Category Archives: Financial Services
Data Governance, the art of being Regulation Ready is about a lot of things, but one thing is clear. It’s NOT just about the technology. You ever been in one of those meetings, probably more than a few, where committees and virtual teams discuss the latest corporate initiatives? You know, those meetings where you want to dip your face in lava and run into the ocean? Because at the end of the meeting, everyone goes back to their day jobs and nothing changes.
Now comes a new law or regulation from the governing body du jour. There are common threads to each and every regulation related to data. Laws like HIPAA even had entire sections dedicated to the types of filing cabinets required in the office to protect healthcare data. And the same is true of regulations like BCBS 239, CCAR reporting and Solvency II. The laws ask; what are you reporting, how did you get that data, where has it been, what does this data mean and who has touched it. Virtually all of the regulations dealing with data have those elements.
So it behooves an organization to be Regulation Ready. This means those committees and virtual teams need to be driving cultural and process change. It’s not just about the technology; it’s as much about people and processes. Every role in the organization, from the developer to the business executive should embed the concepts of data governance in their daily work. From the time a developer or architect builds a new system, they need to document and define everything and every piece of data. It reminds me of days writing code and remembering to comment each code block. And the business executive likewise is sharing business rules and definition from the top so they can be integrated into the systems that eventually have to report on it.
Finally, the processes that support a data governance program are augmented by the technology. It may seem to suffice, that systems are documented in spreadsheets and documents, but those are more and more error prone and in the end not reliable in audit.
Informatica is the market leader in data management infrastructure to be Regulation Ready. This means, everything, from data movement and quality to definitions and security. Because at the end of the day, once you have the people culturally integrated, and the processes supporting the data workload, a centralized, high performance and feature rich technology needs to be in place to complete the trifecta. Informatica is pleased to offer the industry this leading technology as part of a comprehensive data governance foundation.
Informatica will be sharing this vision at the upcoming Annual FIMA 2015 Conference in Boston from March 30 to April 1. Come and visit Informatica at FIMA 2015 in Booth #3.
The problem many banks encounter today is that they have vast sums of investment tied up in old ways of doing things. Historically, customers chose a bank and remained ’loyal’ throughout their lifetime…now competition is rife and loyalty is becoming a thing of a past. In order to stay ahead of the competition, gain and keep customers, they need to understand the ever-evolving market, disrupt norms and continue to delight customers. The tradition of staying with one bank due to family convention or from ease has now been replaced with a more informed customer who understands the variety of choice at their fingertips.
Challenger Banks don’t build on ideas of tradition and legacy and see how they can make adjustments to them. They embrace change. Longer-established banks can’t afford to do nothing, and assume their size and stature will attract customers.
Here’s some useful information
Accenture’s recent report, The Bank of Things, succinctly explains what ‘Customer 3.0’ is all about. The connected customer isn’t necessarily younger. It’s everybody. Banks can get to know their customers better by making better use of information. It all depends on using intelligent data rather than all data. Interrogating the wrong data can be time-consuming, costly and results in little actionable information.
When an organisation sets out with the intention of knowing its customers, then it can calibrate its data according with where the gold nuggets – the real business insights – come from. What do people do most? Where do they go most? Now that they’re using branches and phone banking less and less – what do they look for in a mobile app?
Customer 3.0 wants to know what the bank can offer them all-the-time, on the move, on their own device. They want offers designed for their lifestyle. Correctly deciphered data can drive the level of customer segmentation that empowers such marketing initiatives. This means an organisation has to have the ability and the agility to move with its customers. It’s a journey that never ends -technology will never have a cut-off point just like customer expectations will never stop evolving.
It’s time for banks to re-shape banking
Informatica have been working with major retail banks globally to redefine banking excellence and realign operations to deliver it. We always start by asking our customers the revealing question “Have you looked at the art of the possible to future-proof your business over the next five to ten years and beyond?” This is where the discussion begins to explore really interesting notions about unlocking potential. No bank can afford to ignore them.
