Machine Learning in Lending Summit Recap and Key Highlights
Last Wednesday, September 27th, we at Tavant hosted the first ever Machine Learning in Lending Summit at the JW Marriott in San Francisco Union Square. This was an exclusive leadership summit – invites were extended to key executives in the mortgage and consumer lending industries. This one-day summit consisted of keynotes, workshops, a panel discussion, and interactive sessions that showcased the practical applications of Artificial Intelligence and Machine Learning in the mortgage industry. The summit began with a welcome address by our CEO, Sarvesh Mahesh. Next on the agenda was R.V. Guha, a renowned scientist, who spoke on accelerating digital transformation with AI and empirical modeling. He began his keynote by defining what exactly the buzz is around data science and the importance of empirical modeling. While analytic models have limitations, empirical modeling has had a lot of success in the past decade. He continued on to state that “datasets drive research” and deep dives into the varieties of data sets, available databases, current resources (i.e. Schema.org), and proposed future solutions (i.e. datacommons.org). Key takeaway: Empirical modeling is for complex systems what calculus is for classical engineering. This new class of models can handle complex phenomenon that has a significant social and behavioral component. The next speakers featured Manish Arya (CTO, Tavant) and Aseem Mital (Tavant Founder), who had an interactive session on Applications of Machine Learning in Lending and how these applications and concepts can be applied to the mortgage industry. Prasun Mishra (Senior Director, Tavant) and Harsha Naidu (Director, Tavant) led the Lending Club Workshop which demonstrated a general approach for creating decision models. Prasun and Harsha used publicly available Lending Club data and created a stepwise approach that used Machine Learning to develop a credit risk model and predict loan performance. They also introduced supervised learning techniques. Next up was an engaging panel discussion featuring Robert Carpenter (Principal in Technology, CoreLogic), Nick Stamos (CEO and Co-Founder, Sindeo), Brian Pearce (SVP, Wells Fargo), Ronald Olshausen (Managing Director, HedgeServe) and Gabe Minton (CIO, Guild Mortgage). The panel provided key insights into problems and challenges that businesses currently face with AI and Machine Learning in respective industries. The final session featured Mohammad Rashid (VP, Tavant) and Matthew Wood (Senior Director, Tavant) who discussed blockchain 101, applications and case studies, and how blockchain technology is disrupting industries globally. Key takeaway: Overview of the Tavant digital mortgage landscape, and how to disrupt the mortgage process and lifecycle. The summit concluded with a closing session presented by Hassan Rashid (CRO, Tavant). The summit was highly successful and attendees found the content thought-provoking and valuable. We wanted to express our concerns with how AI and Machine Learning were being applied in other industries at a rapid rate, but companies in the mortgage industry are falling behind by not utilizing the newest technologies. We wanted to demonstrate to senior leadership that it is now easier than ever to apply AI and Machine Learning in the mortgage industry. It is imperative for companies to apply this technology, accelerate innovation, and strengthen their competitive advantage. The summit concluded with innovative and disruptive ideas that senior business executives were able to take back to their respective organizations. Watch a recording of the live stream of our Machine Learning in Lending Summit here. We’re listening. Have something to say about this blog post? Share it with us on LinkedIn, Facebook, Instagram and Twitter. OR Please add your thoughts, ingenious analysis, and feedback in the comments section below. We look forward to hearing from you. FAQs – Tavant Solutions What machine learning insights did Tavant share at recent lending summits?Tavant presented breakthrough applications in predictive underwriting, automated document intelligence, real-time fraud detection, and adaptive risk modeling that are transforming lending operations and customer experiences. How does Tavant stay at the forefront of machine learning innovations in lending?Tavant invests heavily in R&D, participates in industry conferences, partners with academic institutions, and maintains innovation labs focused on emerging ML applications for financial services and lending automation. What are the latest machine learning trends in lending?Current trends include explainable AI for regulatory compliance, federated learning for privacy, automated model governance, real-time decisioning, and the integration of alternative data sources for more inclusive lending. How is machine learning changing credit scoring?Machine learning enables dynamic credit scoring using alternative data, real-time updates to creditworthiness, more accurate risk assessment, reduced bias in lending decisions, and personalized credit products. What machine learning applications are most valuable in lending?Most valuable applications include automated underwriting, fraud detection, customer segmentation, price optimization, default prediction, and document processing that significantly improve efficiency and accuracy.
