Author: konsultera

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AI

How is AI Revolutionizing the Insurance Landscape?

With so many real-world applications, AI has become a powerful medium for insurers to adapt to the ever-changing customer expectations and standards. AI-driven personalization could allow insurers to design Insurance products that are tailored to each consumer’s unique situation. Insurers can mine data from connected systems and adjust their rates on a case-by-case basis based on a customer’s unique situation. A new generation of AI-powered insurtechs is rapidly emerging. The insurance landscape is still in its early days of AI integration, but more companies are already trying it out and anticipating the next wave of technological development. 

Here are some quick benefits of incorporating AI in insurance:

Empowering Sales Forces and Identifying New Leads

Sales force enablement in insurance through AI and ML has been a buzzword in recent years. As customer expectations change, AI and ML solutions have become increasingly important to improve sales performance. Such a system would harness a company’s collective knowledge, identify the best customer to target, record agents on calls, analyze transcriptions and learn from each call. Then, it would be able to provide agents with the most current information to maximize their sales performance. 

In addition to enabling the sales process, AI can also identify new leads by using a prospect’s social media footprint and prioritizing them by relevance. Using AI to help sales reps increase revenue will free up time that can be used for inputting documentation or mining existing accounts. Sales force enablement solutions can significantly streamline marketing and sales processes.  

Automating Decision-Making and Underwriting Procedures  

AI and ML can improve the decision-making process of insurance companies through automated processes. These algorithms are designed to analyze objective data and produce more accurate decisions than human underwriters by classifying identical data. Furthermore, these algorithms can be trained to draw insights from historical data and recommend coverage options based on them.  

AI-driven underwriting systems can integrate with the entire insurance value chain. The insights from cross-platform visibility can open up new cross-sell opportunities, while the insights from centralized data lakes empower underwriters to approach customers with personalized insurance coverage. AI-driven systems can be trained to analyze the customer’s journey and provide the right kind of coverage for the right customer.  

Offering Claims Judgment to Adjudicate Better 

AI is already being used in insurance claims adjudication, with some insurers leveraging AI and ML in their processes. AI can proceed to mine data from electronic health records, access medical files automatically, and automatically calculate pay-outs before forwarding them to a human agent for approval. For e.g., in Health Insurance, AI-enabled claims adjudication can automate pre-authorization workflows and provide current analytic reports in a fraction of the time it takes humans. Eventually, AI can be trained to predict diseases and develop personalized treatments.  

AI and ML own the potential to drastically improve the claims adjudication process in insurance. Insurers can limit the number of claims that are out of the ordinary, allowing for less manual processing. Furthermore, AI augments human intelligence and learns from past data. This means that fewer claims go through the administrative staff, increasing productivity. This technology will make insurance claims adjudication easier for insurers and save them time and money. AI-based claims adjudication is an area that has seen a significant amount of development. Insurers have taken the lead in adopting AI, ML, and robotic process automation, and Attributum’s capabilities include all of the above and more. The adoption of AI by insurers is a sign that they’re aiming to improve productivity in their processes and create a better customer experience. 

Facilitating Seamless Documentation and Efficient Operations 

AI in insurance can identify and extract data from various sources, including handwritten documents. ML bots can identify key data points in supporting documents and translate them into structured data for updating. As the insurance industry undergoes significant pressure post-pandemic, these technologies will give insurers a competitive advantage over their rivals. Besides being excellent tools to improve operational efficiency, AI and ML have a wide variety of practical applications.

Detecting Fraudulent Activities and False Profiles 

AI can help insurers detect potential perils and make quick decisions. It can detect patterns and flag potential fraud in insurance applications and claims. AI chatbots can also flag new policies and warn customers of potential risks. AI can help insurers prevent insurance fraud by spotting patterns in consumer behavior and flagging them as higher risk. ML and AI are rapidly becoming indispensable parts of insurance documentation, and carriers should invest in the right talent to make it work in the future.

The AI-driven technology that enables insurers to create a unique risk profile of an individual will help reduce onboarding costs, speed up the process, and improve customer satisfaction. Insurance companies should prioritize customer acquisition to keep up with the competition. AI and ML will allow them to do all of this. So, if you’re an insurance company, don’t wait! Get ahead of the ordinary curve by opting for this technology today.

The Takeaway

As AI continues to evolve, insurers must invest in the foundational technology that will allow them to fully benefit from the new AI capabilities. The use of big data analytics is at the heart of AI, but insurers must take steps to secure their data and make it available. While some insurers have made the leap and are born digital, others still have inflexible legacy systems that hinder the use of AI. The future of insurance AI is bright, but insurers must take the necessary steps to prepare themselves. 

If you are looking for the right and adaptable platform to incorporate AI in your insurance operations, try PIVOT from Attributum, powered by Konsultera’s partnership, and streamline your hefty day-to-day procedures.

