What are preconfigured solutions?

SAP Preconfigured solutions are implementations featuring standard functionality or common patterns. Since they include common enterprise features such as supply chain, finance, and inventory management, preconfigured solutions can be deployed rapidly. In simple terms, SAP preconfigured solutions are simple, ready-to-consume solutions that adapt to your business needs.

SAP Rapid Deployment Solutions allows the development of preconfigured solutions for specific functional areas, complete with pre-built reports, preconfigured content, and predefined best practices. Such suites enable enterprises to deploy software easily, with accelerated implementation times, and predictability in cost and scope.

Each preconfigured solution is a complete, end-to-end implementation. Enterprises may adopt it as such, or use it as a base for developing a full-blown customized solution. Open source solutions allow enterprises to download the source code and customize the solution.

Traditional preconfigured solutions came on-premise. The SAP HANA Enterprise Cloud heralds the cloud version of preconfigured solutions.

Related Reading: What is Business Process Expertise in SAP and Why You Need it

How preconfigured solutions enhance industry operations?

Preconfigured solutions spare enterprises from “rediscovering the wheel.” When solutions exist for standard requirements, it avoids the wastage in development efforts. Preconfigured solutions save time, trial-and-error, and labor. The in-built accelerators allow rapid implementation and configuration. The shortened time to market delivers a competitive advantage to firms.

A preconfigured solution offers a working model with glitches removed. These solutions connect key functional areas, to streamline operations and improve communication flow across departments. It automates routine and repetitive functions and offers well-structured content that improves visibility into key fields.

SAP offers built-in support for industry best practices. Solutions developed using SAP combines the latest technology, industry best practices, and processes in a single package.

Developers using SAP to build preconfigured solutions can adopt a modular and scalable approach. They mix modules to create targeted solutions such as CRM, field management suite, ERP and more. Clients may choose the most relevant reporting tools for their reports using SAP Business Intelligence Adoption rapid-deployment solution. SAP Predictive Analytics Content Adoption rapid-deployment solution helps to implement a predefined predictive analysis use case.

Transforming various industry verticals

Preconfigured solutions deliver efficiency improvements in several industries and verticals. Five of them are mentioned below:

1. Real Estate

Unstandardized information, inefficient processes, and weak communications often affect the real estate industry. Preconfigured solutions enable enterprises to streamline data and workflows. 

Developing preconfigured solutions for key functional areas of the real estate industry allows business owners to access information in real-time, prevent opportunities from slipping through the cracks, and remain in control of the business. Here are a few key functional areas where pre-configured solutions can come to the rescue of real estate enterprises:

• Document management with powerful search and sort functionality.
• Process automation functions to streamline operations.
• Contact maintenance to keep track of customers and upcoming tasks.
• Reporting and analytics to generate and share data and other critical information.

2. Supply Chain and Logistics

Preconfigured solutions make the complex supply chain relationships simple and easy to handle. SAP’s Model Company for supply chain planning offers a ready-to-run, comprehensive solution, complete with relevant business content, accelerators, and enablement services.

The suite co-opts:

• Demand planning to manage demand streams and increase productivity.
• Response and supply planning.
• Supply and allocation planning.
• Deployment planning.
• Sales and Operations planning.

The inbound and outbound integrations with SAP S/4HANA ensures seamless integration with other functional areas, such as sales. Businesses gain improved visibility to the upstream and downstream business value chains and can visualize the entire supply chain network. The preconfigured solution aligns demand and supply plans with financial targets and key performance indicators.

Related Reading: Seamlessly migrate to S/4HANA with these tools and methodologies

3. Healthcare

The healthcare industry is under pressure to innovate while keeping up with regulations. Preconfigured solutions automate regulatory concerns and compliance. Ready-to-run process models and scenarios enforce standardization with tight quality controls. It improves efficiency in research and development. Accelerators support rapid design and implementation.

