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SMARTS in credit and risk management


SMARTS in credit and risk management

If you envision modernizing or building a credit origination system, an insurance underwriting application, a rating engine, or a product configurator, our SMARTS decision management platform can help you. Discover it here through a selected list of use cases we consider to be representative of decision management applications in modern credit and risk management, based on data, models, and automation.

If your project is different, just contact us or request a free trial. The Sparkling Logic team enjoys nothing more than helping customers implement their most demanding business requirements and technical specifications. Our obsession is not only to have you satisfied, but also proud of the system you will build.

Selected use cases

In credit and risk management, SMARTS has been used in applications where many data-driven decisions were frequently invoked and decision logic often updated, in response to changes in industry regulations, market dynamics, and business strategy. For this blog post, we select some applications that our customers have built with SMARTS.

Credit origination
An American rating agency has integrated SMARTS into its origination platform to help its corporate clients manage their credit risks, from screening to closing. With SMARTS, the agency manages credit risk for 4 of top 5 telcos and 30 of top 40 banks.

Credit risk management
A Chinese financial services provider uses SMARTS as the engine for its credit risk management from customer registration and identity identification to credit scoring and amount calculation to loan approval and money transfer. With SMARTS operational, the fintech company increased loan volumes to over 38 million lending transactions with greater control over its business risk.

Deposit risk management
A consortium of US banks specializing in deposit risk management measured SMARTS simulations of 1 billion transactions on 4 cores in less than 42 minutes, enabling the consortium to execute their decisions and compute complex business metrics beyond the traditional statistical means, variances, and deviations.

Flash fraud detection
A global online payment platform used BluePen for fraud detection. Since the deployment of the model, the detection time of a fraudulent transaction has been reduced from two weeks to less than a day, and the saving amounts to $10M’s per ongoing flash fraud.

Insurance claims adjudication
A major US-based third-party administrator for long term care insurance products uses SMARTS as the decision management engine for the company’s claims adjudication system, which processes 90,000 claim decisions per month over 1.3 million policies. Development and deployment took less than 6 months.

Healthcare insurance
A global risk platform company has used SMARTS to create, test, validate and put into production COVID-19 conditions for its drug prescriptions for more than 500,000 policyholders, located in more than 10 countries. Full development from specification to production took less than 12 months.

Life insurance underwriting
A Chinese life insurance company uses SMARTS so that all the underwriting rules and nearly 70% of the claims rules are managed by business experts, without calling on the IT department to update the rules. This allowed IT to focus on the reliability and availability of the system. Additionally, updating rules now takes no more than an hour from development to production.

Benefits

As reported by our customers, credit and risk analysts were able to leverage data and scoring models to intuitively build credit and risk management applications that can easily evolve with the business activity, internal policies, and industry regulations.

They also benefited from SMARTS agility and flexibility, giving them the ability to configure and refine decision logic, test, simulate decision services, experiment, choose decision strategies, and finally publish and manage deployment. Credit and risk analysts were able to participate in the entire solution lifecycle through web forms and point-and-click interfaces, without the sole reliance on IT.

On the other hand, IT had all the required performance, security, integration, and scalability capabilities to fit their enterprise architecture and governance without additional development or changes in the current applications. SMARTS was delivered in the form of a containerized product ready to install, deploy, and run as part of an interactive system, a service to invoke in a service-oriented environment, a program to call in a message-oriented environment, or a batch processing application.

To explore more, we invite you to visit our blog, webinar, resources, and demo pages where you can learn about SMARTS capabilities, features, and tools that make it an all-in-one low-code platform for building smart decisioning applications without a heavy involvement from IT beyond first installation.

Further reading

Sparkling Logic SMARTS in 10 Questions and Answers, a recent blog post that presents SMARTS all-in-one decision management platform through the 10 most asked questions and their responses.

Sparkling Logic: Decision Making Rendered Simple and Holistic, a “30,000-foot view” of SMARTS, Sparkling Logic, Inc’s low-code digital decision-making platform by CIOReview magazine.

About

Sparkling Logic is a Silicon Valley company dedicated to helping businesses automate and improve the quality of their operational decisions with a powerful decision management platform, accessible to business analysts and ‘citizen developers’. Sparkling Logic SMARTS customers include global leaders in financial services, insurance, healthcare, retail, utility, and IoT.

