At the end of February, ClearBank – the first clearing bank to enter the UK market in more than 250 years – confirmed that it is running its core operations on the Microsoft Cloud platform.

Built from the ground up on a combined public and private cloud infrastructure, the bank says that its modern platform will enable it to offer new competitive transactional banking services more cost effectively and efficiently when it opens for business this coming autumn.

“There are thousands of new fintech startups and challenger banks improving choice, but the industry will never truly move forward while it’s constrained by the challenges of legacy operational structures,” said Nick Ogden, ClearBank’s executive chairman, during the launch event on 28 February. “Figures from the Cruickshank Report indicate that, with the improved efficiency delivered by ClearBank’s built-for-purpose technology, between £2bn and £3bn could be saved from the annual costs that are paid for transactional banking in the UK.”

Similar success stories are being told across the financial services industry and beyond.

US life insurance company MetLife is taking advantage of Microsoft Azure to run complex actuarial simulation models, delivering high quality actuarial insights with incredible speed to decision makers around the globe. This is resulting in an improved customer experience and business decision making process, with an expected 45-55% saving in infrastructure costs.

And, thanks to the Microsoft Dynamics 365 platform, Metro Bank in the UK is able to provide employees with immediate access to information, such as branch traffic patterns or a customer’s account activity. “Technology should be used to engage people and that’s what we do at Metro Bank,” says CEO Craig Donaldson.

Speaking at the FinTech Ideas Festival in San Francisco, US, Nadella explained that Microsoft’s mission is grounded in empowering every person and organisation on the planet to achieve more, and that companies must not simply make digital products, but also look to engage their customers digitally.

“There is a broad spectrum of use cases of digital technology,” Nadella says. “Everyone is a digital company or software company today. The question is, how good are you at it? You’ve got to ask yourself what capability you’re building, whether it’s AI, machine learning, or the digital experience.”

For Karen Cone, who heads up Microsoft’s financial services division, the reason the digital transformation strategy is resonating with financial institutions is because it covers off two key areas of importance – it shows the opportunities to be had from cutting-edge innovation, but it also helps to tackle the challenges many businesses face here and now, related to modernising their legacy systems.

“I call it the ying and the yang,” says Cone. “On one front we’re working with financial institutions to create innovative customer and employee experiences. In this instance, it is critical that there is agility and innovation, and that company employees are digitally empowered. For example, we’re helping them to take advantage of advanced analytics, and push next best offers and actions that are relevant to individual customers.”

“But on the flipside, we’re also focused on issues such as risk management, ensuring compliance, modernising legacy systems and cost reduction,” continues Cone. “It’s about us helping financial institutions to rapidly adapt to the changes happening around them, with operational efficiency and agility.”

Microsoft customers are harnessing developments, including artificial intelligence (AI), the internet of things (IoT), and high performance computing as part of their digital transformation journey. Mitsubishi UFJ Securities International, for example, is using high-performance computing grids in Microsoft Azure to scale its compute power to support its risk computations and regulatory compliance. This has helped the company save millions of dollars in servers and data centre space. By using sensors (IoT) to collect preventative maintenance data from ATMs and analyse it in the Azure Cloud, Diebold Nixdorf has reduced its maintenance costs by 90%.

I’m particularly excited about the ever-growing potential of AI and the cloud (which is fuelling AI),” Cone says. “The promise of AI is possible now because of three key factors. The first is the vast amounts of data from devices, sensors and a world that is being digitised. More than 10 zettabytes of data were generated in 2015, and this is projected to rise to 180 ZB in 2025. AI will make it possible to sort through all this information. Second is that we now have almost limitless computing power in the cloud. And finally, we’re developing new algorithms that can make sense of and reason over all of this data.”

Developments around the application programming interface (API) economy are also allowing financial institutions to build exciting new digital experiences. “It’s giving rise to the opportunity for new partnerships – both within and outside of the industry – which could integrate many current common banking touchpoints seamlessly into more encompassing customer experiences,” Cone explains. “It’s ushering banks into a new battleground of integrated services, with the winners claiming the right to be a customer’s preferred digital point of entry into banking services. They will differentiate themselves based on insightful predictions of what customers need, taking advantage of seamless integration and assistive AI to build a full lifecycle customer purchase journey.”