The most popular modules of SAP’s preconfigured solutions in healthcare are meant for:

• Research and development
• Production
• Regulation
• Quality and traceability
• Logistics and transport
• Purchases and provisioning
• Marketing and commercial

4. Sales and Marketing

SAP preconfigured solutions infuse efficiency to customer-facing functions and increase customer satisfaction. Its most popular implementations in the sales and marketing domain include:

• Predicting customer demand based on real-time data.
• Tracking sales history.
• Automating sales operations. The solution tracks all processes, from ordering of raw materials till the delivery, and takes care of auditing, notifications, and reporting.

5. Financial Services

The SAP Model Company solution for Financial Services offers a ready-to-run, comprehensive solution to support the core financial processes, including:

• General accounting
• Cash and treasury functions
• Planning and forecasting

These preconfigured solutions come with relevant business content for a specific use-case, accelerator, and enablement service. These solutions enable gap analysis, address resource bottlenecks, and support lean implementations.

Today’s enterprises seek efficiency improvements and cost savings without compromising quality. Fingent uses SAP to build pre-configured solutions that enable enterprises to realize such goals. Implementing these custom-built pre-configured solutions helps you transform your processes across various business areas and improve your customer relationships. 

Contact us to get a free consultation with our SAP Experts. 

How to Solve Accounting Challenges in Business with Augmented Intelligence

The challenges faced by finance and accounting teams are like the underwater icebergs that can crash a huge ship. The Titanic sank because of poor decision-making. Likewise, weak financial decisions can affect your business. This blog will help your finance and accounting teams to identify the hidden challenges and provide insights on how to use Augmented Intelligence to overcome complex business challenges effectively. 

5 Reasons Why Augmented Intelligence Is Gaining Importance 

Many businesses are embracing Augmented Intelligence because;

• Enormous volumes of data can be processed quickly and efficiently with Augmented Intelligence.
• Accounting tasks such as audits, payrolls, taxes, and banking can be automated using Augmented Intelligence.
• Due to its ability to continuously learn, Augmented Intelligence can constantly improve efficiency while eliminating the risk of human error.
• It enables humans to make crucial decisions without bias by providing fair information and recommendations.
• Tedious tasks such as bookkeeping can be automated and streamlined.

Top 4 Solutions Offered by Augmented Intelligence 

Challenge 1: Protecting the business from fraud

According to the 2018 global fraud and identity report, 63% of businesses still continue to experience the same number or more fraud losses than the preceding year. And only 54% are ‘somewhat confident’ in their ability to detect fraudulent activity. The wide variety of fraud types and the enormity of the work involved in reviewing the data manually or by rule-based systems can make the detection and prevention of fraud a huge challenge.

Solution: 

With the help of Augmented Intelligence, large transactions can be analyzed in real-time which helps in detecting fraud. Since Augmented Intelligence can even categorize the score of fraudulent activity, investigators are able to prioritize their work effectively. Once the fraud is detected, Augmented Intelligence allows you to reject the transaction outright. Since Augmented Intelligence continues to learn from past data, it can learn from investigators’ reviews and understand how to discern patterns that lead to fraudulent activities.

Related Reading: Artificial Intelligence and Machine Learning: The Cyber Security Heroes Of FinTech

Challenge 2: Risk Assessment

While evaluating potential risks in lending money or providing credit, businesses could end up denying credit without assessing their current situation using traditional methods. Worse yet, they could end up approving credit to churners who could affect profits. The organization might also face the challenge of explaining to the consumer the reason for denying them credit.  

Solution: 

Augmented Intelligence helps you assess your customers’ current income and recent credit history based on the enormous data that is available at hand. This allows for a more realistic and accurate assessment of each borrower. Such kind of assessment allows financial firms to make more individualized decisions. Besides, Augmented Intelligence can provide reason codes which would explain the important aspects involved in credit decisions, making it easier to provide reasons why credit is being denied.