Sparkling Logic SMARTSTM (SMARTS for short) is a cloud-based, low-code, decision technology platform that unifies authoring, testing, deployment and maintenance of operational decisions. SMARTS combines the highly scalable Rete-NT inference engine, with predictive analytics and machine learning models, and low-code functionality to create intelligent decisioning systems.

Hassan Lâasri is a data strategy consultant, now leading marketing for Sparkling Logic. You can reach him at hlaasri@sparklinglogic.com.

Sparkling Logic SMARTSTM in 10 Questions and Answers


Sparkling Logic SMARTS in 10 Questions and Answers

Sparkling Logic helps businesses automate and improve the quality of their operational decisions with a technology platform that is powerful and simple: SMARTS for short. In this post, we present SMARTS through 10 selected questions and answers.

Q&A

1) What is SMARTS?

SMARTS is a decision management platform for business analysts and ‘citizen developers’ to author, test, simulate, deploy, run, and change decisions autonomously, without involving developers or IT beyond first installation.

2) Is SMARTS a business rules engine?

SMARTS is more than a business rules engine. It integrates multiple decision technologies into the same platform. SMARTS provides eight execution engines: A decision flow engine to sequence tasks of a business process; a state-machine engine to orchestrate tasks; a rule set engine to sequence decisions; a sequential engine that either fires all or just the first valid decision; a Rete-NT engine for inference; a lookup engine for data search in large datasets; a PMML engine to execute predictive models; and a DMN 1.3 engine to execute decision models. Depending on the problem you have, you may choose one or the other, or even combine them in the same set-up.

3) What are the typical applications for which SMARTS is the best fit?

In the financial, insurance, and healthcare services, SMARTS often won over the competition for origination and underwriting, pricing and rating engines, account management, fraud detection, and collections and recovery. More generally, SMARTS is a good fit when there are a lot of decisions that are data-based, frequently invoked, and likely to change often.

4) What is the difference between authoring business decisions and rules with SMARTS and coding them directly in the final application?

You can code decision logic but you will need detailed specifications from business analysts. This process may take too much time when compared to SMARTS. And once the decision logic is coded, it becomes complicated for business analysts to understand and take control of. SMARTS targets business-critical decision logic that either implements business models, corporate policies or industry directives in a dynamic and continually changing economy. Think of all the financial, insurance, and healthcare regulations since the financial crisis of 2008 and the changes since the coronavirus crisis of 2020. These two crises are typical examples of complex situations where business decisions not only need to be implemented quickly and accurately, but they also need to change dynamically and continuously.

5) Does SMARTS come with a decision design process?

SMARTS not only supports but it also augments the Decision Model and Notation (DMN) standard of the OMG (Object Management Group). DMN models decision dependencies very well, but not decision sequencing, which is also a natural way experts use to describe a complete decision logic. SMARTS addresses both dependency and sequencing through the combination of Pencil, RedPen, and the decision flow.

6) What machine learning models does SMARTS support?

SMARTS supports the execution of 13 machine learning models including classification, linear and logistic regression, support vector machines (SVMs), decision trees, random forests and ensemble learning, clustering, and neural networks. SMARTS uses PMML, the standardized predictive model markup language, to import and execute whatever model your data scientists have built.

7) Does SMARTS integrate with business process management platforms?

Yes, a SMARTS decision service can be natively invoked by a business process like any other service. Also, for decision-centric processes, SMARTS provides an orchestration capability.

8) What is the difference between an RPA tool and SMARTS?

If you think of a process as a sequence of “what to do”, “how to do it”, “do it”, and “report it”, then SMARTS automates the “what to do” and “how to do it” tasks while an RPA tool automates the “do it” and “report it” tasks.

9) Is SMARTS cloud-based?

SMARTS was designed from the ground-up for the cloud. Whether you have chosen to host your application or use our SaaS solution, we provide you with the most modern tools. SMARTS comes in a container, ready to install on your premises, AWS, GCP, Azure, or Aliyun. Choose yours, change your mind, no need to recode to redeploy your application.

10) What makes you unique?

Our motto is “your decisions, our business”. We enjoy nothing more than helping customers implement their most demanding business requirements and technical specifications. Our obsession is not only to have clients satisfied but also to be proud of the system they built. So dare to give us a challenge and we will solve it for you in days, not weeks, or months. Just email us or request a free trial.