Improving Buyer Experience through Customer Data
Gain more insights into the aftermarket space to improve how a customer feels – every time you send an offer, provide a service, or advertise a new product. A digital registration platform integrated with analytics can make an organization’s customer-experience strategies powerful. Organizations often lack one-on-one interactions with the most important stakeholder in their business — the customer. Businesses need to capture detailed customer expectations of the products they use. When businesses understand those expectations, they will understand the users’ experience and know what proportion are going to become brand ambassadors. Registering products after sale requires just a mobile device. Even without one, a simple online data-capture form links the organization to a host of information, which can be used to improve customer experience in the aftermarket. However, to add value throughout the product lifecycle, companies need to interact with customers, analyze the data, and determine what customers want and what they may need in the future. Then companies need to respond to that data and improve services and new products accordingly. I think the part about a mobile device is unnecessary. Why a Digital Platform? A digital platform cost effectively streamlines omnichannel communication. Using the data, you can inform customers of the latest mix of offers, insider information, warranty liabilities, and product-use tips — exactly how the customers prefer. This increases customers’ tendency to rely on one brand. Capabilities to integrate the product-registration process with analytics gives an organization the power to improve customer experience holistically. A multi-channel brand engagement model is the foundation for cross-selling and improving customer confidence and brand loyalty. Stressing Simplicity The importance of convenience can never be under-estimated in a customer-facing process. The registration, and all the activities thereafter, should be designed accordingly. A single digital platform at the OEM’s end that allows the customer to interact with the company is increasingly being considered. After the sale, a customer should be able to register the product by QR code or bar-code scan, social media plug-ins, a mobile app, or a website. These channels provide the company with a data set, which includes valuable personal information, feedback, and customized tips on benefiting from the product. The communication from the OEM’s end may differ depending on age, location, product details, etc. Analytics and Automation Software capabilities to use the information gathered are vital. Analytics helps an organization use registration-level information to deliver improvements and customized information. From identifying issues customers may have to cost-effective changes in product design, analytics plays an instrumental role in converting data to insight-driven actions. With simple dashboards supported by back-end intelligence, a product-registration platform, integrated into the rest of your technology setup, improves brand image. The AI-automated, customer-facing activities align services and products to market preferences. Organizations need to ensure simplicity in the customer’s registration platform interface. The challenge with that is striking a balance between respecting the customer’s time and maximizing the feed for analytics. The value generated each time is directly proportional to the depth and accuracy of data discovered. Interactive data also plays a vital role. With data backing your organization, you can maximize the engagement through the right content and improve insights in the long run.