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Document-Digitization_Blog_Banner
Categories
Uncategorized

An Insight into Konsultera’s Intelligent Document Digitization Platform – MYSTiQUE 

One of the biggest challenges enterprises face is handling document digitization. Handling paper documents is time-consuming, repetitive, and error-prone. While AI and Robotic Process Automation have made it possible to handle documents automatically, enterprises still struggle to eliminate manual processes. Invoice processing and procurement-to-pay processes are two of the most common examples of business processes that involve documents. With an intelligence-powered document digitization solution, these processes can be automated and handled with a minimum of human error.

Incorporating Konsultera’s intelligent document capture platform, MYSTiQUE into your workflow can make a huge difference. Our modern intelligent platform can process semi or unstructured documents to extract relevant information. MYSTiQUE’s advanced technologies use a pattern-matching tool to determine which information should be extracted from paper documents. These technologies are more accurate than ever, thanks to our recent improvements in processing capabilities. In addition, our document digitization platform can handle a wide variety of formats, such as excel files, texts, PDFs, and images, making them suitable for a variety of different applications.

An Insight into the Functioning of MYSTiQUE as a Platform

While focusing on implementing an effective document digitization process, we realized that most of the systems rely on OCR (Optical Character Recognition) technique. This technique digitizes the documents, but it doesn’t fulfill the purpose of the document digitization process, i.e., easy extraction of files. While extracting some files can be easy, finding some other files can be tricky, which need specific sorting as per time, number, or any other attribute. This logical extraction is not possible with OCR alone.

Thus, we fixed the goal of our document digitization platform and created a strategy around our aim to offer absolute digitization and extraction so that the whole process can be completely automated and soothed. To do the same, we use AI Orchestration as a Service through MYSTiQUE.

To make MYSTiQUE help companies get ready to go digital, we incorporated Intelligent Process Automation (IPA). This technology allows them to access information from any type of document. Once digital, these records can be searched using a keyword. This means fewer resources are needed to process the data. The platform also allows businesses to use more advanced search methods to discover data, such as sales figures and customer profiles.

Here’s the step-by-step process that we follow while digitizing a document through MYSTiQUE’s intelligent platform:

  • Receptor
    The receptor is the first component of the platform in which files in any format are received and processed further for predictive analytics. It can process any type of data, be it images, documents, or excel spreadsheets.
  • Preceptor
    After the input of source data, the process of digitization begins. Preceptor comprises pre-trained ML models, which makes custom models faster. This pre-processing unit helps in improving the accuracy of the process while labeling, model training, and re-calibrating the data.
  • Endeavor
    Now data proceeds to Endeavor, which is powered by OCR (Optical Character Recognition) and IPA (Intelligent Process Automation). It consumes several ML models to establish a customized workflow for business requirements. While scanning the data thoroughly, this step introduces intelligence-enabled operations to make data extraction more effective, dynamic, and logical.
  • Enactor
    This component enables efficient extraction using techniques like RPA, AI Chatbots, HyperAutomation, Rest API, Smart assistant interface (Alexa, Google Assistant), Data Visualization using Data Lakes, Big Data Ecosystems, Large Scale Search and Match. In this step, the data that is digitized is extracted seamlessly as per the requirements of businesses and individuals.

How is MYSTiQUE Taking Document Digitization to the Next Level by Offering AI Orchestration as a Service?

Our intelligent document digitization can kick off manual processes and workflows, such as processing invoices and customer queries. By linking ad-hoc processes to business apps, an AI-enabled document digitization platform can provide significant benefits. In addition to converting documents into digital formats, AI and machine learning can liberate business data embedded in documents. As a result, our MYSTiQUE is scalable, cost-effective, and capable of delivering high levels of accuracy.

1. Increased Throughput: Analog documents contain structured, semi-structured, and unstructured information. By automating these documents, we can improve throughput, increase accuracy, and promote enterprise efficiency. To begin automating processes, organizations must identify the right processes to pilot. Quick wins are important because they free up capital and accelerate adoption throughout the organization. Top-tier organizations apply a bottom-up opportunity estimate methodology, and processes for intaking structured documents are typically the first to be automated.

2. Saved Time & Efforts: Government agencies handle huge volumes of data, including sensitive documents. The government alone employs many people, and processing information by hand can take a toll on workers and result in data entry errors and long nights. Intelligent document processing has enabled forward-thinking government agencies to jumpstart their digital transformations. Whether you are a small business, large enterprise, or nonprofit, Document digitization using IPA can automate processes and save you time and money.

3. Reduced Human Error: Intelligent document digitization combines AI and machine learning technologies to transform manual documents into digital data. It enables companies to extract valuable information from documents. Automation is the key to increasing efficiency and profitability. Intelligent document digitization makes it easy to transform documents from one format to another. Our Intelligent document platform, MYSTiQUE improves the customer experience, decreases human error, and improves employee satisfaction.

4. Seamless Data Extraction: Intelligent document processing can transform documents into digital data by leveraging optical scanning technology and artificial intelligence. It extracts data from documents using artificial intelligence, identifies document types, and exports them to other applications or a data repository. With intelligent document processing, companies can reduce costs and improve efficiency by automating data entry procedures. MYSTiQUE will eliminate the need for human intervention in document digitization. This platform will also help companies automate and streamline processes involving large volumes of documents.