Challenge 3: Trading and Investment

According to a 2018 survey conducted in the US, 70% of millennials use mobile banking in the US alone. And this figure is steadily increasing all over the world. Businesses cannot function without mobile applications. It has become a channel of interaction with customers who would like to review transactions, pay bills and find customer service. Failed interactions would translate into increased customer churn, lost transactions and even lost revenues.

Solution: 

Augmented Intelligence can assist your business in detecting anomalies in transaction volume by identifying the triggers for such anomalies. Based on previous data patterns, the system can look at expected data volumes which can then be compared with real-time transaction values. This will help in your decision-making process because it clearly and quickly indicates the highs and lows of a transaction by suggesting solutions that meet each individual demand.

Challenge 4: Combating Money Laundering

It is estimated that the amount of money laundered globally in one year is 2 – 5% of the global GDP! And this seems to be increasing at an alarming rate. To combat money laundering, extensive investigations must be performed by the finance and accounting teams. 

Solution: 

Augmented Intelligence can detect suspicious and complex transactions and raise a red flag on such transactions so investigators can further examine them. Augmented Intelligence can learn from each experience and more effectively safeguard your firm.

Related Reading: The Future Of Communication and Security Using Augmented Reality

Discover New Growth Opportunities by Applying Augmented Intelligence

Augmented Intelligence can help finance and accounting teams reduce costs, improve operations, increase consumer satisfaction and reduce the time taken for various processes by 80-90%. It can also reshape your entire organization from internal operations to treasury services. It can assess the available unstructured content and help your business unlock valuable insights from them. This enables smarter decision making, which in turn helps in the growth of your business. 

When your business adopts Augmented Intelligence as part of your methodology, it gives your customers benefits that will lead to loyalty and growth. Fingent top custom software development company has been helping many clients achieve this, and we can help you too. Give us a call and let’s discuss. 

Robotic Process Automation Reflecting The Banking, Insurance & Logistics Industries

Robotic Process Automation is the fastest-growing segment of the global software market. Using this technology, companies can fast-track their digital transformation initiatives. Although RPA is useful in all industries, the biggest adopters of this technology are banks, insurance companies, and logistics. These companies traditionally have numerous legacy systems and choose RPA solutions to enhance or replace manual IT processes. This article discusses how Robotic Process Automation is revolutionizing the banking, insurance, and logistics industries. First, let’s consider what is Robotic Process Automation.

What is Robotic Process Automation?

Robots have fascinated humans for a very long time. From the futuristic robot Maria from the movie Metropolis in 1927 to this day of AI sci-fi, the possibility with robots is a topic of endless discussion. Interestingly, though, this word “robot” in Robotic Process Automation (RPA) does not involve a physical or mechanical robot. Instead, it is a software running on a virtual or physical machine. Aaron Bultman, director of Product at Nintex simplified the expression saying, “RPA is a form of business process automation that allows anyone to define a set of instructions for a robot or ‘bot’ to perform.” 

How to accelerate your business growth with Robotic Process Automation

According to Gartner, RPA grew by 63% in 2018 and continues to be one of the fast-growing technologies in many industries! RPA lets companies automate current tasks as if a real person was doing them across systems and applications. It interacts with each system just as a human user would interact. This does not require complex system integration. These functional RPAs are virtual workers and execute rule-based information processes, enhancing efficiency and accuracy. Additionally, it is easy to model and deploy. Let us consider the three specific industries where RPA is most beneficial.

RPA in Banking

The banking industry is completely process-oriented. Every activity is done meticulously to avoid errors in processing. The repetitive nature of the job and the high probability of human error could cause mistakes that might prove very costly. Therefore, in the recent past, leading banking institutions have started using RPA to minimize errors. According to a report by KPMG, RPA will perform almost 75% of the existing offshore jobs, which could save operational cost. 

Scalable Benefits of RPA in the Banking Industry

• Mortgage Lending. RPA can enable the banking industry to meet loan quality and cost concerns head-on. Automation of repetitive and time-consuming manual tasks will free up your team to focus on the more important details of loan applications. It speeds up the work, increases revenue. enhances customer experience, reduces operational costs, decreases risk and improves compliance. 