Chatbots and Their Role in Consumer Lending and Warranty
I joined Tavant in the Mobile Team and soon got an opportunity to get my hands dirty on Chatbots. As we all know, Tavant is a leader in providing services in Consumer Lending and Warranty, I decided to pursue a chatbot for each of these use cases. I plan this series over 3 parts, where towards the end we will have a fully functional chatbot Mobile app. Let me first define a Chatbot. How do they work? How do I build my own ChatBot? How can I use chatbots to help my clients? I’m sure these questions are running through your mind since chatbots have gained popularity and occupy a niche space in user engagement. You might have already interacted with chatbots on social media and not realized it! Now is the perfect time to delve into this exciting world of chatbots. So what is ChatBot? A ChatBot is a program that simulates human conversation or chat through Artificial Intelligence. Typically, a chatbot communicates with a real person to provide the services like customer care agent, e-Commerce or any Hotel/Cab booking, etc. The chat interface can either be Facebook Messenger, Twitter, slack, or even your own custom chat messenger. Let’s see some examples of ChatBots that are currently available. Example: 1. Book a cab: Want to book a cab? Don’t have a cab booking application on your phone? No problem! Uber has recently launched their Facebook chatbot, which helps you book your Uber cab without installing their app. Experience the chat by clicking here. 2. Ordering a pizza: Hungry? Want to order a delicious pizza? Just use your messenger to chat with a Dominos bot. You can place an order, track your order, and cancel your order by just chatting with a bot. https://vimeo.com/179171202 3. Weather application: These bots are designed to get the weather report of your location. They can also suggest whether you should bring your umbrella before you leave your house. https://www.youtube.com/watch?v=m5ViHWRo9KU 4. News bots: These bots allow you to be updated on your News. You can subscribe to your favorite news topics or you can ask for the latest headlines on a specific topic. https://www.youtube.com/watch?v=8iwxWU-8cuM 5. HDFC Bank OnChat: This is a facebook messenger bot, which helps you recharge your prepaid and postpaid bills, book event tickets, book cabs, etc. https://www.youtube.com/watch?v=6bnKhqZmdsw You should definitely do some research to get an idea of how chatbots are used by companies to provide better customer service. Why chatbots? You must be thinking “Why is this sudden popularity of chatbots in an enterprise?”. Let me explain… According to “Chatbots magazine”—“This is for the first time ever people are using messenger apps more than social media apps. So logically, if you want to build a business online, you want to build where the people are. That place is now inside the messenger apps. This is why chatbots are such a big deal. It’s potentially a huge business opportunity for anyone willing to jump headfirst and build something people want.” So now that you understood the importance of chatbots, the next question which comes to your mind would be “How does a chatbot respond to your message and does the business for you?” To understand their functioning better, let us first see the different types of chatbots out there. Well there are 2 types of chatbots. 1. Chatbot that functions based on a set of rules: This type is limited to certain transactions. It can respond to only a few specific commands based on a decision tree, which a developer may have built. It has limited to no understanding of natural language and contextual meaning. If you say something vague, it doesn’t understand what it is. 2. Chatbot that functions based on Machine Learning: This bot has an artificial brain called as artificial intelligence. You don’t have to be specific. It also understands the natural language along with commands. This bot continuously gets smarter with previous conversations. Bots are created with a specific business purpose in mind. For example, an online store is likely to create a chatbot, which helps you purchase something. UPI apps like Paytm is likely to create a bot for bills payment, mobile recharge, etc. Artificial intelligence: The next riddle you must be thinking over is if bots use artificial intelligence to make them work, isn’t it hard to do so? Do I have to be perfect in AI? The answer is NO, you don’t have to be an expert in AI. Now, we have many readily available AI solutions that are backed by giants like Google, Facebook, IBM to name a few. Things to do for building your first chatbot Figure out what business problem you are going to solve with your chatbot. Identify the right messenger platform(s) like Facebook, Twitter, or design your own interface in an existing mobile app. Set up a server to run your bot. Choose a service to build your bot. Time to see an example of a Chabot in Warranty Management System I went about writing a chat interface in one of our Mobile App