Achieving Regulatory Compliance with Decision Management

The 2008 financial crisis affected each of us in some manner. In particular, financial institutions and banks felt most of the heat. There were several repercussions of this crisis in the form of increased regulations and various legislation in an effort to curtail such an occurrence in the future. The aim of such regulations is to maintain confidence in the financial system, to increase financial stability, to protect consumers at some level and to reduce financial irregularities.

Since financial institutions now live in a climate of increased compliance and regulation, there has been an increase of consulting firms – both technical and advisory – in providing specialized services to help these institutions implement regulatory compliance so that these institutions can focus on their business while complying with these ever changing regulations.

It would be futile to jump into a solution of how this can be achieved without understanding what regulatory compliance means. Compliance means conforming to a rule which can be a policy, standard or law. Regulatory Compliance describes the goal that companies aspire to achieve in order to comply with relevant laws and regulations.

Where do business rules fit in the picture?
Business rules are by definition a statement that describes the policies or constraints of an organization. Since compliance requires conforming to a policy in general, business rules fit the perfect picture as a placeholder of such policies. This is for various reasons. First, rules are repeatable and tractable to automation. Second, rules are transparent and easily traceable. This makes for increased visibility of the policies which are to be complied with. Business rules implemented with IBM’s Operational Decision Management software can be exported to a word or excel document, and even be emailed to an organization’s legal department in the format they are written. Third, rules can be changed easily with zero down time to make the change to production. This helps organizations cope with an ever-changing regulatory environment and allow them to focus on its business rather than inviting preseason resources keeping up with a changing regulatory environment.

How can regulatory compliance be achieved by Operational Decision Management (ODM)?
The best way to describe ODM’s capabilities for regulatory compliance would be to take existing compliance policies that firms have to constantly deal with, and propose an implementation using ODM. We take one of the most challenging regulations that was recently (2010) enacted by the 111th US Congress – it is the Foreign Account Tax Compliance Act or more popularly known as FATCA. The act aims to tackle tax evasion by US Citizens to tax havens or strong data protection countries like Switzerland. Foreign financial institutions like banks, insurance firms and fund houses are affected by FATCA and need to comply with FATCA regulations. Individuals with US nationality, US address or phone number and corporations with substantial US ownership are affected by this legislation. Complying with FATCA became so complex and necessary at the same time that IBM has offered a specialized FATCA solution in their offerings.

One of the challenges FATCA brings is the amount of information it requires an organization to process which especially creates a hassle to the organization’s technology platform. There are three different impacts to the technology platform with FATCA – customer classification, transaction monitoring and finally IRS reporting.

In our business case example, let us study customer classification. In order to comply with FATCA, financial organizations have to collect a W-9 form from all account holders who are US Persons. This is clearly business logic which can take an ugly and complex turn when implemented in application code. The solution: WebSphere Operational Decision Management (ODM). The above business logic can be copied word to word and represented in the form of a business rule. It can be created in what is called a rule designer. This is how the same business logic looks like when written in ODM as a business rule:

The above business rule can be exported as-is to what is called the decision center which is the special portal that business users have access to with the ODM suite of products. Decision Center gives immense visibility to the rules across an organization. Major stakeholders can log in to this portal and view the contents of critical decision tables or business rules. Returning to our scenario above, the same FATCA rule when deployed to the decision center, can be edited by business users by click of a button. Clicking on the “Edit” link below, the rule can be easily modified by a non-technical user:

Any changes to these business rules in general can be directly deployed to production environment, through the decision center portal. Obviously, there are various recommended governance strategies that provide checks and balances along with regression testing, so that incorrect information is not pushed to production servers. Nevertheless, the capability to change an existing policy (or a decision table) is available with ODM.

Conclusion

Regulations are here to stay and the sooner organizations adapt to implement compliance with these regulations, the better they will become for their competition. In our example for FATCA we just saw how ODM can be leveraged to implement changes at a lightning pace. There is much more that can be achieved with ODM, this just gives a small glimpse of what your organization can look forward to when selecting ODM as a solution to meet your organization’s compliance.

Akshat Srivastava is a Senior ODM Consultant at Prolifics with about 7 years of experience in the IT industry having worked in insurance, banking, retail and public sector companies. He is experienced in all aspects of the development life cycle, including bottom-up estimates, analysis, design, development, testing, release management, and bug-fixing. He has created rule based solutions at various clients, authored rule repositories and best practice documents while focusing on WebSphere Operational Decision Management as the implementation environment. He has also created BPM applications for client onboarding for leading financial institutions. Akshat holds a bachelor’s degree in computer science from California State University.