As the industry continues to push forward with its innovation efforts, so too is Microsoft. “When we think about the future of technology, we believe the answer resides in the notion of intelligence,” says Cone. “We’re looking into how we can apply AI to help solve some of the biggest challenges in financial services. This includes areas like financial crime prediction, detection and prevention, risk management, personalising the customer experience and next best customer offers, and providing robo-advisory, chat bot and other innovative services.”

The company is also making good progress in areas such as blockchain. Many financial institutions are using the capabilities of over 30 fintechs in Azure’s Blockchain-a-as-Service to rapidly develop, test and prove blockchain use cases. This includes Microsoft’s own treasury department, which is working with Bank of America Merrill Lynch to explore uses of distributed ledger technology in areas such as trade financing. The company has also entered partnerships with the likes of R3, Tierion and AMIS. The latter to build Asia’s first consortium blockchain network on Azure.

“With our financial services industry solutions, global cloud, development and productivity platforms and strong enterprise focus, we’re positioned to help our customers build new business models and customer experiences, and navigate the new collaborative economy,” says Cone. “Together, we’re showing what’s possible when you have the capabilities in place to modernise legacy environments and embrace innovation, all while balancing the realities of risk, regulation and cost pressures.”

Read more on the Microsoft Banking & Capital Markets and Insurance blogs.

This article was originally published on The Record.

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Today, executives are now personally liable for any illicit transactions that slip through. Noncompliance with strict regulations can cost banks dearly – fines related to sanctions have cost US banks over $200 billion between 2008 and 2015.[i] In order to prevent crime and protect themselves from fines, banks need a rigorous sanction-screening solution that will solve the following three pain points: 

1. Ensuring compliance is difficult, because of the frequent changes to regulations and high scrutiny by regulators 
2. Maintaining a balance of meticulous and rapid screenings is a challenge, especially without interrupting legitimate customer transactions 
3. Updating sanction lists is time-consuming and tricky, especially with an inflexible system

1. Ensuring compliance is difficult

Intense regulatory scrutiny in response to terror funding and other sanctioned transactions has created immense challenges for banks. 20% of financial services have experienced enforcement actions by a regulator, and that number is likely to grow.[ii] Banks face massive fines, operational shutdowns and reputational risk if they don’t check against regulations and ensure all informational gaps are filled before a transaction occurs. And banks are not the only ones that suffer if they do not comply – their customers are experiencing an impact from the compliance crackdown as well. A bank in Asia was ordered by regulators to completely cease operations as a result of serious regulatory breaches and poor management oversight of bank operations.[iii] Customers expect compliance as a prerequisite and sign of good governance to ensure that the banks they are doing business with are not mixed up in criminal activities. 

2. Maintaining a balance of meticulous and rapid screenings is a challenge

Preventing funds from reaching sanctioned politically exposed persons (PEPs) and terrorists is difficult and comes at a high operational cost for staff and IT, especially when it must be done without disrupting legitimate transactions. Inefficient screenings with high false positive rates can cripple customer relationships – holding up a large company’s payroll just once because of a false positive with an employee’s name could cause a bank to lose important business. Overly-cautious screening systems can actually flag customers who have the same name as someone on the watch list, which might result in loss of customers if these names are treated as fraud.[iv] 

3. Updating watch lists is tricky and time-consuming

Today, there are frequent changes to the multiple watch lists that banks need to screen against to ensure they are capturing all sanctioned entities. With growing numbers of sanction lists from numerous national, regional, and global organisations, this step becomes ever-more time-consuming. The number of entities on these lists increases with each update, as do aliases and spelling variations. 

The quality of sanction lists has a direct impact on a filter’s detection capability. As lists become increasingly complicated and intertwined, they require a more sophisticated mix of screening methods and enhancement of the raw data to maintain high quality filtering. A flexible architecture and list handling system is needed in order to meet current standards and easily adapt to future requirements.

4. Addressing the pain points of transaction screening

Banks need a powerful screening tool in order to avoid illegal transactions, minimise disruption of legitimate transactions and keep up with rapidly changing watch lists. 