for Warranty and was pleased by the final outcome. The chat feature in my mobile app got the user engaged longer than my normal screen flows to complete the same task. Let’s consider a use case where the mobile app has to provide a feature to the user for creating a service request, collect feedback for the last service and allow the user to register complaints and suggestions. Users can also request information about their next service appointment. Also, I built a service to provide guidelines/help from an agent, etc. You can do all this by chatting with a bot. It is an easy, automated, secure way of executing these business services rather than the old traditional way. It’s cool. Isn’t it? I have posted the demo for the same video here Now let’s see the example of Consumer Lending application. The user can ask your assistant bot about home loan services and its eligibility criteria. He can also request for a home loan. And
The Countdown is On for UCD and HMDA
Regulations are constantly changing in the mortgage industry. Lenders are under continuous pressure to meet fast approaching deadlines on UCD and HMDA. The Uniform Closing Dataset (UCD) is a standard industry dataset enabling information on the CFPB’s Closing Disclosure to be communicated electronically. The first deadline of 25 September 2017 mandates lenders to deliver borrower data and Closing Disclosure in the UCD file. UCD improves loan quality through increased data accuracy and consistency. This is of interest to the GSEs as it enhances the loan’s eligibility for sale in secondary markets.The year 2018 brings updates to the HMDA. The new HMDA rule requires over 48 data points to be collected, recorded and reported. This includes multiple new data points and a few modified from the previous rule. New fields include credit scores, CLTV ratio, DTI ratio, detailed demographic data etc. The CFPB asserts that the changes improve the quality and type of data reported by financial institutions leading to greater transparency. The updated regulations bring a new set of challenges to lenders. Investments in technology systems and processes can potentially increase the ever-rising loan origination cost. Data privacy and security is another concern. With the increased number of data fields, protecting sensitive borrower information is a priority. Additional data can also be used in fair lending claims thereby increasing litigations risks and costs. Since 2008, the mortgage industry has been taking giant strides in improving data reporting and compliance standards. TRID rule impacted the industry at almost every point along the transaction, and UCD/ HMDA will change the way data is collected, recorded, reported and delivered.Over the years, Tavant’s mortgage expertise has helped lenders implement regulatory changes with cutting edge technologies. In 2015, we helped multiple lenders achieve TRID compliance ahead of schedule. In 2017, we are doing the same with HMDA and UCD. It’s time to achieve Accelerated Compliance with Tavant Testing. The countdown is on!To learn more about our testing solution please visit: UCD/HMDA Compliance Testing by Tavant FAQs – Tavant Solutions How does Tavant help lenders prepare for UCD and HMDA compliance deadlines?Tavant provides automated compliance management systems with built-in UCD (URLA Conversion Deadline) and HMDA (Home Mortgage Disclosure Act) reporting capabilities. Their platforms automatically generate required reports, track compliance metrics, and provide audit trails to ensure lenders meet regulatory deadlines and requirements. What specific UCD and HMDA compliance features does Tavant offer?Tavant offers automated URLA form generation, HMDA data collection and reporting, compliance dashboard monitoring, exception tracking, and regulatory change management capabilities. Their system ensures accurate data capture, timely report submission, and comprehensive documentation for regulatory examinations. What are UCD and HMDA requirements for mortgage lenders?UCD (URLA Conversion Deadline) requires mortgage lenders to use the redesigned Uniform Residential Loan Application (URLA) form. HMDA (Home Mortgage Disclosure Act) requires lenders to collect and report detailed mortgage lending data including borrower demographics, loan terms, and decision outcomes for regulatory analysis. What are the penalties for UCD and HMDA non-compliance?Non-compliance with UCD and HMDA requirements can result in regulatory fines, enforcement actions, reputation damage, and operational restrictions. Penalties vary based on the severity and duration of non-compliance, with potential costs ranging from thousands to millions of dollars. How can mortgage lenders ensure UCD and HMDA compliance?Mortgage lenders can ensure compliance by implementing automated data collection systems, regular staff training, internal audit processes, compliance monitoring tools, and working with experienced compliance technology providers who understand current regulatory requirements and changes.