Testing Philosophy in ODM: Feasibility of Complete Rule Testing in Decision Validation Services (DVS)

Software testing is an important step in the software development life cycle. IBM Operational decision Management (ODM) is not an exception. Testing in ODM is done through Decision Validation Services (DVS). It automatically generates an excel sheet with specified input fields from the Execution Object Model (XOM).  To run a test you need to fill out the excel sheet with test cases and expected outputs. Each row would represent a test case. In this article I would like to discuss the feasibility of running a complete (or close to complete) test in DVS based on the number of fields and the complexity of the decision (rules).

Let us first consider the feasibility of complete test regardless of the technology/software choice. For simplicity let us consider rules around only three fields (Field1, Field2, Field3), which carry binary values. The maximum number of test cases needed to run a complete test for the ruleset is 2^3=8.

#	Field1	Field2	Field3	Ruleset Output
1	T	T	T
2	T	T	F
3	T	F	T
4	T	F	F
5	F	T	T
6	F	T	F
7	F	F	T
8	F	F	F

This is a simple example (n=3), but it can help us visualize and understand how to handle the test cases with a lot more fields/elements. Note:  2^3=8 is also the maximum number of unambiguous rules that can be implemented with 3 fields. This can also be visualized as a binary tree. The height represents the number of fields and the leaves of the tree represent the rules. E.g. the left most leaf R1 corresponds to the rule#1 in the above table (F1=true and F2=true and F3=true).

In general for N fields, each of which can take K values (group of values), there can be at most K^N unambiguous rules implemented. In the above example N=3 and K=2 (binary fields). We can generalize it even further. There can be fields with different number of accepted values (group of values).  If there are n fields, each of which can take k values and there are m fields each of which can take p values, there can be at most k^n* p^m unambiguous rules implemented. 

Another philosophical question we should ask is how much testing is sufficient. E.g. if we have implemented R1,R2,R3, do we have to implement test cases for the tracks R4, R5, R6, R7,R8 , i.e. do we have to prove that unimplemented rules did not fire(unintentionally)?!?!  The answer is - it depends!! We may have to do 1 or 2 test cases for unimplemented rules, depending on the complexity of the rules. Example: loan approval application that has a rule: “if the age of the applicant is greater than 40 and the credit score is “good” then approve”. If we were to write test cases for that single rule, we might have to do the following:

#	Age is greater than 40	Credit score is “good”	Expected output
1	T	T	Approve
2	T	F	The default approval status

Theoretically we did not “have to” do the second test case, but it is good to make sure the approval is set by the implemented rules and not by some bug that sets it to  “approve”  regardless of rule conditions. 

What if there were 100 fields instead and let us keep them binary for simplicity (would not change the problem if they could accept 3, 4, 5 ... n values). The max number of rules constructed and the max number of test cases need to do a complete case is 2^100. 

#	Field1	Field2	…	Field100	Ruleset Output
1	T	T		T
2	T	T		F
…	…	…		…
	F	F		F

Often times we implement rules with more than 100 XOM elements and to run a complete test we would need 2^100~1.27*〖10〗^30test cases. Theoretically this is an unfeasible problem if we consider the worst case scenario. 

The number of fields is relevant only in theoretical discussion, considering the worst cases (2^n  , where n is the number of fields). In practice though the number of test cases is needed for DVS is equal or comparable to the number of rules.  That means that if it was feasible to create N number of rules, then it would be feasible to implement sufficient test cases for complete testing in DVS. 

To learn more about Prolifics' ODM solutions, visit our website or contact solutions@prolifics.com.

Artur Sahakyan is an Associate Consultant at Prolifics specializing in IBM WebSphere Operational Decision Management (v5.xx - v8.xx). Artur has a strong background in mathematics and probability/statistics. He also has profound knowledge of IBM Business Process Manager, IBM Integration Bus (IIB v9), IBM WebSphere MQ (v7), IBM SPSS Modeler, IBM SPSS Statistics, Java, C++, C.

Customers Purchase Benefits, Not Products

Business organizations have core competency in certain areas and are more likely to have strong capabilities in those areas. Firms are also likely to look for outside consultants in areas where they do not have enough home grown talent and more likely to outsource capabilities such as IT in case of an internal gap. This article is a quick overview of some of the decision challenges faced by the firms while trying to decide what capabilities to outsource.