To avoid fines without disrupting the customer experience, they must be able to compare watch lists quickly while maintaining a low false positive rate. Screening solutions achieve this false positive rate by incorporating historical transaction data and trend analysis. Additionally, effective screens will be able to easily integrate with existing systems, so that banks don’t have to significantly alter their current IT architecture to implement the solution and keep up with new requests. 

Banks have been called upon to help stem the flow of money to sanctioned entities. Using a specialised screening solution, such as the Screen solution from Temenos, they can ensure that they successfully play their part in catching these transactions. To find out more about Temenos’ Screen solution, visit Microsoft AppSource.

Read more on the Microsoft Banking & Capital Markets and Insurance blogs.

[i] http://www.cnbc.com/2015/10/30/misbehaving-banks-have-now-paid-204b-in-fines.html
[ii] Global Economic Crime Survey, PwC, 2016
[iii] http://www.mas.gov.sg/News-and-Publications/Media-Releases/2016/MAS-directs-BSI-Bank-to-shut-down-in-Singapore.aspx
[iv] https://dealbook.nytimes.com/2014/06/15/bank-account-screening-tool-is-scrutinized-as-excessive/

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Insurance is an industry based on managing risk by interpreting data – and one that demands constant increases in compute power to meet regulatory and reporting requirements. Now that insurers have started to embrace the cloud, our customers are asking targeted questions, including:

• How do you protect my data?
• How do you use my data?
• How can you help me with my compliance needs?
• Where is my data and who has access to it?
• What do you do in response to government demands for customer data?

This really boils down to one question: ‘Why should I trust you?’

Making the right decision entails answering all of these questions, reviewing the data, analysing your needs and finding the right technology partner to enable success.

Financial regulators want the right to inspect and they want businesses to have greater control over their cloud operation environment. In many countries, regulatory bodies need to be engaged in these discussions. Even where they don’t, it’s better to be proactive and get a ‘no objection’ from the regulator than to have them reviewing and ‘not approving’ your solution.

Cloud service providers need to have a strong security foundation with appropriate practices in place to support their services – and you need the tools to authenticate, access, manage, encrypt, monitor and build on your secure solutions. Once you have all this, it’s easy to bring third parties into your virtual environment in a secure, seamless fashion.

Cloud providers must also adhere to key principles within the ISO 27018 Privacy Standard, including transparency over the handling and location of data, communication with customers and regulators in the event of a breach and giving customers control over how their data is used.

With a secure environment in place we can enable solution providers to build proven, lower-cost solutions that can seamlessly run in – or with – the cloud to bring more value to your business, your users and your bottom line. The support structure and trust required for this can only be achieved by building these industrial-sized solutions together, using the same tools and technologies from concept to delivery and beyond.

Find out more by downloading Microsoft’s Perspectives on Insurance Risk Modelling

The post Risk Modelling in Insurance: Choosing the right cloud for Insurance appeared first on Microsoft Industry Blogs - United Kingdom.

For an industry where risk prediction is the name of the game, many insurance providers are failing to recognise one of the biggest threats they face today: their own legacy systems. The cloud presents an opportunity for more powerful, secure and efficient risk modelling, but insurers remain hesitant to move forward. This is understandable, as insurance providers tend to be more conservative when it comes to the adoption of new trends.

But cloud is far more than just a trendy buzzword. It is disrupting the insurance industry and driving innovation at a breakneck pace. The rest of the world is moving to the cloud – and insurance companies that don’t adopt early run the risk of falling behind. They are likely to end up with limited modelling capabilities, costly on-premises infrastructure expansions and increased vulnerability to security breaches.

Limited computing capacity means limited modelling potential

For accurate risk modelling, speed and capacity are essential. Insurers are always pursuing solutions that will provide the computing power necessary to run models faster and which address a greater number of scenarios. However, most insurers currently lack the necessary resources. A 2014 study found that two thirds of insurers were still executing actuarial models on individual PCs and desktop apps. These tools lack the processing power needed for high-octane risk modelling.