• Compliance and Risk Management. It enables the banking industry to automatically integrate and aggregate compliance information into business processes, streamlining the required work while reducing expenses. RPA eliminates the need for manual regulatory monitoring and data collection. It can empower risk management and compliance teams. It enables banking industries to avoid costly fines and damages to reputation. It provides accurate and complete information.

• Customer Service and Support. RPA ensures the longevity and loyalty of your customer relationship and the future of your bank. It helps you engage customers in real-time. It automates customer service activities so the customer is not waiting endlessly. It increases the productivity and efficiency of the team.  

Related Reading: Check out these 5 simple hacks on using banking mobile apps safely. 

RPA in Insurance

An insurance company receives hundreds of claim requests. Validating each request and handling them is not only a herculean task but also a painstakingly slow manual process. The entire process of the claim takes several days. Because this is a costly and time-consuming process, the company risks losing customers. To prevent further damages, insurance companies are now relying on RPA to help them improve operational excellence and reduce costs.

Scalable Benefits of RPA in the Insurance Industry

• Improves customer service because RPA effectively reduces the turnaround time in resolving customer issues.
• Processes and workflows could be tracked and recorded at each phase. This reduces staff workloads and improves process efficiency.
• Reduces the processing time by 40-80%.  This frees up the team to focus on more important activities such as acquiring new clients.
• Reduces errors made during data entry significantly.
• Speeds up and organizes the processing of claims through a systematic underwriting process.
• Based on the demand, intelligent bots can scale up or down, which delivers consistency in service and operational efficiencies.
• Improves audibility and operational risk management due to the accuracy level of RPA.
• The time for the cancellation process could be reduced by one-third.

Related Reading: Here’s how machine learning is accelerating paperless offices for legal firms. 

RPA in Logistics

The logistics industry depends on several processes to facilitate the proper distribution of products, materials, and services from B2B or B2C. The need for an intelligent logistics system increases as the industry along with competition advances every day. Here’s how the RPA can contribute to the logistics industry:

Scalable Benefits of RPA in Logistics.

• Better data management and customer service.  Negative experiences and a multitude of errors with logistics providers are causing customers to lose their trust in online shopping. With the benefits of automation and digitalization brought about by RPA, logistics providers no-longer need to rely on huge amounts of paperwork, which was the underlying cause for errors and poor customer service. Logistics companies are enabled to manage real-time monitoring of flow and resources, availability, costs, staffing, transportation, suppliers and so on more efficiently. 
• Improved work safety for employees. Through the use of automated machines in unsafe environments and the reduction of repetitive stress in manual tasks, work injury has been dropping steadily with the aid of RPA. This results in savings in terms of injury compensation and loss in reputation. It can also increase productivity, improve employee satisfaction and loyalty, and increase their efficiency.
• Improved efficiency and precision. RPA can help logistics companies easily manage the supply chain processes more efficiently. The anticipatory logistics system helps companies gauge the demand from their customers and adjust their production volume accordingly. It can help in managing and analyzing huge amounts of data within seconds, resulting in fewer human errors, faster deliveries, and fewer errors in delivery.
• Cost reduction. Fewer errors from human decision-making result in cost savings for logistics companies. Also, RPA reduces the need for human workers, which results in fewer paychecks and more profits. Where workers are still needed, it can raise their productivity, margins to a whole new level. It improves customer satisfaction and creates a safer work environment for the workers.

Related Reading: Know more about how AI is reshaping the supply chain and logistics industry.

Empower Your Business With RPA 

According to Global Market Insights Inc., the RPA market is expected to reach $5 billion by 2024. It is increasing capabilities and improving performance while reducing costs in several industries. Fingent Technologies has been one of the top software companies empowering industries globally with robotic process automation capabilities. Give us a call and let us discuss how we can transform your business with RPA.