Incur Lower Warranty Cost While Generating Greater Revenue
In dealing with warranty packages, organizations around the globe are known to suffer leakage, of thousands of dollars, due to unoptimized claim-processing loopholes. It is advisable to improve how you administer and track all your warranty claims holistically, leaving zero room for false claims. To be able to improve profits, a closed-loop warranty system is necessary. Customer satisfaction is the key. Every organization strives for it in innovative ways. But the best hassle-free claim processing experience customers can get when you have a robust warranty-operations controlling system. Rules-based technology Most of the time, organizations tend to bleed valuable revenue through fraudulent claims, as they have limited control over warranty operations with rigid and worn-out systems. Therefore, it is advisable to implement IT for it to function according to business rules and organization policies accurately. A typical claim process starts from submission, pre-approval, claim evaluation, final approval, and disbursement. The entire cycle needs to be automated along with the incorporation of an EWS (early warning system) to capture real-time cost drivers. Field-asset tracking and management As business dynamics have grown complex, organizations need a system to facilitate field-asset tracking and management better. It is the most important part of warranty management, as it keeps account of the replaceable parts at any given point of time. That, in turn, helps the organization to make provisions in the accounting books to allocate funds and other resources optimally. Orchestration with real-time data For businesses to reap maximum benefit from warranty software, they need to implement a technology which perfectly syncs dealers, service centers, suppliers, service providers, and of course, the OEM itself. Orchestration of the sort makes it possible to share real-time data on business activities across global locations and assess the associated warranty liabilities. An integrated data-driven workflow is essential to limit warranty spend and enhance customer satisfaction. A cut in the warranty spend, in turn, can release more funds, which a smart organization may use to improve product quality through investments in expertise and state-of-the-art R&D facilities. Final thoughts Organizations can use automated analytics and reports to re-evaluate their spend analytics from time to time. It will help them create room for extra savings. After all, the ability to improve aftermarket services in the manufacturing sector depends on how well you optimize other costs. Claim processing itself can be cumbersome and incur massive overheads, with tons of unmanageable paperwork and countless phone calls. Such processes are nothing but revenue killers, which can be streamlined to help focus on productive operations. It is important to stop possessing expensive workforce and spend less time on processes—an attainable goal for manufacturers, which is fast becoming a necessity at all altitudes of the industry.
Extended Warranties: A Retrospection
In today’s competitive business environment, organizations are concentrating not just on sales but the aftermarket promises – made in the form of extended warranties. While people have been reading the abundant material, written by skeptics, on why extended warranties might do more harm than good, efficient contract management has proved to be the key to retaining and expanding customer bases for many manufacturers. There is a growing need for organizations to imbibe technological innovation into their culture. The current drive is to automatically manage rules for payouts, contact deadlines, rates, replaceable spares, and so forth. A better customer management process can only be achieved with an end-to-end support system in place. What customers like Customers relentlessly crave for more – every time and are willing to spread the good words about your brand if you make them feel that warranty claims are a cakewalk. Organizations, thus, use intelligence-driven claim-submission modules for customers to avoid unnecessary interactions. Extended warranty holds the key to OEM profitability, and in the long run, helps achieve deeper market penetration with smart, dynamic pricing. It is a general observation that a field asset may not be replaced entirely, especially if the spare is not included in the warranty. That is where you can create the scope for a customer to benefit from the power of dynamic pricing while offering extended warranty. You can offer to replace the spare for a one-time payment, which optimally covers the cost and doesn’t create a burden on any of the sides of the business. Thus, extended warranty helps attract more customers and improves ROI, while increasing your aftermarket profitability. Offering what customers prefer With artificial intelligence and machine learning enabled features like new quote management, OEMs and dealers can reach out to customers with new offers and promotions. Preparation of such offers can be a daunting task for sales teams, but with smart technology, they can progress efficiently. In this way, customers can benefit from real-time pre-approved discounts, pricing updates, the latest products and services, and more. Organizations are looking for platforms which can deliver such information in a customized way and increase the real value offered to customers. Extended warranty a common practice Decentralized operations of extended warranty have reaped benefits for organizations as well as customers. It is standard practice these days that dealers or distributors offer extended warranties in addition to standard warranties provided by OEMs. This approach creates value and captures market share by extending goodwill toward the market. And, finally It is imperative for OEMs to monitor their internal policies continuously and maintain their command over operations. That would prevent leakage through fraudulent claims and add to customer delight. Organizations require a flexible technology arm, which can modify, cancel, and alter contracts as per client demands, but in line with the organization culture. Get to know more about ideas and thoughts from a team that is passionate about delivering artificial intelligence and machine learning solutions that impact customers’ core businesses. Have something to say about this blog post? Share it with us on LinkedIn, Facebook, Instagram and Twitter. Meet our AfterMarket experts at Warranty Chain Management conference, WCM 2018 in San Diego from March 6-8, Booth 11.
