Given the high risk of financial services, quality is a business-critical requirement. As a result, lenders and bankers must adopt a quality-first approach in their software development lifecycle. Quality Engineering entails QE involvement from the start of the SDLC so that quality-related processes run concurrently with development until the final release. This is undoubtedly impossible to accomplish manually, necessitating test automation. The shift-left strategy refers to moving QE to the early stages. However, shifting to the left is no longer sufficient in today’s constantly changing customer demands and volatile financial markets. Quality should be omnipresent, necessitating a shift-everywhere QE strategy. A shift everywhere strategy and a Quality Engineering approach result in an application that scores highly on all key parameters such as functionality, security, reliability, and performance, among others. As businesses look to automate more of their business operations through technology, a well-designed QE plan should include an in-depth and broad-based performance testing plan that identifies trouble spots, recommends solutions that can then be properly implemented, and provides continuous testing. With a shorter time to market, enterprises now have less time to test. What’s next? Tavant – An Absolute Commitment to Quality Engineering Tavant’s QE approach focuses on testing and combines industry best practices with our own methodologies and powerful proprietary tools to guide clients through an ever-changing development environment. Tavant’s Quality Engineering (QE) programs aim to improve the quality of software development and incremental release cycles while avoiding serious technology failures that could have a negative business and brand impact. Our QE experts use a quality management process to ensure that a product/service/platform meets all required specifications as well as all desired operational functionality. Our engineers adhere to a robust process-driven strategy that facilitates and defines specific design goals concerning product/platform/system development roadmaps. Our goal is to track and resolve all bugs, blockers, coding errors, and other issues that may arise and should be addressed before they have a negative business impact. Tavant’s Quality Engineering services are designed to address such challenges throughout the software development and delivery lifecycle. We use the CI/CD approach to ensure faster and higher-quality testing. Rather than relying solely on DevOps for iterative QE, Tavant advises customers on how to establish a dedicated QE strategy and focused action plan that seeks to mitigate and/or eliminate identified risks, enable compliance, and minimize costs. Financial quality engineering services and banks have used QE to test technology deployments for bugs and defects and measure them against internal business and security standards and regulatory mandates through rigorous and thorough performance testing. At the same time, this may satisfy many. Tavant fintech quality engineering services works differently and strives for excellence rather than just meeting minimum standards. We believe speed and accuracy go hand in hand. We appreciate thoroughness, accuracy, and identifying and resolving problems through a well-planned, phased, and executed testing and solution-driven schedule that includes a rigorous back-end testing component. We reimagine software testing for the age of disruption with a ready-to-use test automation platform and a suite of tools and accelerators. Through high-velocity automation, our team helps you spend less time on routine tasks while gaining more insights from data for greater innovation. We elevate testing to the next level by implementing quality engineering throughout the entire lifecycle, from code quality and pipeline quality gates to performance, resiliency, post-production coverage feedback, and everything in between. For more information, visit here or reach out to us at [email protected]. FAQs – Tavant Solutions How does Tavant implement quality engineering for lending institutions?Tavant employs comprehensive quality engineering including automated testing, continuous integration, performance monitoring, and security validation. Their approach ensures rapid deployment while maintaining high reliability and compliance standards. What quality engineering services does Tavant provide to achieve lending agility?Tavant offers test automation frameworks, DevOps implementation, quality assurance consulting, performance optimization, and reliability engineering services that enable faster time-to-market without compromising quality. What is quality engineering in financial services?Quality engineering in financial services encompasses automated testing, continuous quality monitoring, risk-based testing, performance optimization, and security validation to ensure reliable, compliant, and high-performing financial applications. Why do banks need to focus on speed and agility?Banks need speed and agility to compete with fintech companies, meet changing customer expectations, respond to market opportunities quickly, and adapt to regulatory changes in the rapidly evolving financial landscape. How can traditional banks become more agile?Banks can become more agile through cloud adoption, automation, DevOps practices, API-first architectures, continuous integration, and cultural transformation toward iterative development and customer-centric innovation.
Web 3.0 – A Game Changer for Advertisers
Advertising has been evolving by leaps and bounds over the last few decades. As a result of technological advancements, we are now witnessing the shift of advertising from traditional forms to digital avenues. While advertisers seek to increase conversions, consumers demand data ownership and transparent information usage. Web 3.0 and the metaverse have provided a solution to this long-standing demand, and they have the potential to be game changers for both advertisers and consumers. Revolutionary Web3 The current system, web 2.0, has many major flaws, such as the big tech controlling the internet with an iron fist, a lack of transparency, and the involvement of a plethora of intermediaries. The transition to Web3, the most recent version of the internet, will provide enormous benefits, with advertisers playing a significant role. Blockchain, the underlying technology of web 3.0, helps advertisers improve data transparency, eliminate intermediaries, and directly connect brands to their consumers while saving millions of dollars. International brands have already begun to adopt web3 and complementary technologies such as the metaverse by hosting events, sponsoring, and creating unique user experiences. In web3, the focus will shift from improved visibility to enhanced user experience and relevant messaging by giving advertisers complete control over their data and providing meaningful value to their users Advertising – Changing Dimensions Role of interoperability – Interoperability is an important concept in Web 3.0. The initial prototype of Web 3.0 is based on shared platform experiences. Users can carry their avatars and digital profiles across multiple applications and websites while maintaining a unified experience. With interoperability, advertisers would have unprecedented freedom to engage with potential customers. Metaverse real estates – Since its inception, metaverse real estates have experienced rapid growth. Platforms such as Decentraland and Sandbox have grown exponentially in months. As this trend continues, businesses will need to consider metaverse real estates essential to their advertising strategy. Soon, advertisers’ primary metric of campaign success will be metaverse traffic. Cross-platform collaborations – The ownership of digital rights has changed how consumers interact with segments such as gaming, entertainment, etc. Data is the next stage in this transformation. Customers can finally take control of their data and decide how it will be shared and used on the internet with Web3. A shift in digital tools – With Web 3.0 and metaverse, the tools used for advertisements are expected to evolve. Advertisements in virtual reality – VR has primarily remained a secluded medium for advertising. However, as users move away from text and video-based interactions, businesses should increase their focus on VR advertisements. In-game advertisements – The play-to-earn economy is an important part of the metaverse. Companies should explore 3D rendered advertisements within games by determining how to work on in-game ads without interfering with the customer experience. User-driven advertising – Because of the transparency of blockchain, a significant shift toward ethical marketing is required by obtaining explicit consent from users before using their data. This will allow users to receive a portion of ad revenue. User-driven sharing will enable businesses to reach their target audience without relying heavily on previous data collection models. Looking Ahead Though Web3 is still in its infancy, advertisers have already begun to see the metaverse as a profitable channel for engaging with audiences and marketing. Decentralization is fast emerging as the internet’s future. With the aggressive growth expected in Web3, advertisers are expected to explore newer ways to engage with modern audiences and capitalize on the opportunities in the Web 3.0 era.