How Machine Learning Systems Detect And Prevent Frauds Without Affecting Your Customers

There is nothing more fearful than imbalanced data, especially when dealing with various payment channels like credit and debit cards in banks and other financial organizations. With the wide increase of different payment mediums, businesses are finding it difficult to authenticate transactions. But Machine Learning has been a viable solution to detect fraudsters.

Machine Learning can be referred to as the ability of machines to learn data with the help of human intelligence as well. According to the latest report by Gartner, by 2022, more than nearly half the data and analytics services/ tasks will be done by machines.

Related Reading: How machine learning can help boost customer experience. 

Machine Learning In Making Real-Time Decisions To Prevent Fraud Activities

If a business is able to predict which transactions can lead to fraudster attacks, then the business can considerably lower costs and make critical decisions. While sending sensitive data to a third-party, it is important that the data is not misused for fraudulent activities. This can be done as follows:

1. Using Machine Learning Models

Consider a score produced from a number of algorithms that is a combination of all possible features. This set of algorithms can be termed as a machine learning model. This machine learning model constantly queries these algorithms in order to produce an accurate score that can be used to predict frauds.

Machine learning models can be compared to data analysts who run numerous queries on large volumes of data and try finding out the best from the derived outcomes. Machine Learning makes the whole process fast and accurate.

2. Fraud Scores For Fraud Detection

There always exists large amounts of data. Machines are trained using these data sets that are pre-labeled as frauds. These labels are based on earlier records of confirmed fraudulent activities.

The machines are then trained using this labeled set of data. These data sets are now called as training sets. By a named label, the machine is taught to determine if a new transaction or a particular customer is likely to be a fraudster based on a score of 0 to 100, being the probability.

This score enhances the ability of a business to ensure a considerable reduction in frauds by providing accurate predictions.

Related Reading: Check on to this Infographic to learn more about Machine Learning.

Can Machine Learning Actually Predict And Prevent Fraudsters?

Designing as well as being able to apply algorithms that are on the basis of data sets from the past, enables to analyze frequent patterns in these data sets. These patterns in data via the algorithm are taught to machines and these machines considerably reduce human effort.

These algorithms help businesses boost predictive analysis. Predictive analysis is important for data reduction by using statistical modeling techniques that help in predicting future business outcomes on the basis of past data patterns. In fact, among many businesses, 75 percent of them find growth to be their main source of value, whereas 60 percent of some others believe that it is nothing else but predictive analytics that is the key to deriving value!

Machine learning algorithms are not only used in predictive analytics, but also in image recognition, detecting spam, and so on. Machine Learning can be trained by a 3 phase system.

1. Train
2. Test
3. Predict

So to be able to predict an occurrence of fraud in large volumes of data sets and transactions, cognitive technologies of computing are applied to raw and unprocessed data.

Machine Learning thus facilitates, prediction and prevention of fraudsters for the following key factors:

• Scalability: Larger the data sets, increased is the effectiveness of machine learning algorithms. Initially, the machine learns which transaction/data sets are fraudulent and which ones are safe, the machines are well able to predict such cases in future transactions.
• Readiness: Manual tasks are time-consuming. These are not preferred by clients. Hence, machine learning strategies are used to acquire faster results. Machine learning algorithms process a large number of data sets in real-time to customers. Machine Learning frequently and periodically analyzes and processes new data sets. Advanced models like neural networks have provisions for autonomous updations in real-time.
• Productivity: The need to perform redundant tasks reduces productivity. The continuous repetitive task of data analysis is performed by Machine Learning algorithms and prompts for human intervention only when required.

Related Reading: Check out how machine learning is revolutionizing software development.

Machine Learning Methods – Using White Boxes And Ongoing Monitoring To Detect Fraudsters

What does a machine learning system do? The methods adopted and the various approaches used for this are termed Whiteboxes, as there is no definite method or model to analyze the score obtained. Similarly, regular and ongoing monitoring is critical for a machine learning system to identify the trends and data statistics on a regular basis.