HVAC Profitability: Defining Destiny
HVAC users are spread across the globe, living in diverse climates with increased maintenance requirements. The service contract for each machine often excludes vital parts, and that can be a cause for great customer grievance especially before certain seasons. Service charges also ply, as manufacturers are unable to provide free labor to their sizeable markets. As in many other sectors, the HVAC aftermarket can feel burdensome, leaving little scope for CXOs to launch new offers and improve services. Need of the hour HVAC manufacturers need to plan for improving aftermarket satisfaction at a competitive cost meticulously. Predicting service requirements, utilizing resources cost effectively, and finding better techniques to improve product life are essential for that purpose. It can lead to long-term advantages, as more customers are likely to buy from a manufacturer that has a good reputation for its aftermarket services. The good news HVAC manufacturers need not offer free services to the aftermarket but should strive to provide lower costs and better outcomes than their competitors. It requires streamlining the workflow for every HVAC maintenance date in the calendar through early preparation. Customer satisfaction Customers expect maintenance services to lead to lower electricity bills, better durability, improved performance, and above all – peace of mind. Using historical data related to services, you can identify frequent problems, and their root causes to improve future maintenance. It is also important to have seamless data connectivity over a shared platform in your value chain so that you can help prepare your suppliers and service teams well in advance of scheduled maintenance. Customers also want transparency during the service and around the year. A mobile app with customized interaction can live up to their expectations. Value-chain satisfaction As a result of optimizing the workflow based on data-driven analytics, you can ensure a less stressed-out workforce. You can acquire better leads for equipment and accessories by looking at intuitive dashboards conveying and predicting the requirements, based on real-time data, including everything from weather patterns to customer budgets. Staying prepared for service deployment also lets you offer flexible work hours. Social impact The HVAC sector has a tremendous opportunity to make a difference to the global energy spend. While the primary focus will always be on more profits, what matters is the path they choose to achieve it. Service and product design improvements, to control energy spend, can be carried out based on service history. All you need is a technology to convert those huge piles of data into insights for engineers. Sustainable growth will be the result of competitive aftermarket services and how you use the data generated there. If your database has the relevant details, technology can continuously give you the right insights to make your products more reliable, improve savings during services, and market the right offers to the right people cost effectively.
Introduction to Precision Agriculture Technology
Humankind has witnessed great progress, first with the industrial revolution, healthcare, information technology, followed by biotechnology, and more recently the big data revolution. Increased life expectancy, growing population and shrinking arable land have contributed to mounting pressure on traditional agriculture (and somewhat led to dispelling the agrarian myth). The adoption of technology and extensive potential application of information technology to agriculture has led to the evolution of agriculture into Precision Agriculture. Precision Agriculture may be defined as a set of technologies that help farmers to adopt farm operations to manage field’s variability. The goal is to optimize yield (having better nutrient content) and maximize return on investment. Often Precision Agriculture involves satellite farming or site specific crop management based on observing, measuring, and responding to inter and intra field variability in crops. Steps in Precision Agriculture: The Precision Agriculture cycle can be considered to consist of the following steps or processes: Gather (Data Acquisition) Analyze (Processing the data and transform it into relevant analyzable information) Decide (Analysis of this data for decision making, sometimes via the agronomic model of utilization) Execute (Implementation/Adaptation) Approaches in Precision Agriculture: Broadly, Precision Agriculture can be practiced in either a Predictive Approach or a Control Approach. The Predictive Approach is when practices are adapted prior to start of the season. The predictive approach steps can be categorized as: 1. Gather—Use historical data, such as weather data, soil data, crop status during a period; as the starting inputs. 2. Analyze—Characterize the agro-climatic context, define management zones. 3. Decide—Adjust the crop inputs, such as seeds and fertilizer source. 