On March 25th, Josh Lee, Global Director for Insurance Marketing at Informatica and Cindy Maike, General Manager, Insurance at Hortonworks, will be joining the Insurance Journal in a webinar on “How to Become an Analytics Ready Insurer”.
Register for the Webinar on March 25th at 10am Pacific/ 1pm Eastern
Josh and Cindy exchange perspectives on what “analytics ready” really means for insurers, and today we are sharing some of our views (join the webinar to learn more). Josh and Cindy offer perspectives on the five questions posed here. Please join Insurance Journal, Informatica and Hortonworks on March 25th for more on this exciting topic.
See the Hortonworks site for a second posting of this blog and more details on exciting innovations in Big Data.
- What makes a big data environment attractive to an insurer?
CM: Many insurance companies are using new types of data to create innovative products that better meet their customers’ risk needs. For example, we are seeing insurance for “shared vehicles” and new products for prevention services. Much of this innovation is made possible by the rapid growth in sensor and machine data, which the industry incorporates into predictive analytics for risk assessment and claims management.
Customers who buy personal lines of insurance also expect the same type of personalized service and offers they receive from retailers and telecommunication companies. They expect carriers to have a single view of their business that permeates customer experience, claims handling, pricing and product development. Big data in Hadoop makes that single view possible.
JL: Let’s face it, insurance is all about analytics. Better analytics leads to better pricing, reduced risk and better customer service. But here’s the issue. Existing data sources are costly in storing vast amounts of data and inflexible to adapt to changing needs of innovative analytics. Imagine kicking off a simulation or modeling routine one evening only to return in the morning and find it incomplete or lacking data that requires a special request of IT.
This is where big data environments are helping insurers. Larger, more flexible data sets allowing longer series of analytics to be run, generating better results. And imagine doing all that at a fraction of the cost and time of traditional data structures. Oh, and heaven forbid you ask a mainframe to do any of this.
- So we hear a lot about Big Data being great for unstructured data. What about traditional data types that have been used in insurance forever?
CM: Traditional data types are very important to the industry – it drives our regulatory reporting and much of the performance management reporting. This data will continue to play a very important role in the insurance industry and for companies.
However, big data can now enrich that traditional data with new data sources for new insights. In areas such as customer service and product personalization, it can make the difference between cross-selling the right products to meet customer needs and losing the business. For commercial and group carriers, the new data provides the ability to better analyze risk needs, price accordingly and enable superior service in a highly competitive market.
JL: Traditional data will always be around. I doubt that I will outlive a mainframe installation at an insurer; which makes me a little sad. And for many rote tasks like financial reporting, a sales report, or a commission statement, those are sufficient. However, the business of insurance is changing in leaps and bounds. Innovators in data science are interested in correlating those traditional sources to other creative data to find new products, or areas to reduce risk. There is just a lot of data that is either ignored or locked in obscure systems that needs to be brought into the light. This data could be structured or unstructured, it doesn’t matter, and Big Data can assist there.
- How does this fit into an overall data management function?
JL: At the end of the day, a Hadoop cluster is another source of data for an insurer. More flexible, more cost effective and higher speed; but yet another data source for an insurer. So that’s one more on top of relational, cubes, content repositories, mainframes and whatever else insurers have latched onto over the years. So if it wasn’t completely obvious before, it should be now. Data needs to be managed. As data moves around the organization for consumption, it is shaped, cleaned, copied and we hope there is governance in place. And the Big Data installation is not exempt from any of these routines. In fact, one could argue that it is more critical to leverage good data management practices with Big Data not only to optimize the environment but also to eventually replace traditional data structures that just aren’t working.
CM: Insurance companies are blending new and old data and looking for the best ways to leverage “all data”. We are witnessing the development of a new generation of advanced analytical applications to take advantage of the volume, velocity, and variety in big data. We can also enhance current predictive models, enriching them with the unstructured information in claim and underwriting notes or diaries along with other external data.