How Fraudsters Are Detected And Prevented By Using Machine Learning

Data sets are initially collected and partitioned. The machine learning model is taught the sets in order to predict data fraud. The following are the steps in which Machine Learning implements and performs fraud detection:

• Data Partitioning: The data is segmented into working in three different phases such as training the machine, testing for data sets and finally, cross-checking of the prediction results.
• Obtaining Results of Historical Data: To obtain such data sets, training sets have to be first provided to the machine that includes input values associated with its corresponding output values. This helps in predicting and detecting frauds.
• Predicting Anomalies, If Any: Based on the input and output data, predictions are determined by analyzing the anomalies or fraud cases in the data sets. For this, building models are used. This can be done by many techniques such as using Decision Trees, Logistic Regression, Neural Networks, and Random Forests, etc.
• Out of the techniques, Neural Networks are quick in processing results by analyzing data sets and helps in making decisions in real-time. It does so by observing regular patterns of frauds in earlier cases of data sets given to it for learning.

In a nutshell, Machine Learning is proving to be the right technology in detecting and preventing fraudsters from malicious activities. If banks start using machine learning systems, it could analyze unstructured data and prevent customer’s accounts from fraudulent activities. To know more about how you can empower machine learning and other technology trends to secure data, get in touch with our custom software development experts today!

There were times when common banking activities like withdrawal of money or deposit of money meant time-consuming visits to the bank and waiting in line for hours. As inconvenient and troublesome as that was, it also meant less risk of being cheated and less chances of theft of personal information. Today, we have banking at our fingertips, with mobile banking applications. What we used to do in probably three to four hours earlier, can be done now with a few simple clicks or taps in a matter of seconds and that too from anywhere in the world if you have a smart device and the internet. But how secure are these mobile banking apps and online transactions? Could someone be stealing all the information you send out through such apps?

The truth is that there are various risks of being victims to such cyber attacks, but thankfully mobile banking apps these days are made with several layers of protection and it would take considerable effort for a thief to break in through all of that. Nevertheless, there are some things that you should do too, to make sure that your information is safe and protected while using mobile banking apps. Here’s what you should do for a safe banking experience online:

1. Avoid following links and thus phishing – Phishing refers to the practice of acquiring personal and important information such as passwords, usernames and the like by pretending to be a trustworthy person or entity. It basically involves tricking someone into providing sensitive information and then using that information for malicious practices. It is in a way similar to actual ‘fishing’ as both of them involve bait to lure the victim into the trap. The bait in phishing could be a simple text message with an internet link or an email, or even a website, which could even look like your bank’s website (spoofing). You should never follow links on such emails and messages. According to the Federal Trade Commission, these are the most common ways that scammers use to steal private information from you. Legitimate companies and banks never ask for credit or debit card numbers, passwords or social security numbers and the like through emails and texts, so if you see a message somewhat like this:
   “We suspect an unauthorized transaction on your account. To ensure that your account is not compromised, please click the link below and confirm your identity.”
   DO NOT click on the link.
2. Download only the official banking app from a reputed site or store – Most leading banks offer their official applications on most smartphone app stores. For a fact, such apps are a lot more safe and secure than other apps and are definitely better than sending SMSs and emails. Banks actually go a long way to ensure that any information entered and sent across through their apps is encrypted. Hence make sure you download only the official app and only from leading well-known app marketplaces, like that of Google’s and Apple’s. Your bank will probably have information about their official app on their website, which you can use to verify the credibility of the app you are about to download.
3. Avoid banking through public networks – Public WiFi networks are often not that secure. Even simple banking activities like checking your balance can make your private information vulnerable over the network. Most places that offer such WiFi or hotspot networks often advise their users not to share private information through it. It is always better to switch to your phone’s network in case you have to use your banking app while in a public network, as fraudsters and thieves could also be using the same network and may be waiting to steal your information. Some phones allow automatic switching to WiFi once they are in range of an open one. Hence, make sure you are not on a public network before using online banking apps or sharing any private, sensitive data.
4. Avoid having personal data on your phone – For the same reason that your phone is the most convenient tool that you can easily carry around everywhere, it also proves to be sort of a risk sometimes. Your phone can have all kinds of information, like your calendar appointments, your passwords and your contacts. Such information can be read by other apps and other devices if not properly monitored and can be used against you. It also means you should be careful about where you leave your phone. Try avoiding maintaining private information on your phone as much as possible. If at all you have to, make sure you have several layers of protection for your phone. This will at least give you some time to lock your phone in case it gets stolen or lost.
5. Make sure you have an updated anti-virus system – Keeping your system up to date with the latest software along with the latest security patches can actually help a great deal in keeping away malicious software and people. It is also good to download an appropriate, trusted antivirus program for your phone as well. That adds as an extra layer of protection to the phone as well.