4. Execute —Vary the sowing density of seeds; vary the Nitrogen application within the fields. The Control Approach is when adjustments are made during the season with an aim of optimizing the yield by reducing/optimizing the in-season requirements. The steps in control approach can be: 1. Gather—Monitor crop growth conditions during the cycle. 2. Analyze —Assess current intra-field variability. 3. Decide—Adjust the crop inputs to crop needs. 4. Execute —Vary the Nitrogen application and chemical application within the field. Tools to Gather Data Precision Agriculture adapts multiple technologies for advancement and betterment of agricultural practices. The tools for gathering the data that can then be analyzed for Precision Agriculture applications are as follows: – GPS to geo-localize the field boundaries, to geo-tag field observations – Sampling (Plant tissue sampling, Soil sampling [texture and nutrients levels analysis]) – Hand sensors and In-vehicle sensors (proxy detection) of crop status (biomass) – Aerial/satellite remote sensing of crop status (biomass, growth anomaly) – Combine (Yield monitoring) Tools to Analyze Data Based on the approach and the type of data gathered for the purpose of Precision Agriculture, processing of the data and transformation into relevant information can be done with the help of information technology and big data processing tools. Tools to Decide On the basis of the inputs from analysis step various models for decision making can be applied. For example, an averaging out approach may aim at averaging the yield throughout the field by reducing/controlling the field variability, this can be achieved by applying or pointing more resources, to regions where the growth lags behind the average field growth. The opposite approach would be to direct more resources (water, fertilizer, chemicals) to regions which already show better growth/performance compared to the field average. Tools to Execute Once the decision has been taken, various tools that can be adapted to meet the goals can be summarized as below. This can be done with the help of tractor combines, robotics or manual intervention. What can be adjusted: Inputs Dose – Seeds – Fertilizers – Chemicals – Irrigation Field Operations (time, fuel) – Tillage – Planting – Fertilizing – Spraying
Being an SFDC Tester
Salesforce is a very hot topic now-a-days in the market. It is a really refreshing change with clean and spontaneous user interface. Testing plays a key role for any application or software, as proper testing of application increases the quality. Typically, salesforce testing of apex classes and triggers is done by the developers themselves as it is necessary to write the test classes (for apex classes and triggers) to move the code from sandbox to production. Developers must ensure that their code coverage is minimum 75%. But, the functional testing should be done by the QA team to strengthen the quality of application. A lot of things can be done in salesforce via point and click administration which include automating the tasks like – automatically creating the tasks, making the field updates and sending the emails. This makes salesforce so interesting that a tester feels that he is working like a developer. What is the role of QA Team? Understanding the Business Requirement Document. Brainstorming sessions for functional understanding by the QA team members. Configuring and setting up of data. Assumption before configuration and data setup:The QA team has basic knowledge and role in salesforce comprises of: Creation of Accounts Creation of Contacts to relate with Accounts Enabling created contacts as External Users Assigning Product licenses to External Users Creation of Internal Users Assigning SFDC and TWOD (Tavant Warranty on Demand) Product licenses to Internal and External Users If we are using Public groups and queues in project, then once users are created, assigning those users to respective queues and public groups. Checking all page layouts All related lists of detail pages All the columns in the related list Creation of test data to perform testing. Working closely with the development team to design, build and test the application Providing the direction for system enhancement and defect fixes Providing the new ideas and information Prioritising and estimating the critical deadlines across the project Providing detailed documentation to business and developer team Organising the training session/demos for the customers It is not always true that a QA must do the configurations. If you don’t know the configuration part, you need not worry. Any one member of your team can do the configurations who is having salesforce’s basic knowledge. You just need to set up your data and perform testing. Testing in Salesforce Testing in salesforce includes the following features: Manual Testing in Salesforce is performed by the QA team which includes happy path testing, functional testing, integration testing, regression testing and system testing Automation Testing in Salesforce can be done by any of these tools available in the market—Provar, AutoRabit, AssureClick, Selenium and QTP. Selenium is the best choice as it is the open source tool. Use