There will be challenges. Insurance companies will still need to make important decisions on how to incorporate the new data into existing data governance and data management processes. The Chief Data or Chief Analytics officer will need to drive this business change in close partnership with IT.
- Tell me a little bit about how Informatica and Hortonworks are working together on this?
JL: For years Informatica has been helping our clients to realize the value in their data and analytics. And while enjoying great success in partnership with our clients, unlocking the full value of data requires new structures, new storage and something that doesn’t break the bank for our clients. So Informatica and Hortonworks are on a continuing journey to show that value in analytics comes with strong relationships between the Hadoop distribution and innovative market leading data management technology. As the relationship between Informatica and Hortonworks deepens, expect to see even more vertically relevant solutions and documented ROI for the Informatica/Hortonworks solution stack.
CM: Informatica and Hortonworks optimize the entire big data supply chain on Hadoop, turning data into actionable information to drive business value. By incorporating data management services into the data lake, companies can store and process massive amounts of data across a wide variety of channels including social media, clickstream data, server logs, customer transactions and interactions, videos, and sensor data from equipment in the field.
Matching data from internal sources (e.g. very granular data about customers) with external data (e.g. weather data or driving patterns in specific geographic areas) can unlock new revenue streams.
See this video for a discussion on unlocking those new revenue streams. Sanjay Krishnamurthi, Informatica CTO, and Shaun Connolly, Hortonworks VP of Corporate Strategy, share their perspectives.
- Do you have any additional comments on the future of data in this brave new world?
CM: My perspective is that, over time, we will drop the reference to “big” or ”small” data and get back to referring simply to “Data”. The term big data has been useful to describe the growing awareness on how the new data types can help insurance companies grow.
We can no longer use “traditional” methods to gain insights from data. Insurers need a modern data architecture to store, process and analyze data—transforming it into insight.
We will see an increase in new market entrants in the insurance industry, and existing insurance companies will improve their products and services based upon the insights they have gained from their data, regardless of whether that was “big” or “small” data.
JL: I’m sure that even now there is someone locked in their mother’s basement playing video games and trying to come up with the next data storage wave. So we have that to look forward to, and I’m sure it will be cool. But, if we are honest with ourselves, we’ll admit that we really don’t know what to do with half the data that we have. So while data storage structures are critical, the future holds even greater promise for new models, better analytical tools and applications that can make sense of all of this and point insurers in new directions. The trend that won’t change anytime soon is the ongoing need for good quality data, data ready at a moment’s notice, safe and secure and governed in a way that insurers can trust what those cool analytics show them.
Please join us for an interactive discussion on March 25th at 10am Pacific Time/ 1pm Eastern Time.
Register for the Webinar on March 25th at 10am Pacific/ 1pm Eastern
In honor of International Women’s Day 2015, Informatica is celebrating female leadership in a blog series. Every day this week, we will showcase a new female leader at Informatica, who will share their perspective on what it’s like to be a woman in the tech industry.
Area Vice President for US Financial Services
Women bring different perspectives to all situations. Sometimes it’s welcomed and sometimes it’s not embraced because it’s outside of the norm – which actually makes it of even greater value. The technology field is still dominated by men. Many times I am the only woman in the room and most times I am the only woman in a position of leadership; this also presents a unique opportunity to stand out.
It has been a long haul to get to where I am today with many stories of great successes and some real misses. Those “misses” always lead me to the vow of “never again” and to exceed in new ways. Today I have the confidence that my “different perspective” will change the course of things. I am unapologetic for my ideas or directions even though they may be contrary to the norm. I am grateful to have been given the chance to work personally with leaders in the tech industry and been given opportunities that stretched me beyond what I believed my own capabilities to be. Only to realize I am more than capable and actually able to move beyond.