5. Environment & Space-Friendly: Another advantage of our document digitization platform is that it frees up valuable office space. The typical paper document can take significant time to find and access, which is not very convenient for customers. Digitized documents are searchable and can be immediately accessed, saving you time and money. Documents digitized by MYSTiQUE are easy to share with others. The process is also more environmentally friendly, as digitized documents can be reused. Besides being environmentally friendly, digitized documents also help protect the confidentiality of the company. Not only does this ensure better accessibility for employees, but it also allows for more effective management and avoids the risk of losing important documents.

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Rating Notes Augmentation
Categories
Enterprise

Rating Notes Augmentation

Business Objective​

One of India’s largest rating companies want to introduce ML and AI to generate assessments and analysis to automatically create insight notes Qtabular information​

Problem Statement​

Rating Analysts need to ​Compute aggregated attributes of the company from their data.​ Plot this data and create notes based on visual analysis

Solution & Outcome​

MYSTiQUE is helping parse through information from these tables and graphical information and generates rating insights with detailed training from historical information​

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Insurance Underwriting
Categories
Enterprise

Insurance Underwriting

Business Objective

Insurance providers wanted an onboarding process that used video to capture remote KYC and onboard customers as per regulator norms

Problem Statement

Insurers are mandated to collect:

  • Consent
  • Liveliness, face match with the ID
  • Document extraction for form pre-fill

Solution & Outcome

MYSTiQUE helped reduce on-site visits and customers can complete their process in under 1 minute with 90% accuracy

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Data Ecosystem & Data Lake
Significance of Data Ecosystem & Data Lake for SMEs
Categories
Enterprise

Significance of Data Ecosystem & Data Lake for SMEs

Companies with large amounts of unstructured data turned to big data lakes, enabling large pools of structured and unstructured data stored in the cloud. In addition to enabling data scientists to process and analyze large volumes of unstructured information in real-time, data lake enables data to be dumped on-the-fly, without requiring any preprocessing steps.

A data lake provides a large staging area where data is processed. These data lake solutions can be structured or unstructured and can be accessed by systems regardless of any technology. This allows technologists to create views over the data and make informed decisions. They can also be accessible from any device. By creating these systems, companies can ensure that they never run out of storage space and are capable of keeping up with the growth of their business. And because of their high scalability, data lake and data ecosystem are a must-have for companies.

Data Privacy Act

A data privacy act protects your personal information. This includes your name, address, and contact information. It also includes any information you provide online. Many people are concerned about the collection and storage of their personal information. The act prohibits certain practices and sets out some of the rights of users. It is a great idea to read the law carefully. 

Here are some of the most common practices that are protected under this law.

You Must Not Store More Personal Data Than You Need

The Act is designed to protect you from having your information used by unauthorized parties. If you do not store your data securely, you will risk having it misused. By storing your data only for as long as is necessary, you can minimize the risk of it being misused or irrelevant. It is also inefficient and unnecessary for the business to retain your personal information for longer than you need to.

You Must Explain How You Use Your Customers’ Data

Data privacy laws protect individuals from companies and governments that use their personal information. The Family Educational Rights and Privacy Act (FERPA) sets forth the rights of parents and eligible students when requesting their education records. The Gramm-Leach-Bliley Act is another example of a data privacy act. It requires financial companies to explain how they use customer data and allows customers to opt-out. While these laws are far from perfect, they are good starting points for ensuring that your personal information is protected.

Data at Rest

The term “data at rest” describes the information stored on computer storage. This can be in digital form or in analog forms, such as a paper document or spreadsheet. There are two types of data at rest, structured and unstructured. Both types can cause problems if they are not regularly backed up. The first type is referred to as “non-active data” and is the most common. Keeping data at risk can be a good idea for several reasons.

Data at rest refers to digital data that has not been moved between devices or network points. It is not a permanent state; it moves from one device to another when processing a request or when a user needs to access it. Examples of such data include hard drives in PCs and laptops, portable storage devices, and edge-point devices. In addition to being inactive, the data at rest state can be vulnerable to attack.

The apt way to protect this type of data is to keep it secure. By using encryption, your data is protected even if it is not in use. By following security guidelines, you can reduce your risk of data breach and ensure your business’s data is secure. Moreover, this type of data is more secure and difficult to steal. It can be in the form of documents, archives, or reference files that change regularly. And hackers are ever-present, so it’s important to protect your data at rest from them.

Data at Rest Vs Data in Flow

Often, people confuse data in flow and data at rest. However, there is actually a distinction between the two types of data. While both are potentially vulnerable to hacking, they have different purposes and processing requirements. In this article, we will examine the differences between the two types of information. We’ll also discuss the ways to secure these types of information. Let’s get started! What is the difference between ‘data at rest’ and ‘data in use’?