Businesses are facing a challenging landscape. The customer is connected and empowered. The customer can compare healthcare insurance plans at the click of a button. He or she can search for the best price for consumer goods online and order it online to have it delivered the same day. The customer is purely shopping for benefits while the firms are selling products/services to provide those benefits. Consumer needs have changed, since they are exposed to products from across the globe. A customer's access to information is unbound, thanks to internet. This has resulted in firms re-evaluating their business model to see if they are still serving the evolving customer needs. An insurance company offering high deductible plans with a wide coverage might no longer be relevant in a new target market. The new market demand, due to changing demographics, might be for lower deductibles with a smaller specialist network. An historically well-performing video game with MP3 song playing capabilities might no longer be relevant because of the availability of music on smartphones.

Under such scenarios, the firm has to re-think its business model and make key decisions about how best to leverage its existing capabilities to meet the new market demands. After the firm has decided to revamp its product/service to best meet the new consumer needs, it has to review its existing capabilities - human resource capabilities, IT capabilities, supplier capabilities etc. Because of the competitive landscape, the time to market for modified products/services has to be very short. Productivity of its employees becomes critical in order to achieve high speed to market. IT systems play a key role in increasing the productivity of a firm's employees. During the process of selecting a suitable IT product, the firms have to select a product that best compliments its employees’ skills. Not every "out of the shelf" product will meet the needs of the firms. Especially since the changing business needs require updated employee skills, it is rare for "off-the-shelf" products to meet the new needs of the firms exactly. The IT products needs to be customized to the needs of the firms. Under such a scenario, it is critical for the firms to engage with IT product & consulting companies that have worked with firms from various industries and effectively understand the changing needs of its clients. Firms such as IBM have worked with clients from various industries for a long time and collected extensive domain knowledge. This knowledge is helping IBM and other firms in its ecosystem to quickly develop products and solutions to effectively deal with the emerging challenges. IBM products such as IBM BPM 8. X (Business Process Manager), Cognos, ODM (Operations Decision Management) carry with them an history of experience with business clients with evolving needs. This experience has resulted in development of features that are applicable and adaptable to various business needs. E.g.: The business process design and integration capabilities are as adaptable to a retailers in-house legacy mainframe systems as they are adaptable to a newly on-boarded supplier’s web services. Cognos data analytics capabilities can “talk” to an insurance firm’s legacy data source systems as well as capture real time data generated by the process.

When the time to market is so short, it might be difficult for firms to build the IT capabilities in-house. Firms are more likely to benefit from outsourcing IT development in areas where the internal employees have not yet matured at. Besides, the key upside of outsourcing an IT skill is quick development of IT applications and helping in the final goal of delivering a firms product/ service to market faster. Before making the decision to choose an IT consulting firm, the business firm has to evaluate the client portfolio of the IT consulting firm, it's nature of projects implemented historically and breadth of domain expertise. IT consulting firms that have worked with key players in a particular industry have better exposure to industry challenges. Consultants that have a shorter learning curve will achieve higher productivity while helping to design and build an suitable IT application.

Bottom Line: When businesses choose the right, flexible IT application and partner with consultants with right skills, they increase their chances of effectively catering the evolving needs of their customers.

N.R. Vijay is a Solution Architect in the Business Process Management division of Prolifics. He has over 10 years of consulting experience across domains such as Retail, Healthcare and Banking. Specializing in technology, management concepts and enterprise strategy, he is focused on change management and process improvement initiatives. He co-authored a whitepaper titled "Improving Customer Loyalty through Business Process Optimization and Advanced Business Analytics"

ODM Integration with SPSS Predictive Analysis Suite - Part 1: PMML Import

There are a few ways of integrating the SPSS Predictive Analytics Suite with ODM. To get started, it is required to install the SupportPac (LB02).

The SupportPac provides two features that support the usage of business rules and Predictive Analytics together:

• Part 1: Import a decision tree model via PMML (Predictive Model Markup Language) and generate an Operational Decision Management decision tree at design time (discussed in this article)
• Part 2: Reference predictive scores within business rules and obtain those scores at runtime from the SPSS Scoring Service (not discussed in this article)

In this article I am going to describe step-by-step the instructions to utilize the ODM capabilities of PMML Import of Decision Tree models. Part 2 will be a separate article describing ODM-SPSS Scoring Service approach. Both approaches require an installation of IBM WebSphere Operational Decision Management Integration with the SPSS Predictive Analytics Suite SupportPac.
To install the IBM WebSphere Operational Decision Management Integration with the SPSS Predictive Analytics Suite SupportPac, you must:

1. Unzip the SupportPac deliverable in the WebSphere Operational Decision Management installation directory.
2. Install the predictive analytics features from Rule Designer.