the Selenium web driver for automating the browser. Use eclipse for running the selenium code Functional flows report based on status of test cases, where testers are required to create the functional flows to understand the functionality of application Process builders to check the behaviour of the system, by giving different entry and rule criteria Workflows to check the functionality of time based events The few challenges that we faced during the testing of salesforce application include: Testing of Visualforce pages through automation. The issue lies in creating field locators reliably on a page. Salesforce will generate the Ids at runtime which means any change to our APEX code, leads to the change of field locators based on Ids which need constant maintenance Writing test cases with different roles and mentioning the settings Some of the standard functionalities although not in use, can’t be removed GUI tests don’t work when we switch the test environment. Automated tests need to work in all our test environments. Field Locators are how you automate tests, find the field or button on a page. There is an issue creating field locators for the Salesforce screens as some field IDs differ between Organisations. Last but not the least, the most important thing is to understand the Salesforce administration without fail. The beauty of Salesforce lies in its success community. Community is a great way to share the information and collaborate with the people outside your company. There is a help guide which is written by the salesforce admins and developers. One of the biggest advantage of Salesforce is that you can perform testing any time. For this, you don’t need any VPN access. You just need a web browser with a reliable internet connection. Just sitting at your home, you can do testing. Salesforce1 Mobile application is also available which is a better way to experience Salesforce using your mobile. Cited below are few links to study the Salesforce Concepts: https://developer.salesforce.com/trailhead/en http://www.djmlab.com/moodle/ -> For salesforce admin 201 certification. Salesforce, Making Life Easy……………
Solving the Problem of Inefficient Handling of Goods Return with Reverse Logistics
Have you felt that overlooking reverse logistics puts your organization behind others who master the discipline? If yes, it is not you alone, as there are many organizations yet to decide that reverse logistic is a strategic concern. However, it involves adopting the most efficient way of dealing with the process. Reverse logistics is the practice of efficient transportation of finished products from their destinations back to their origin to capture residual value (or salvage value). Manufacturers want to retrieve defective products efficiently from their valuable customers, and IT solutions are a definitive boost in that context. By improving the process, manufacturers can save costs and speed up their service to ultimately promote a positive brand image. It also helps the marketing aspect of business significantly. How large organizations tackle typical challenges To pursue the fresh stock, companies have started focusing on clearing old inventory. However, to do so, there are several hindrances for enterprises. Due to huge sales volumes and extensive customer bases, organizations face the problem of many unidentified and unauthorized returns. Warranty management software establishes total control over such processes by maintaining unique product identification numbers and tracking mechanisms. As all the claims are managed automatically through software, there is no scope for unauthorized system inventory movement without a laid down protocol being followed. Most of the time, organizations are unable to write off a significant amount of returned inventory held in their warehouses. The claim processing rate is far lower than the inward-inventory movement rate, which results from a lack of return agreements with retailers. The latest warranty software are a step ahead in this aspect, as they manage the return policies and protocols laid down right from the beginning of product life cycle. Software capabilities Warranty systems come with cross-functional integration capacity and minimize the claim-processing time, helping improve customer confidence. With high-level integration, the collection of goods from customers can be managed automatically. The software can be synchronized with third-party logistics providers (3PLs). As soon as a claim is processed, an automated intimation is sent to initiate the collection sequence. After the inventory arrives at the organization premises, it is accounted for automatically against a goods receipt note (GRN), leaving no gap for fraudulent claims. With traceability to this extent, organizations can extract maximum value from salvage of the returned goods in parallel to a hassle-free operation. Companies can also re-engineer and reintroduce the product back to the market and derive profit. Meet Tavant warranty experts at Booth #3 at 13th Annual Warranty Chain Management Conference (WCM) on Mar 7th-9th, 2017 in Tuscon, AZ