‘Data at rest’ refers to data that has not been actively transferred between devices. It could be on a hard drive, a flash drive, or archived. The aim of data protection at rest is to protect inactive or unreadable information. This type of information is usually less vulnerable than ‘data in flow,’ but the risk profile varies widely between the two. Listed below are some examples of the difference between the two types.

Data at rest refers to data that hasn’t been moved between systems or processed on the CPU. Unlike data in flow, it’s protected by several security measures. Companies use encryption, hierarchical password protection, and secure server rooms to protect the privacy and integrity of their data. They also implement strict data security protocols, such as multifactor authentication and hierarchical password protection. Some organizations use data federation as a way to prevent unwanted access.

Companies Catering Better to Their Customers with Data Lake Solutions

Big data lake solutions are ideally located near the data and fed from external data sources, such as APIs and batch processing. Another perk of this aspect is that it can handle ever-increasing amounts of data. This approach can help companies eliminate data silos and speed up big data analytics. 

Companies that have a big data problem can benefit from a data lake. They can leverage big data analytics to make real-time decisions based on analytics. The data stored in these systems are constantly changing, and the users don’t have to worry about losing ongoing changes. A data lake turns out to be a single repository that allows consumers to read the same datasets in whatever manner they choose. That makes it extremely useful for companies looking to make decisions based on the latest data. Data lake allows for a 360-degree view of data, which makes it more useful for analysis and decision-making. Moreover, a well-engineered data lake can be scaled and managed fairly easily.

Data Lake Vs Data Warehouse

What is the difference when it comes to data lake vs data warehouse? The differences are in the structure and process of storing and analyzing large volumes of data. Both have their advantages and disadvantages. 

  • The first is that a data lake is more flexible and scalable, while a data warehouse is more rigid and can be difficult to scale and change. (Here we are assuming that data warehouses refer to significant amount of accumulated data at rest)
  • Historic data warehouses primarily use structured data. On the contrary, data lakes comprise a wider span of data while also covering unstructured data. 
  • Data warehouse is more complicated, requiring developers and integrations across different technologies.
  • Data lake solutions provide more cost-effective storage for huge amounts of data in comparison to the data warehouse. 
  • In contrast to data warehouses, which have very limited flexibility, data lakes can be used to process unstructured, unaltered, and hybrid data. 
  • The main difference while analyzing data lake vs data warehouse lies in the types of data stored within. A data lake contains unstructured data, such as texts and images, while a data warehouse stores structured data. 
  • A data warehouse can be difficult to understand or navigate. A data lake, on the other hand, has a greater range of possible uses.
  • One more difference between a data lake and a data warehouse is that the latter is lightweight & easy to manage, making it more suitable for non-missing-critical engineering and machine learning. 

Some Common Purposes That Both the Data Lake and Data Warehouse Serve

  • Both types of data lakes and data warehouses are built to be scalable and highly available. 
  • Both can be accessed by data scientists, CEOs, marketing teams, and business intelligence professionals. 
  • Both types of data can be used for analysis and decision-making.

An Insight into Big Data Ecosystem

As the universe moves toward a big data ecosystem, companies must make sure that the tools used to process that data are reliable and scalable. While there are a few key components of a big data ecosystem, many businesses are still struggling with how to get started. Luckily, there are now numerous options available to help them navigate the landscape. 

The first component of a big data ecosystem is an infrastructure that helps process, store, and analyzes large amounts of data. Relational databases have been utilized by enterprises for decades, but these tools were not designed to handle large, complex data. As the volume and variety of unstructured data have increased, new technologies were required to capture and analyze this information. These technologies can handle terabytes of data and can run on systems with thousands of nodes.

The big data ecosystem comprises a number of components. For example, the first stage of big data analysis is the extract, transform, and load (ETL), a process that prepares data for analysis. This pre-analysis work is known as data wrangling. While smaller analytics require minimal prep work, big-data analytics are more complex and require a much larger infrastructure than small-data analytics. The next component is visualization, which involves creating real-time dashboards, charts, graphs, and maps.

Importance of Data Ecosystem & Data Lake Solutions for SMEs

When implementing a big data analytics program, it’s important to evaluate the total cost of ownership and the capabilities of the solution. Another consideration is the security of the data. If a company has sensitive data, it will likely need to ETL sensitive data to another location or anonymize it for downstream consumption. For these reasons, a data ecosystem or a lake is the right choice. In addition, small enterprises should consider the lesser cost, risk, and time of implementation.

A data lake is for all the data generated by an organization. It eliminates data silos and makes historical data analysis available to all departments. By combining all data into a single repository, a company can perform all kinds of functions and make more informed decisions. The power of this technology is vast. By leveraging a single data lake, a small enterprise can power a wide variety of functions.

Big data analytics is critical for manufacturing companies. Real-time insight derived from data flows is a vital component of the manufacturing process. Millions of dollars of activity flow from factories to warehouses each year. Good business intelligence is essential for these companies to make smart decisions. In order to gain insight from this information, small enterprises can use a large-scale data ecosystem to turn their unstructured data into a valuable source of analytics.