In this post, we introduced SMARTS through 10 selected questions and answers. If you have more, feel free to read our blog, sign up for our webinars, or contact us. We would be happy to get back to you very quickly.

About

Sparkling Logic is a Silicon Valley company dedicated to helping businesses automate and improve the quality of their operational decisions with a powerful decision management platform, accessible to business analysts and ‘citizen developers’. Sparkling Logic’s customers include global leaders in financial services, insurance, healthcare, retail, utility, and IoT.

Sparkling Logic SMARTSTM (SMARTS for short) is a cloud-based, low-code, decision technology platform that unifies authoring, testing, deployment and maintenance of operational decisions. SMARTS combines the highly scalable Rete-NT inference engine, with predictive analytics and machine learning models, and low-code functionality to create intelligent decisioning systems.

Hassan Lâasri is a data strategy consultant, now leading marketing for Sparkling Logic. You can reach him at hlaasri@sparklinglogic.com.

Software industry trends behind the digital transformation revolution


This article presents the three software industry trends driving the digital transformation revolution: DevOps, low-code / no-code automation, vertical integration with digital decisioning.

Introduction

The pandemic changed tech priorities for many people both at work and home making a ‘hybrid’ work a top initiative. Where and how we do the work accelerated the need to improve customer digital experiences and efficiency across work, shopping, and everyday chores.

The data supports this new trend. The independent research firm Omdia compiled over 300 responses from executives at large companies indicated that working away from traditional offices will become the new norm. 58% percent of respondents said they will adopt a hybrid home/work. Even more interesting is that 68% of enterprises believe employee productivity has improved since the move to remote work.

Similarly, adoption of everyday on-line activities such as shopping, banking and entertainment further accelerated the pace of digital transformation. The need for improved applications increased the pressure on companies to relaunch efficient, friendly front-end customer apps with more intuitive UX. The back end now needs to support faster turnaround with the need to automate processes for the new on-line community of users demanding faster, cleaner, and more intelligent offerings.

To respond to this digital transformation, companies are rapidly adopting easy-to-use integrated enterprise software tools to optimize and accelerate development of these efficient digital products.

Several trends like DevOps, Low-code/automation and vertical integrations with integrated digital decisioning have emerged to help enterprises take the digital transformation journey faster and cheaper.

DevOps

DevOps is a software development concept bringing together historically disconnected functions in the lifecycle of the software development. Traditionally, business analysts would define the problem, developers would interpret the concept and build applications, and operations teams would test, report bugs and provide feedback. The disconnect between the functions, silo’d approach created inefficiencies, increased costs and slowed down application releases.

The emergence of integrated tools and processes which integrate this multiple aspect of software development and promote collaboration between these different functions supported growth of the DevOps industry.

In fact, the market data shows that these trends are supported by the investment community and exit activity. According to Venture Beat, in 2Q 2021, Venture funding for global DevOps startups reached $4 billion and the exit activity deal value was dominated by the IPOs of UiPath (robotic process automation) and Confluent, (data / application integration platform).

Low code / no code automation

Application development is also coming closer to non-developers with low/no-code approach and automation.

Software engineering, traditionally owned by IT and software engineers, has always been coveted by other, non-IT stakeholders in the enterprise. In 1991, Powerbuilder introduced a revolutionary concept of a development framework, aiming at democratizing development by allowing non-software professionals to get access to application development. Perhaps ahead of its time with clunky UX, WYSIWYG, Powerbuilder started the revolution of introducing emergence of ‘citizen-developers’, people who originally participated alongside IT in shaping the application and business models but could not code and create the applications themselves. It also introduced data integration with application logic and object-oriented concepts like inheritance and polymorphism and encapsulation, bringing software engineering to the masses.

Fast forward to 2020’s, virtually every enterprise tool platform and enterprise customer have adopted a low-code/no-code approach. The mission is the same as 30 years ago – to provide easy to use, graphical UI/UX, drag and drop concept to application development and allow business analysts, ‘citizen-developers’ and non-software engineers to create, test and even deploy enterprise applications.

Vertical integration with digital decisioning

The perennial challenge of allowing non-developers to create applications is the conundrum of how deep they can develop without coding and to what extent they can customize complex enterprise cloud applications without IT and coding.