As a leader, the most critical aspect is to build a management team that complements my own skills.
- Diversity in talent is important so that we leverage each other’s strengths.
- Open communication is a critical aspect to my leadership and success.
- Honoring and respecting what each individual brings to their teams – while giving just enough guidance, has led to ensuring forward momentum, having ultimate buy-in to what we do, and delivering consistent contributions – all of which is the foundation for great success.
Advice for women:
Put yourself out there. Be bold. Take your seat at the table in a big way! Have mentors. Know who to trust (and who not). Create a network of colleagues. Always help other women succeed.
Thoughts about Informatica’s culture:
Informatica is a great place to be. I wake up every day, passionate about what I do and excited about the difference that my team and I are making for our company and for our customers. We have a culture of integrity, excellence and innovation. This translates in everything we do. As we are critical in some many transformational initiatives for our customers. Who we are has been the basis for how we have delivered for our customers time and time again. Now with the future being all things ‘data’, Informatica will be instrumental in helping our customers leapfrog to their next level of growth. This is the best time to be part of Informatica.
At long last, the anxiously awaited rules from the FAA have brought some clarity to the world of commercial drone use. Up until now, commercial drone use has been prohibited. The new rules, of course, won’t sit well with Amazon who would like to drop merchandise on your porch at all hours. But the rules do work really well for insurers who would like to use drones to service their policyholders. So now drones, and soon to be fleets of unmanned cars will be driving the roadways in any numbers of capacities. It seems to me to be an ambulance chaser’s dream come true. I mean who wouldn’t want some seven or eight figure payday from Google for getting rear-ended?
What about “Great Data”? What does that mean in the context of unmanned vehicles, both aerial and terrestrial? Let’s talk about two aspects. First, the business benefits of great data using unmanned drones.
An insurance adjuster or catastrophe responder can leverage an aerial drone to survey large areas from a central location. They will pin point the locations needing attention for further investigation. This is a common scenario that many insurers talk about when the topic of aerial drone use comes up. Second to that is the ability to survey damage in hard to reach locations like roofs or difficult terrain (like farmland). But this is where great data comes into play. Surveying, service and use of unmanned vehicles demands that your data can answer some of the following questions for your staff operating in this new world:
Where am I?
Quality data and geocoded locations as part of that data is critical. In order to locate key risk locations, your data must be able to coordinate with the lat/long of the location recorded by your unmanned vehicles and the location of your operator. Ensure clean data through robust data quality practices.
Where are my policyholders?
Knowing the location of your policyholders not only relies on good data quality, but on knowing who they are and what risks you are there to help service. This requires a total customer relationship solution where you have a full view of not only locations, but risks, coverages and entities making up each policyholder.
What am I looking at?
Archived, current and work in process imaging is a key place where a Big Data environment can assist over time. By comparing saved images with new and processing claims, claims fraud and additional opportunities for service can be detected quickly by the drone operator.
Now that we’ve answered the business value questions and leveraged this new technology to better service policyholders and speed claims, let’s turn to how great data can be used to protect the insurer and drone operator from liability claims. This is important. The FAA has stopped short of requiring commercial drone operators to carry special liability insurance, leaving that instead to the drone operators to orchestrate with their insurer. And now we’re back to great data. As everyone knows, accidents happen. Technology, especially robotic mobile technology is not infallible. Something will crash somewhere, hopefully not causing injury or death, but sadly that too will likely happen. And there is nothing that will keep the ambulance chasers at bay more than robust great data. Any insurer offering liability cover for a drone operator should require that some of the following questions be answered by the commercial enterprise. And the interesting fact is that this information should be readily available if the business questions above have been answered.
- Where was my drone?
- What was it doing?
- Was it functioning properly?