SMEs are looking for solutions that comprise well-versed frameworks capable of accommodating their needs and addressing hyper-automation requirements as soon as a fair amount of data is analyzed in the ecosystem.

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Environment, Social, Governance
Categories
AI Enterprise

Environment, Social, Governance & Sustainable Businesses

ESG stands for Environment, Social, Governance, primarily comprises the three vast areas for which the term “socially responsible investors” is conventionally used. Investors who won’t greedily and selfishly compute the potential profitability and give equal importance to values and environmental concerns while making investments are included in this category.

For example, under the classification, ‘environmental’ are issues like pollution or the amount of toxic waste an industry produces and the factors associated with climate change. Socially responsible investment can be apprehended as one that supports sustainable investment, mission-related investment, and impact-based investment. Investors who come under the category of ESG investors are more of the activist type who tend to participate in shareholder meetings and contribute to amending company policies and practices. 

Well, if you ask, ‘Why must businesses must focus on the true essence of ESG to run a sustainable business?” Then, we would like to elaborate on these points as – 

  • Sustainable approaches lead to more customers, optimize resource availability, lower energy and water usage, and, as a result, lower production costs.
  • Sustainable approaches promote social credibility, retain talent, increase job satisfaction, and strengthen community ties.
  • Government backing, incentives, overcoming increasing competitive pressure, and better investor relations, for example, in terms of better financing conditions or cheaper capital costs, are all possible outcomes of environmental sustainability.

ESG Criteria

Each of the three variables of ESG investments – environmental, social, and governance (corporate) – has a set of requirements that can be utilized by socially conscious investors or organizations looking to take a more ESG-friendly approach to their operations. Though many ESG criteria are subjective, efforts are underway on a number of fronts to provide more objective, trustworthy assessments of a company’s performance in terms of ESG policies and procedures. 

ESG – Environmental

The term “social criteria” refers to a wide range of potential difficulties. There are many different social aspects to Environment Social Governance, but they all revolve around social relationships. Many socially responsible investors consider a company’s relationship with its employees to be one of its most important ties. 

Here’s a quick glance at some of the factors to consider when assessing how a firm manages its social relationships:

  • Is employee compensation competitive, or even generous, when compared to similar jobs or positions across the sector? What types of retirement funds are accessible to employees? Does the corporation contribute to the retirement plans of its employees?
  • What benefits or perks do employees receive in addition to their basic income or salaries? If you do things like providing a free, very luxurious buffet lunch for all employees every coming Friday – or avail other types of perks that aren’t common at all workplaces, such as an on-site health club – it can make a major impact on the evaluation of your company with Environmental Social Governance – conscious investors.
  • Corporate policies on multiculturalism, inclusiveness, and sexual harassment prevention are regularly discussed.
  • Staff education and training programs; for instance, does your firm provide financial assistance for ongoing or higher education and/or flexible work schedules for employees seeking further education; what prospects do employees have at the company to be trained in new employable skills that will qualify them for higher-paying roles?
  • Is there a prominent level of employee involvement with management? How much say do employees have when it comes to defining operational processes in their departments?
  • The percentage of employees who leave.
  • What is the mission statement of the company? Is it relevant to society and profitable to society?
  • How well do you handle your customer relationships? Is there any interaction between the company and its customers on social media? What is the customer service department’s level of responsiveness and efficiency? Is there a history of customer protection issues, such as product recalls, with the company?
  • Is there a public or political stance taken by the corporation on human rights issues? Is money donated to charitable causes?

ESG – Governance

In the context of Environment Social Governance, governance refers to how a firm is run by officials in the executive suites on the top floors. How well do the company’s senior management and board of directors look out for the interests of the company’s major stakeholders, such as staff, vendors, investors, and consumers? Is the corporation involved in the community where it operates?

Transparency in finance and accounting, as well as complete and honest financial reporting, are frequently regarded as essential parts of successful company governance. Board members must also behave in a legitimate fiduciary relationship with shareholders, avoiding conflicts of interest while performing that role. Are the members of the committee of directors and the executives of the organization diverse and inclusive?

According to the ESG rating report, many investors are particularly concerned about CEO compensation, as they do not favor multi-million-dollar incentives for executives when the company imposes a salary freeze on all other employees. Is additional compensation for CEOs properly linked to the company’s long-term value, durability, and profit growth?

A rule that does require the top-level chief executive officer to maintain stock ownership similar in value to ten times their annual salary is one of the company’s corporate policies aimed at ensuring that company executives take a strong interest in the company’s ongoing success, rather than just in earning some quarterly bonus. Furthermore, executive rewards are computed using a variety of factors other than sales or profits, including workforce, investor, and client satisfaction.

ESG Metrics in Fashion Industry

In the modern-age fashion segment, ever-evolving trends are fabricated, manufactured, and supplied to users in increasingly quicker time slots, thus pushing a dramatic decrease in the number of times the clothing is worn before getting thrown away. Increasingly more clothes are getting discarded, the associated economic value is getting lost, while there are even worse environmental implications.