To accelerate digital transformation, enterprise software vendors are emerging mostly from the workflow / BPA world, such as Pega and ServiceNow. They are applying a two prong approach – core tool collection and vertical integration. The workflow vendors have developed (or acquired) a collection of point tools in a core-component framework. Those components typically include AI/ML, reporting, workflow, RPA (Robotic Process Automation), case management, rules engine, decision management, knowledge bases, BPA (business process automation) and process orchestration. Those components typically feature common UI and work across a normalized data model and unified architecture.

But that is not enough. To satisfy modern rapid digital transformation needs, in case of fintech enterprise customers (i.e. banks, insurance companies and financial services) also now require pre-built workflow, data and application models. These vertical templates are higher level and more specific, providing out-of-the box, drag/drop solutions like credit card operations, loan management and payment operations. Using the low-code approach, a business analyst can graphically drag/drop pre-defined steps into a loan origination workflow with pre-defined commonly used tasks, created using best practices defined by the ‘centers of excellence’. Companies like UIPath have created a 3rd party marketplace for additional steps and templates created by analysts and consultants. (Those steps could be ‘get customer data’, ‘OCR input form’, ‘scrub customer data’, authorize user’, ‘assess risk profile’ etc.).

Beyond the top level tasks, the functionality ultimately becomes more complex and the sophisticated customer needs powerful decision capabilities to introduce their own business rules and implement proprietary features. The ‘secret-sauce’, which separtes most common steps from proprietary concepts distinguishes top corporations from the competition, requires more sophisticated digital decisioning tools. These digital decisioning tools enable non-developers to customize and manage decision logic, implement AI/ML features, run A/B testing and visualize performance results on training and production data in real time.

To satisfy most common customer base, digital workflow vendors typically provide rudimentary business rules integrated in their low-code platforms and further integrate them with the downstream workflow platforms and vertical ecosystem vendors (i.e. FiServ, Jack Henry, SAP, Salesforce and FIS in banking for example).

The most sophisticated and demanding customers, however, need a more sophisticated set of digital decisioning tools like standalone professional DM platforms. To simplify and visualize this complex decision management, a new generation of low-code digital decision management platforms like Sparkling Logic emerged. These platforms integrate historical business rules engine, data and AI, demystifying machine-learning and providing low-code approach to development and monitoring of application logic performance, continuously as the business logic and training data change and drift.

The pandemic, hybrid work and pervasiveness of the cloud computing have irreversibly changed the software application development. Enterprise customers are seeking and deploying better, faster, more integrated software tools. DevOps integration, low-code, vertical templates, integrated AI and digital decisioning are becoming a new normal while defining the next generation of applications, created not only by software engineers, but by mere mortals across the enterprise.

About

Davorin Kuchan is the CEO of Sparkling Logic, Inc, an AI-driven digital decision management enterprise tools platform. Major enterprise customers like Equifax, Centene, First American, Nike, SwissRE and Enova deploy and integrate Sparkling Logic SMARTS digital decision engine. Sparkling Logic, Inc is based in Sunnyvale, California. http://www.sparklinglogic.com

Authoring Business Rules with Data, Standards, and Apps in SMARTS


Nowadays, business rules automate hundreds, thousands, and sometimes millions of operational decisions that some organizations make every day. The most representative examples of such organizations are financial, insurance, and healthcare sectors. All these organizations make automated decisions with several combinations of terms and conditions, legal constraints, eligibility criteria, risk levels, and price ranges. In this blog, I explain how business analysts and ‘citizen developers’ author decisions with rules, data, standards, and apps in Sparkling Logic SMARTSTM.

Business rules

Business rules are not new; but until recently they were encoded in the rule syntax as “IF THIS THEN DO THAT” statements. As such, they needed detailed specifications from business analysts and skilled developers to code these business rules. And once the business rules were coded, they were complicated for business analysts to understand or control.

Authoring with data

Gone are the days when business rule creation started with lengthly interviews where IT professionals asked business experts how they made decisions in line with company policies, industry regulations, and market dynamics. Starting with data, transactions, and use cases is now the new way. Fully in line with this new approach, SMARTS provides RedPenTM, SparkL, and Pencil. These are three independent but complementary technologies that business analysts can use to import data, and start authoring rules.