Keeping all these points in mind, you can very well use mobile banking apps safely. All you need to do is be a little careful and alert. In spite of all this, if you happen to lose your phone, you have the Federal Laws to the rescue. According to CNN, you can recover your losses with a limit of $50 if you report the loss within two days of its discovery. Several banks apparently already have policies in place, that waive the liability completely. Even then, prevention is better than cure, so it’s always better to avoid theft and follow these simple steps while using mobile banking apps.

Some marketing campaigns are hilarious and others heartbreaking, whatever they are, they are interruptive for sure- because it makes you stop by and notice! To justify the statement, you may think digital marketing campaigns should always be the most attractive and catchy. But that is not often the case. For instance, the banking and finance industry is one of those industries in which you cannot really make use of a lot of creativity and colorful marketing campaigns. Whether it is a social media campaign or any other kind of digital marketing technique, you need to put in a lot of thought, while also keeping in mind the various regulations governing the financial industry. So, how exactly can you go about digital marketing for this industry?

Here are some tips:

• Talking to customers about more than just banking – Whether it is through the social media or through any other digital marketing channels like e-mails or websites, it is important to keep your customers engaged. It is true that talking to customers about events and activities in the banking industry can be rather less exciting and it might be difficult to keep the customers engaged. Hence, you need to make an effort to think beyond the financial perspective of what you can do for your customers and get them talking about what they might be interested in or what they can relate to. For example, you could ask questions through your facebook page to get to know your customers’ opinions on general matters of interest like events that happened in their city etc.
• Adding a little color – When using social platforms for marketing, make sure that you talk in their language. Connect with them and communicate with them like they do. If you make your communication formal, on any social platform, it will turn out to be an extension of your website and people will lose interest. Hence, you can share pictures or videos of events in banks or of new services provided, and engage with customers in a meaningful way. For example, Wells Fargo has posted pictures of the last signs switching over through a social media channel when they transitioned the last of their Wachovia branches over, instead of sharing a press release about the same.
• Organizing contests – Contests have always proved to be one of the most effective ways to engage with customers. You can have contests on any digital marketing channel, although it might be most effective on a social networking channel. Contests, again help you connect with and keep regular contact with your customers. For example, HSBC Students had promoted their scholarship contest through social networking channels and it triggered an overwhelming response within their community.
• Highlighting success stories – What could be more effective for promotion than a genuine third party endorsement. Rather than having self promotional ads, you can have some of your existing customers share online, their experiences with your bank. You can identify some of your customers whom you’ve had the longest relationship with, or some with a unique story etc. and share them through your digital marketing channel. If you share these stories in a creative and fun way, you can have your customers interacting and engaging in no time.

These are some things you can do while carrying out your digital marketing campaigns. In order to increase the effectiveness it can be accompanied by other regular marketing campaigns as well like partnering with colleges or universities etc. Marketing for banks and financial institutions, even though is a tough job, if done properly and thoughtfully, can generate best results.