An apt part is that more and more people are aware of the same fact, specifically with the sustainability-driven credentials of the global fashion segment entering enhanced scrutiny. Many of the fashion industries are leading towards sustainable approaches with an aim to zeroing greenhouse gas emissions by the year 2050, reinstating the environment and ecosystems, procuring endangered species, and reducing single-use plastics by the year 2030.

Environmentally-Friendly Businesses Provide a Lot of Advantages

 Though there are no law mandates to pressurize you, environmentally-friendly business methods will merely assist you in limiting your environmental effect and protecting natural resources. Your company can benefit the environment in a variety of ways –

  • Reduce your reliance on natural resources by using items that do so, for example, rainwater tanks, solar hot water systems.
  • Utilize products made from recycled parts, for example, office supplies designed from recycled plastic, furniture made from recycled rubber. 
  • Examine all of your business activities to determine if you can make any changes, for example, reducing travel by conducting online conference calls instead of interstate meetings. 

Making your company more eco-friendly not only benefits the environment but can also save you money.

Recycling Helps You Save Money

You can save money by avoiding, minimizing, repurposing, and recycling. A few easy modifications to how you handle paper, for example, can engage your employees in ecologically responsible operations while also saving you money:

  • Excessive use of materials should be avoided.
  • By encouraging employees to print double-sided, you can save money on paper.
  • Encourage employees to take messages using scrap paper rather than buying message pads to save money.
  • By shredding extra paper, you can either recycle it commercially or allow employees to take it home to use in their compost.

Good Business Practices Can Help You to Gain New Customers

Branding your eco-friendly practices will help you stand out from the crowd and attract new consumers who want to acquire products and services from a company that cares about the environment.

Enhances Long-Term Durability

Reduce your organization’s environmental effect to uplift its long-term sustainability. Your firm will have a better chance of long-term success if you’re less dependent on natural resources than your competitors and have strategies in place to deal with rising costs as a result of climate change.

ESG ratings are aimed to aid investors in evaluating and comprehending a firm’s financially material ESG concerns. Firms are scored on each fundamental ‘E,’ ‘S,’ and ‘G’ topic, as well as an overall score, based on gathered data, including media sources and financial statements. In the past, a company’s ESG rating was often influenced more by the quality of its public relations department than by its substantive policies. Investors utilize these one-of-a-kind scores as a proxy for ESG performance. Companies that score highly on ESG parameters are considered to be better at predicting future opportunities and risks, more inclined to long-term tactical planning, and more focused on long-term wealth development. Being an eco-friendly company, Konsultera is working on a platform that aids in rating consumers on the basis of ESG. Hence, it can be proudly claimed that the use of technology in this field is rapidly increasing. 

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sme-needing-credit-whats-holding-back-lenders
Categories
Enterprise

SMEs (Small and Medium Enterprises) Needing Credit? What’s Holding Back Lenders?

Is yours a newly established start-up? Are you facing problems while looking for a loan to support your small enterprise? If yes, then you should know that it can really be challenging for people who own small or medium enterprises to attain a lender or commercial bank loan. Banks or lenders often don’t lend money to newly established start-ups as those are the riskiest investments for them. But to be honest, it really is unfair for small and medium enterprises as taking money out-of-pocket cannot be possible for a long time. Hiring new staff, opening new branches, setting up an office, and purchasing inventory require investment which can only be supported with the assistance of additional working capital. There are several reasons why lenders and mainstream banks deny loan requests from SMEs (Small and Medium Enterprises). Let us take a glance at a few reasons in detail – 

1. Erratic flow of income – Mainstream banks only consider loan requests from those SMEs who have a predictable, substantial, and considerable cash flow every month. SMEs who do not provide proof of such stability and consistency of income stream is more likely to be rejected a loan from banks. The main aspect that concerns banks is whether the customer is capable of paying monthly installments on a regular basis while maintaining their payroll, rent, and other expenses. At times small businesses struggle in maintaining their bank accounts even while they are gaining profits just because they have to make upfront payments to their suppliers and other third parties before they get their pay in hand. 

2. Lack of experience – Experience is like abstract proof for the banks and lenders. If the client or customer does not have a minimum of one year of experience in the industry, banks do not consider them for loans. They are considered incapable on the note that their income might not be consistent or even substantial for them to repay the loan. 

3. Limited or lack of collateral – It is very well known that while filling the application for a loan, the bank asks for a valid piece of collateral for the bank to secure while the client obtains the money. Small and medium enterprises are mostly not provided loans due to a lack of proper or limited collateral. Though, that is not the case with large-scale business organizations and giant corporations who have high-value assets and real estate to surrender to the bank. 

4. Poor and unreliable credit history – Before approving or even considering a customer’s business loan, they go through their loan application to review their credit history. If they have a clear credit score, the bank will be assured that the customer has no past of bankruptcy and can manage their corporate and personal finances well without fail in timely payments. Considering the other aspect, if the bank finds out the customer to have a poor and unreliable credit history, then they will be convinced that they are incapable of making financial commitments as per the loan agreements. 