Unprecedented amounts of data are becoming available to insurance companies, but that data is wasted without the capacity to turn it into insight. Low-capacity processers can’t handle the load from the raw data streams that contain granular customer insights. Instead, insurance agencies must resort to clunky demography and generalisations and limited analytics power decreases the accuracy of risk modelling. As a result, these firms are losing against more tech-savvy competitors that can offer precision pricing.

And greater accuracy in risk assessment isn’t just extra credit – it’s increasingly required of insurance agencies. New standards such as Solvency II, Dodd Frank and the International Financial Reporting Standards demand that insurers run more complex models more frequently. This is especially challenging for global insurance providers, who have many different regulatory demands to comply with. Most insurers can’t meet these demands with their current infrastructure and expanding existing infrastructure is costly and time-consuming.

As the amount and variety of customer-specific data available to the insurance industry grows, their computing capacities need to keep pace. Cloud technology is a powerful replacement for legacy systems. Its massive capacity for data input gives insurance firms the scale and computational power needed to perform analyses quickly and simultaneously. Combined with machine learning technology that analyses data with increasing intelligence, insurers are capable of more accurately assessing risk, customer churn and fraud.

Expanding on-premises infrastructure is prohibitively expensive

To expand computing capacity enough to meet regulations and compete in the market, insurance companies that cling to on-premises technology will have to invest in millions of dollars of infrastructure enhancements which may quickly become obsolete. Furthermore, computing needs fluctuate – an insurer may normally use 2000 cores, but need 5000–10,000 for quarterly or annual risk models. The inflexibility of on-premises models means that firms are either sitting on unused capacity or unable to meet unexpected spikes in demand.

Insurers need a solution that is both flexible and cost-effective. Cloud computing gives firms access to tremendous computing power as they need it. SaaS solutions with consumption-model pricing allow for flexibility and total cost of ownership is significantly lower. Businesses can expect to save significantly on their IT costs just by moving their infrastructure to the cloud.

Legacy systems are more vulnerable to attack

It’s natural for insurance companies to be concerned about the risk of working in the cloud. But in most instances, companies find that the cloud provider has more stringent security standards and requirements than their own datacentre. Few individual organisations can replicate the technology safeguards and operational processes that technology providers like Microsoft have developed to protect enterprise cloud services and comply with a wide range of international standards.

MetLife

Forward-thinking insurance companies are acknowledging the risks inherent to legacy technology and taking steps to stay ahead of the curve. MetLife is one of these early adopters. Serving 100 million customers in almost 50 countries, MetLife is one of the largest life insurance companies in the world. MetLife created a processing environment called MetLife Integrated Actuarial Modelling Environment (MIAME), an end-to-end high-performance computing grid-based solution on Microsoft HPC Pack, Windows Server, Microsoft Analytics Platform System and Microsoft SQL Server. To increase compute capacity, speed and performance while reducing costs, MetLife shifted some of the heavy lifting of the high-performance computing and data processing required by MIAME to the Microsoft Azure cloud platform. That enables MetLife to take full advantage of the flexibility and scalability of its data processing capabilities to achieve faster, more accurate actuarial calculations and save significant infrastructure costs, resulting in more value for the customer and the company.

Because MetLife needed a platform that integrated well with its existing tools and processes, the Microsoft Azure cloud computing platform was its first choice. By taking advantage of Azure for processing the massive and complex financial calculations MetLife needs to perform each month, the company can achieve several goals. During peak times, MIAME can scale exponentially to meet business and regulatory needs, which enables faster delivery. By using the Microsoft cloud rather than continuing to build out its own calculation infrastructure, MetLife expects to save 45 to 55% in infrastructure costs that it might otherwise incur to meet reporting timeframes. This also creates year-over-year savings for the company.

Out-computing risk with the Microsoft cloud

Given the massive savings and precision potential that companies like MetLife have seen by adopting cloud computing, the technology is increasingly becoming a requirement rather than a choice for insurance companies. Microsoft Azure, a leading public cloud platform, offers superior risk modelling capacity. Azure delivers powerful analytics capabilities combined with a cloud-based environment that address the limitations of legacy systems and older ISV applications that require regular servicing. With unmatched scalability, flexible consumption-model pricing and the availability of both hybrid and cloud environments, Azure enables customers to offload technology requirements to Microsoft, while maintaining control over their data. Microsoft’s partnerships with solution providers such as Willis Towers Watson, Milliman, FIS and GGY are always growing, demonstrating the breadth of services that Azure can offer the insurance industry.