Properly using the same data management technology as in the previous questions will provide valuable data to be used as evidence in the case of liability against a drone operator. Insurers would be wise to ask these questions of their liability policyholders who are using unmanned technology as a way to gauge liability exposure in this brave new world. The key to the assessment of risk being robust data management and great data feeding the insurer’s unmanned policyholder service workers.
Time will tell all the great and imaginative things that will take place with this new technology. One thing is for certain. Great data management is required in all aspects from amazing customer service to risk mitigation in operations. Happy flying to everyone!!
I recently read an opinion piece written in an insurance publication online. The author postulated, among other things, that the Internet of Things would magically deliver great data to an insurer. Yes, it was a statement just that glib. Almost as if there is some fantastic device that you just plug into the wall and out streams a flow of unicorns and rainbows. And furthermore that those unicorns and rainbows will subsequently give a magical boost to your business. But hey, you plugged in that fantastic device, so bring on the magic.
Now, let’s come back from the land of fairytales and ground ourselves in reality. Data is important, no doubt about that. Today, financial services firms are able to access data from so many new data sources. One of those new and fancy data sources is the myriad of devices in this thing we call the Internet of Things.
You ever have one of those frustrating days with your smart phone? Dropped calls, slow Internet, Facebook won’t locate you? Well, other devices experience the same wonkiness. Even the most robust of devices found on commercial aircraft or military equipment are not lossless in data transmission. And that’s where we are with the Internet of Things. All great devices, they serve a number of purposes, but are still fallible in communicating with the “mother ship”.
A telematics device in a consumer vehicle can transmit, VIN, speed, latitude/longitude, time, and other vehicle statuses for use in auto insurance. As with other devices on a network, some of these data elements will not come through reliably. That means that in order to reconstruct or smooth the set of data, interpolations need to be made and/or entire entries deleted as useless. That is the first issue. Second, simply receiving this isolated dataset does not make sense of it. The data needs to be moved, cleansed and then correlated to other pieces of the puzzle, which eventually turn into a policyholder, an account holder, a client or a risk. And finally, that enhanced data can be used for further analytics. It can be archived, aggregated, warehoused and secured for additional analysis. None of these activities happen magically. And the sheer volume of integration points and data requires a robust and standardized data management infrastructure.
So no, just having an open channel to the stream of noise from your local Internet of Things will not magically deliver you great data. Great data comes from market leading data management solutions from Informatica. So whether you are an insurance company, financial services firm or data provider, being “Insurance Ready” means having great data; ready to use; everywhere…from Informatica.
Happy Holidays, Happy HoliData
In case you have missed our #HappyHoliData series on Twitter and LinkedIn, I decided to provide a short summary of best practices which are unleashing information potential. Simply scroll and click on the case study which is relevant for you and your business. The series touches on different industries and use cases. But all have one thing in common: All consider information quality as key value to their business to deliver the right services or products to the right customer.
Thanks a lot to all my great teammates, who made this series happen.
Happy Holidays, Happy HoliData.
A couple months ago, I reached out to a set of CIOs on the importance of good governance and security. All of them agreed that both were incredibly important. However, one CIO retorted a very pointed remark by saying that “the IT leadership at these breached companies wasn’t stupid.” He continued by saying that when selling the rest of the C-Suite, the discussion needs to be about business outcomes and business benefits. For this reason, he said that CIOs have struggled at selling the value of investments in governance and security investment. Now I have suggested previously that security pays because of the impact on “brand promise”. And, I still believe this.
However, this week the ante was raised even higher. A district judge ruled that a group of banks can proceed to sue a retailer for negligence in their data governance and security. The decision could clearly lead to significant changes in the way the cost of fraud is distributed among parties within the credit card ecosystem. Where once banks and merchant acquirers would have shouldered the burden of fraud, this decision paves the way for more card-issuing banks to sue merchants for not adequately protecting their POS systems.