5. Elevated Regulation Standards – After the recession, regulation standards have been raised as banks have become more strict in their federal rules. Providing loans to SMEs is considered a risky investment when compared to well-established large-scale industries and firms. 

6. Debt-to-income ratio – Sometimes, it so happens that SEMs request loans from banks while they are already indebted to other money lenders. When customers have outstanding debts with other banks or money lenders, then the banks tend to hesitate before providing them with loans. At times they reject loan applications from companies and firms who have taken up loans in the past as well. Business start-ups might secure advance cash or loans from multiple sources, especially during their initial set-up phase, which can be a disadvantage for them while applying for a loan from a standard mainstream bank. 

7. Lack of guarantee – According to banks and lenders, newly set-up businesses, small and medium enterprises need to guarantee them the repayment of the loans borrowed by them. If they are not capable of personally guaranteeing them the repayment of the loan even in installments, then the banks do not consider them. Personal guarantees mean the customer is liable to repay the complete amount to the bank failing, which could cause unfavorable circumstances for the customers. 

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No KYC Blog Banner
Categories
AI

Insurtech & ‘No KYC’: How Insurers Will Deal with Contact-Ability Retention of Their Customers?

If you’re an insurer struggling with contact-ability retention amidst this insurtech saga, you’ve probably already heard the phrase, “no KYC required. ” However, this trend is far from over. Avoiding KYC for insurance has a significant impact on insurers’ contact-ability retention. It’s a sign that insurers need to invest in more than just digital technologies.

Adapt and Disrupt Business Processes
Insurers are already facing a number of challenges related to no- KYC in terms of the validation and verification of documents. Managing the issue will require the insurer to adapt and disrupt some of its legacy business processes. It’s not enough to simply implement a new system. An insurtech company insurer must be able to disrupt its own processes. It will have to work with an external network to do so. This way, the insurers will be able to take a step towards the fintech revolution.

Keep Track of Renewal Information
Organizations Insurers not aware of insurtech must work with brokers to obtain renewal information and other critical data. The issue of contact-ability retention is especially problematic for insurers not primarily dealing with life insurance technology. Without a reliable and secure data pipeline, brokers will have difficulty providing administrative services. Insurers should consider exploring blockchain technology, which holds tremendous promise for transactions involving multiple parties and no central trusted authority. Further, they should look for ways to minimize the amount of information they need from brokers and make use of publicly available information.

Make Use of Blockchain Technology
The blockchain has many advantages for KYC processes. The immutability of the network creates trust among parties. By eliminating secondary validation and cross-checking, KYC blockchain software eliminates the need for manual processes. Furthermore, it makes reporting and communication more efficient and prevents mistakes or fraud. Blockchain technology comprises the potential to reshape the way KYC processes are conducted. It allows for decentralized, automated data validation and full control over personal data. In addition, financial institutions are looking to utilize innovative technologies that will improve the way they do business. By embracing Blockchain technology, these organizations can increase transparency and reduce the risk of financial fraud and crime.

A key aspect of blockchain is that it can execute operational and control processes. By codifying workflow routing and KYC controls in smart contracts, businesses can automate KYC. This will reduce the need for periodic reviews. By utilizing the technology, more financial services companies can also implement multilingual solutions. By implementing the technology, banks and other accredited organizations can offer a better customer experience. While the future of Blockchain for KYC is uncertain, it will be a game-changer for the financial services industry.

Endnotes
Despite the challenges and opportunities, this trend is a major challenge to insurers, specifically in terms of the verification of documents. Insurers must adapt to this new reality. They must develop smart contracts and mobile applications to manage customer interactions with their clients. Insurers should use their private key to grant network access to their customers. Then, they can build smart contracts that trigger a claim process based on data provided by sensors linked to the internet of things.

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Evolution of Legal Tech
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AI

Evolution of Legal Tech

In the bygone days, if a lawyer would mistakenly forget to carry with themselves important documentary evidence, they would immediately send someone to bring the documents and, in the meanwhile, would have asked for another hearing from the judge. However, today if a similar situation of crisis occurs, lawyers simply resort to accessing the same document on the cloud storage via their mobile phones!

This shift is possible due to the evolution of legal technology over the past decades.

Legal Tech, the part of the legal industry that operates with the infusion of advanced technologies, has completely transformed the way in which attorneys and law professionals work. With the passage of time, legal tech has made it possible to digitally transform the legal industry and coordinate the proceedings with tech-savvy clients. Due to the efficiency in operations that it brings to the table, legal tech has been adopted by not just the top legal firms but also smaller firms and start-ups who have invested in legal tech.

Digital Transformation in the Legal Tech Industry Over the Years

With the advent of technological upgrades and advanced software solutions, today, there is a presence of numerous Legal tech software and highly efficient tools that Legal tech companies use. The transformation of the legal tech can be seen in the following aspects:

  • Research 

Earlier, the process of legal research was manual. It was time-consuming, tiresome, and also error-prone. With these drawbacks of the traditional process of research, it became difficult for the companies and advocates to meet the needs of their clients and deal with complex issues in a timely manner. The advent of research tools like FindLaw, Casetext, and Casemaker has made the process of legal research much easier.