RedPen is Sparkling Logic’s patented technology for authoring decisions through point-and-clicks. Using RedPen, business analysts write business rules using a use case approach. The loaded sample data provides the context to create, test, and run rules without prior knowledge of a special rule language and syntax. RedPen mimics what business experts do on paper when they flag decisions with a red pen. When business analysts activate RedPen, they can pin an existing rule, a field of this rule, or a rule set and modify it as if they were using a pen on a paper. They can also create new rules with RedPen, SMARTS will automatically turn them into executable rules. For cases where advanced logical, mathematical, and symbolic manipulations are required, business analysts can use SparkL.

SparkL (pronounced “sparkle”) is Sparkling Logic’s language for writing rules in a natural language format. SparkL can be used by business analysts with no formal technical background in rules syntax while still benefiting from mathematical expressions, string manipulations, regular expressions, patterns, dates, logical manipulations, constraints, and much more. They can express any imaginable decision logic and symbolic computation, making it the choice for highly sophisticated decisioning applications where the conditions as well as the actions can take a great variety of forms.

Other cases where the decisioning projects necessitate formal requirements and decision modeling, the standards development organization (OMG) offers a standard called Decision Model and Notation (DMN). Sparking Logic has adopted this standard and developed Pencil to operationalize DMN.

Authoring in the context of DMN standard

Pencil is a tool for users to model business decisions by dragging and dropping graphical icons to form a decision process. Pencil models comply with the DMN standard. Using an intuitive graphical interface, business analysts can immediately start capturing data requirements, decision models, and business rules, while collaborating to achieve the best explicit description of the decisions required for systems and applications. Pencil’s glossary can be used across decisions to achieve consistent use of terminology related to decisions. Business analysts can create or import data and then execute, test and continue to refine and improve decisions. Once decision modeling is done, Pencil provides a direct path to an executable decision.

With SMARTS, a user has not to adapt to the tool, but the reverse, it is the tool that adapts to the user. The business analysts select the appropriate way for the task at hand. In the same project, they may choose Pencil to model decisions, RedPen for the major part of the application, and SparkL for the rest of the application. At any time, they can choose to display the rule sets as a group of rules, a decision table, a decision tree, or a decision graph. Moreover, they can switch from one representation to another and vice versa.

Orchestrating business apps

As intuitive as a decision management tool can be, it may never meet the needs of a real business person. The bells and whistles that business analysts need can be overwhelming for the credit manager or insurance underwriter who needs access to decision logic. This person is certainly more inclined to exploit decision-making logic than interested in learning how to create it, and even less in training on a rules authoring tool.

For untrained business users, SMARTS sets the bar higher towards more simplification, and still within the same interface. They have full control over the configuration, management, and assembly of the decision applications that business analysts have developed, and they can do it all through web forms and point-and-clicks. With this added level of abstraction, untrained business users, business experts, and ‘citizen developers’ can adapt to industry regulations, company policies, and market dynamics, without IT intervention beyond the first installation.

Takeaways

  • Business rules have moved from coding rules in “IF THIS THEN THAT” statements to authoring them with data, standards, and apps
  • SMARTS implements this new way via RedPen, SparkL, and Pencil, three independent but complementary authoring tools that business analysts can use to express their decision logic
  • Business users need business applications, not authoring business rules or developing machine learning models
  • SMARTS gives business owners full control of business apps through web forms and point-clicks
  • Today change is the rule, with SMARTS, automated decisioning is flexible to accommodate ever-changing regulations, company policies, and market dynamics

If you envision modernizing or building a credit origination system, an insurance underwriting application, a rating engine, or a product configurator, SMARTS can help. The Sparkling Logic team enjoys nothing more than helping customers implement their most demanding business requirements and technical specifications. Our obsession is not only to have them satisfied, but also proud of the system they build. Just email us or request a free trial.

About

Sparkling Logic is a Silicon Valley company dedicated to helping businesses automate and improve the quality of their operational decisions with a powerful digital decisioning platform, accessible to business analysts and ‘citizen developers’. Sparkling Logic’s customers include global leaders in financial services, insurance, healthcare, retail, utility, and IoT.

Sparkling Logic SMARTS is a cloud-based, low-code, AI-powered business decision management platform that unifies authoring, testing, deployment and maintenance of operational decisions. SMARTS combines the highly scalable Rete-NT inference engine, with predictive analytics and machine learning models, and low-code functionality to create intelligent decisioning systems.

Hassan Lâasri is a data strategy consultant, now leading marketing for Sparkling Logic. You can reach him at hlaasri@sparklinglogic.com.


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