The judge’s ruling said that “although the third-party hackers’ activities caused harm, merchant played a key role in allowing the harm to occur.” The judge also determined that the bank suit against merchants was valid because the plaintiffs adequately showed that the retailer failed “to disclose that its data security systems were deficient.” This is interesting because it says that security systems should be sufficient and if not, retailers need to inform potentially affected stakeholders of their deficient systems. And while taking this step could avoid a lawsuit, it would likely increase the cost of interchange for more risky merchants. This would effectively create a risk premium for retailers that do not adequately govern and protect their IT environments.
There are broad implications for all companies who end up harming customer, partners, or other stakeholders by not keeping their security systems up to snuff. The question is, will this make good governance have enough of a business outcome and benefit that businesses will actually want to pay it forward — i.e. invest in good governance and security? What do you think? I would love to hear from you.
As I indicated in my last case study regarding competing on analytics, Thomas H. Davenport believes “business processes are among the last remaining points of differentiation.” For this reason, Davenport contends that businesses that create a sustainable right to win use analytics to “wring every last drop of value from their processes”. For financial services, the mission critical areas needing process improvement center are around improving the consistency of decision making and making the management of regulatory and compliance more efficient and effective.
Why does Fannie Mae need to compete on analytics?
Fannie Mae is in the business of enabling people to buy, refinance, or rent homes. As a part of this, Fannie Mae says it is all about keeping people in their homes and getting people into new homes. Foundational to this mission is the accurate collection and reporting of data for decision making and risk management. According to Tracy Stephan at Fannie Mae, their “business needs to have the data to make decisions in a more real time basis. Today, this is all about getting the right data to the right people at the right time”.
Fannie Mae claims when the mortgage crisis hit, a lot of the big banks stopped lending and this meant that Fannie Mae among others needed to pick up the slack. Their action here, however, caused the Federal Government to require them to report monthly and quarterly against goals that the Federal Government set for it. “This meant that there was not room for error in how data gets reported”. In the end, Fannie Mae says three business imperatives drove it’s need to improve its reporting and its business processes:
- To ensure that go forward business decisions were made consistently using the most accurate business data available
- To avoid penalties by adhering to Dodd-Frank and other regulatory requirements established for it after the 2008 Global Financial Crisis
- To comply with reporting to Federal Reserve and Wall Street regarding overall business risk as a function of: data quality and accuracy, credit-worthiness of loans, and risk levels of investment positions.
Delivering required Fannie Mae to change how it managed data
Given these business imperatives, IT leadership quickly realized it needed to enable the business to use data to truly drive better business processes from end to end of the organization. However, this meant enabling Fannie Mae’s business operations teams to more effectively and efficiently manage data. This caused Fannie Mae to determine that it needed a single source of truth whether it was for mortgage applications or the passing of information securely to investors. This need required Fannie Mae to establish the ability to share the same data across every Fannie Mae repository.
But there was a problem. Fannie Mae needed clean and correct data collected and integrated from more than 100 data sources. Fannie Mae determined that doing so with its current data processes could not scale. And as well, it determined that its data processes would not allow it to meet its compliance reporting requirements. At the same time, Fannie Mae needed to deliver more proactive management of compliance. This required that it know how critical business data enters and flows through each of its systems. This includes how data was changed by multiple internal processing and reporting applications. As well, Fannie Mae leadership felt that this was critical to ensure traceability to the individual user.
Per its discussions with business customers, Fannie Mae’s IT leadership determined that it needed to get real time, trustworthy data to improve its business operations and to improve its business processes and decision making. As said, these requirements could not be met with its historical approaches to integrating and managing data.
Fannie Mae determined that it needed to create a platform that was high availability, scalable, and largely automating its management of data quality management. At the same time, the platform needed to provide the ability to create a set of business glossaries with clear data lineages. Fannie Mae determined it needed effectively a single source of truth across all of its business systems. According to Tracy Stephan, IT Director, Fannie Mae, “Data quality is the key to the success of Fannie Mae’s mission of getting the right people into the right homes. Now all our systems look at the same data – that one source of truth – which gives us great comfort.” To learn more specifics about how Fannie Mae improved its business processes and demonstrated that it is truly “data driven”, please click on this video of their IT leadership.