  • Predictive Coding and eDiscovery

The use of Legal tech AI in predictive coding technology has become helpful to determine responsive Electronically Stored Information (ESI) documents. This is also known as Technology-Assisted Review (TAR). Many companies and Legal tech start-ups use these tools to save time and money and make better decisions that are error-free.

  • Legal Document Management

This software helps in legal document creation and management. Legal firms can now organize and access the documents in a much more efficient way which assists them in making the right business decisions.

Key trends to Observe in the Future of the Legal Tech Domain

  • Focusing on client collaboration to ensure greater transparency and a wider acceptance of legal tech tools.
  • The increased use of Legal Tech AI will result in a rise in Predictive Legal Analytics. The innovative solutions and data-driven information would help the new legal tech start-ups and existing firms.
  • There would be a change in the hiring process, and non-lawyers would be hired to contribute to increasing business efficiency using their expertise in sales, process management, and C-suit administration.

The Final Say

With all the revolutionary changes in the legal tech domain and its promising future, it would be a good opportunity for legal firms to explore the legal tech software and tools that would make their work easier. To find the right legal tech solution provider, it is recommended to research various factors such as the team size, teach stack, portfolio, experience, and many more.

For assistance and guidance regarding the appropriate legal tech tools, please connect with our experts at Konsultera and explore the growth opportunities in your business through our machine learning and AI development solutions.

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Fintech Echo System
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Startup

Customer Acquisition Services in a Fintech Ecosystem

A company should be aware that in a fintech-driven ecosystem, customer satisfaction is not only about the product but also about consistency. As the name suggests, a customer-centric approach should be adopted when dealing with customers. The salesforce should be made to understand the customer-centric philosophy of the company. This will ensure that the company’s sales strategy is aligned with the interests of the customer. This would, in turn, allow the sales team to offer better services and, in turn, attract more customers.

However, it should be noted that customer acquisition requires a comprehensive strategy. This strategy should include not only acquisition strategies but also a way of ensuring that these strategies are successful. This can be done by conducting regular customer satisfaction surveys. Additionally, a company should also make sure that it has a good system of training its sales force. The success of the entire fintech industry, thus, hinges on customer satisfaction.

What is a Customer Acquisition Strategy?

A customer acquisition strategy is a sales process that automates the customer acquisition process and supports a company’s overall sales strategy. Customer acquisition services in fintech can be described as a set of activities and processes undertaken to acquire new clients, and this may be done through different approaches and strategies. These activities include providing the business with new business development opportunities, identifying and targeting existing customers, offering solutions, and providing training. The aim of such a process is to build long-term customer relations. At the same time, it helps the business to cut costs and improve profitability.

  • Relationship Marketing Strategy

There are several customer acquisition services in fintech offered by different companies. The most common is the relationship marketing strategy. Under this strategy, a company would create a brand for itself. This brand could either be associated with the product line of the company or the services that the company offers. This way, customers would be encouraged to use the product or services offered by the company. To get new customers, the company would provide valuable information about the benefits of using the product or service and encourage customers to seek the company out for further business.

  • Information and Data Collection

Another way to customer acquisition services in fintech is through information and data collection. It involves collecting information about current customers, analyzing these data, and providing reports on ways in which the business could improve customer service and attract new customers. The reports could also provide ideas on how the business could lower costs and reduce operating costs to increase profits.

  • Training Sessions & Seminars

One customer acquisition service in fintech offered by companies is focused on education. This is done through training and seminars. During this training, the aim is to teach management personnel of various departments about customer service and how they can improve it. The seminars would typically take place once every month or quarter, depending on the size of the company and the scope of its training program. Customer acquisition in fintech can even come from hiring external vendors, especially when the company wants to increase its reach in the market or when it is experiencing growth in its customer base.

  • Customer Relationship Management

One important customer acquisition service in fintech is called customer relationship management (CRM). CRM is the management of customer data, including customer satisfaction and customer return policies. In simple terms, it is about making sure that you can keep your customers satisfied and that they will keep coming back to you. This is why it is very important to hire the best consultants around. Consultancies that specialize in customer acquisition services in fintech are known to be very efficient and effective in keeping their clients happy.

  • Telemarketing & Viral Marketing

Telemarketing is the most preferred method among companies engaged in a fintech-driven ecosystem as it provides efficient communication with prospects. Through telemarketing, the company can establish contact with a customer. Moreover, companies can use various other communication tools to reach out to prospects. Through a number of tools, the business can also establish regular interaction with customers. Another important customer acquisition in a fintech-powered ecosystem is through viral marketing. Viral marketing is a technique that allows a customer acquisition process to spread via exponential growth of the customer base.

The Final Say

The best customer acquisition method should therefore be able to reach out to as many customers as possible. It should be able to bring in new customers while also converting old customers into loyalists. Additionally, a company should also strive to build up its brand equity as much as possible.

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