Microsoft has made significant investments to build out a platform with the security, privacy, compliance and transparency required for the financial services industry. When companies use Azure, they benefit from Microsoft’s unmatched scale and experience running compliant online services around the globe. Azure meets a broad set of international and industry-specific compliance standards, such as FISC, IRS 1075 and PCI DSS Level 1. You can read more about our practices by visiting the Microsoft Azure Trust Centre, which provides detailed security, privacy and compliance information about our cloud services to help customers make their own regulatory assessments.

Insurance firms that are hesitant to embrace the cloud will find themselves falling behind in terms of risk modelling capacity, struggling to keep up with regulatory standards and more vulnerable to security threats. The risks of sticking with outdated IT are matched only by the opportunities of cloud and machine learning. Learn more today about what Azure cloud computing and machine learning can offer insurance firms at www.microsoft.com/insurance.

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Data has been an important part of the insurance industry for centuries, but the emergence of big data has brought unprecedented challenges to insurers around the world. Today, insurance companies large and small need to ingest, process, analyse and act on massive amounts of data from heterogeneous sources quickly and cost effectively. As legacy analytics tools fail to provide the necessary capability and agility for new big data workloads, insurers are discovering Cortana Intelligence Suite, a fully managed big data and advanced analytics suite, as an enabler for their new data, analytics and intelligence needs.

For example, If P&C Insurance, a leading property and casualty insurance company serving three million customers in the Nordic region, found that it was able to uncover the value of data more quickly and cost effectively using Cortana Intelligence Suite’s advanced analytics capability. If P&C worked with Microsoft to complete a pilot project on Cortana Intelligence Suite, with a focus on Azure Machine Learning (ML). The main goal was to evaluate how well Cortana Intelligence Suite handles different aspects of predictive modelling as a replacement for If P&C’s on-premises legacy data analytics platform. The success of the pilot led the company to replace its legacy SAS platform with the Cortana Intelligence Suite based solution.

Three use cases were evaluated in the pilot: a churn model was used to predict whether or not a customer would cancel their policy in a 40-day window surrounding their renewal date, while an upsell model predicted the probability of success of a potential upsell communication to a given customer. Data including age, duration of the policy, product composition, payment solution, household data and contact points on phone and web was used for these two models. The third case, an email text analytics project, helps to classify inbound email, such as identifying messages with negative sentiment that may indicate increased risk of customer churn.

The solution met or exceeded If P&C’s expectations in all the use cases that were evaluated. As Cortana Intelligence Suite components are designed to work together, the company was able to use Azure ML web services to quickly integrate the output of predictive analytics into an end-to-end data pipeline. The solution also helped to boost user productivity, enabling much shorter ramp times for data scientists and engineers. In addition, If P&C estimates that it will realise significant cost savings using Cortana Intelligence Suite. Besides Azure ML, the company is also adopting Azure Data Factory, Azure Data Lake, Azure SQL Data Warehouse and Azure HDInsight, and is integrating these with Microsoft Dynamics CRM.

By utilising Cortana Intelligence Suite, insurers can uncover the value of data quickly and cost-effectively and deliver meaningful visualisations to support focused, insightful information that empowers actuaries to identify and respond quickly to risk. For example, financial modelling can be used to create a vivid, up-to-date view of risk, focusing on areas such as customer profitability, customer churn and potential fraudulent activity.

The advanced analytics capabilities of Cortana Intelligence Suite enable constant analysis of the customer base which can be combined with rich visualisation to deliver value to insurers in any number of areas relating to risk. Milliman is leading the way in this area, with its Power BI solution that provides data to actuaries in a far more visual, meaningful way than the traditional tabular view.

As the insurance business generates growing volumes of data, risk management will continue to demand increasing amounts of data modelling. With Cortana Intelligence Suite, insurers can enhance the data set they get from their models, generate more insight from that data and put themselves in a position to make better decisions, transforming their data into business value.

Find out more by downloading Microsoft’s Perspectives on Insurance Risk Modelling

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