Solution Brief: The Intelligent Data Platform
Thomas Davenport Book “Competing On Analytics”
Competing on Analytics
The Business Case for Better Data Connectivity
The CFO Viewpoint upon Data
What an enlightened healthcare CEO should tell their CIO?
This was a great week of excitement and innovation here in San Francisco starting with the San Francisco Giants winning the National League Pennant for the 3rd time in 5 years on the same day Saleforce’s Dreamforce 2014 wrapped up their largest customer conference with over 140K+ attendees from all over the world talking about their new Customer Success Platform.
Salesforce has come a long way from their humble beginnings as the new kid on the cloud front for CRM. The integrated sales, marketing, support, collaboration, application, and analytics as part of the Salesforce Customer Success Platform exemplifies innovation and significant business value upside for various industries however I see it very promising for today’s financial services industry. However like any new business application, the value business gains from it are dependent in having the right data available for the business.
The reality is, SaaS adoption by financial institutions has not been as quick as other industries due to privacy concerns, regulations that govern what data can reside in public infrastructures, ability to customize to fit their business needs, cultural barriers within larger institutions that critical business applications must reside on-premise for control and management purposes, and the challenges of integrating data to and from existing systems with SaaS applications. However, experts are optimistic that the industry may have turned the corner. Gartner (NYSE:IT) asserts more than 60 percent of banks worldwide will process the majority of their transactions in the cloud by 2016. Let’s take a closer look at some of the challenges and what’s required to overcome these obstacles when adopting cloud solutions to power your business.
Challenge #1: Integrating and sharing data between SaaS and on-premise must not be taken lightly
For most banks and insurance companies considering new SaaS based CRM, Marketing, and Support applications with solutions from Salesforce and others must consider the importance of migrating and sharing data between cloud and on-premise applications in their investment decisions. Migrating existing customer, account, and transaction history data is often done by IT staff through the use of custom extracts, scripts, and manual data validations which can carry over invalid information from legacy systems making these new application investments useless in many cases.
For example, customer type descriptions from one or many existing systems may be correct in their respective databases however collapsing them into a common field in the target application seems easy to do. Unfortunately, these transformation rules can be complex and that complexity increases when dealing with tens if not hundreds of applications during the migration and synchronization phase. Having capable solutions to support the testing, development, quality management, validation, and delivery of existing data from old to new is not only good practice, but a proven way of avoiding costly workarounds and business pain in the future.
Challenge 2: Managing and sharing a trusted source of shared business information across the enterprise.
As new SaaS applications are adopted, it is critical to understand how to best govern and synchronize common business information such as customer contact information (e.g. address, phone, email) across the enterprise. Most banks and insurance companies have multiple systems that create and update critical customer contact information, many of them which reside on-premise. For example, insurance customers who update contact information such as a phone number or email address while filing an insurance claim will often result in that claims specialist to enter/update only the claims system given the siloed nature of many traditional banking and insurance companies. This is the power of Master Data Management which is purposely designed to identify changes to master data including customer records in one or many systems, update the customer master record, and share that across other systems that house and require that update is essential for business continuity and success.
In conclusion, SaaS adoption will continue to grow in financial services and across other industries. The silver lining in the cloud is your data and the technology that supports the consumption and distribution of it across the enterprise. Banks and insurance companies investing in new SaaS solutions will operate in a hybrid environment made up of Cloud and core transaction systems that reside on-premise. Cloud adoption will continue to grow and to ensure investments yield value for businesses, it is important to invest in a capable and scalable data integration platform to integrate, govern, and share data in a hybrid eco-system. To learn more on how to deal with these challenges, click here and download a complimentary copy of the new “Salesforce Integration for Dummies”