PMML is the leading standard for statistical and data mining models. It uses XML to represent mining models, so that models can be shared. In other words, using PMML, models can be developed on one system using one application and deployed on another system using a different application. Models can be created and PMML can be generated and exported using the SPSS Modeler.

The PMML import approach works for Decision Tree models. Decision Tree models are produced by data mining algorithms (such as CHAID, C&RT, ID3, C4.5/C5.0) that identify various ways of splitting a dataset into branch-like segments, forming an inverted tree that starts with the root node at the top of the tree. Decision Tree models are used frequently in the data mining community for classification and prediction as they are easy to understand, easy to use, support both quantitative and qualitative measurements, and are very robust. Data mining workbenches, like the SPSS Modeler, provide rich toolsets for creating and validating Decision Tree models.

The PMML import feature focuses on the Decision Tree model. After your Decision Tree model is exported from a modeling tool to a PMML file, you can import it into a decision tree.

The primary difference between a Decision Tree model, as used in the data mining community, and a decision tree is that the decision tree has actions attached to the leaf nodes while the Decision Tree model usually has some sort of predicted variable or classification attribute specified for each node. In other words, a Decision Tree model can identify the business rules for classifying and predicting a specific variable, whereas the decision tree can actually execute those business rules along with the appropriate actions at run time.

1. Importing PMML you have a choice to either generate the BOM elements the model is using or to map existing BOM elements to the fields in the model. 

2. The PMML import creates a Decision Tree and the BOM elements used in the model. You may get B2X errors and warnings until you create the corresponding XOM class.

3. At this point you can treat the Decision Tree as other Decision Trees (if any) or rule artifacts created in Rule Designer. You are allowed to modify/edit the DT. Best practices around ruleflow orchestration suggest that each decision tree should be contained within its own rule task. 

Note that an imported decision tree currently has no life-cycle link to the PMML file. Consequently, if you change the PMML model itself, you will have to repeat the import/modification process.

Artur Sahakyan is an Associate Consultant at Prolifics specializing in IBM WebSphere Operational Decision Management (v5.xx - v8.xx). Artur has a strong background in mathematics and probability/statistics. He also has profound knowledge of IBM Business Process Manager, IBM Integration Bus (IIB v9), IBM WebSphere MQ (v7), IBM SPSS Modeler, IBM SPSS Statistics, Java, C++, C.

Operational Decision Management: In-Memory (RetePlus) vs. Input Parameter (RetePlus, Sequential)

IBM Operational Decision Manager (ODM) supports multiple rule execution algorithms: RetePlus, Sequential and Fastpath. We are going to compare test run results of the first two algorithms.

RetePlus Mode:

The default execution mode is RetePlus. Use its optimization techniques to improve performance: reduction of the number of rules and conditions, computation of the rules to execute, and prioritization of the rule order. The RetePlus algorithm operates as follows:

1. The rule engine matches the conditions of the rules in the ruleset against the objects in working memory. During the pattern matching process, RetePlus creates a network based on semantic relationships between rule condition tests. 
2. For each match, a rule instance is created and put into the agenda. Then the agenda, based on some ordering principles, selects the rule instance to be executed.
3. When the rule instance is executed, the rule action is executed.
   This action modifies the working memory in the following ways:
   - By adding a new object to the working memory
   - By removing an object from the working memory
   - By modifying the attributes of an existing object.
4. The process carries on cyclically until no more rule instances are left in the agenda

Sequential Mode:

The sequential mode executes all the eligible rules for a given rule task in sequence, which provides specific performance advantages. The sequential algorithm operates as follows:

1. The rule engine performs pattern matching on input ruleset parameters and on the conditions defined on the collections of objects in working memory.
2. For each match, a rule instance is created and immediately executed. When a rule instance is executed, it sets the value of an attribute or an output ruleset parameter.

Input/output objects can be passed in to the rule engine as ruleset parameters or rules can create and manipulate in-memory objects.

Simple three rules were implemented to compare ruleset execution times for permutations of two execution algorithms and two ways of passing in input objects to the rule engine. Each of the three rules is in a separate ruletask in the ruleflow. Execution times are machine-dependent and therefore, execution time comparison of different algorithms is meaningful only relative to each other. Note that in-memory objects can only run RetePlus.  Below is the execution times chart for the following cases:

1. Using input parameters and RetePlus algorithm
2. Using input parameters and Sequential algorithm
3. Using in memory objects and RetePlus algorithm

Input Size	Using Parameters and RetePlus Algorithm  (time in seconds)	Using Parameters and Sequential Algorithm (time in seconds)	Using in Memory Objects and  RetePlus Algorithm (time in seconds)	Number of Rules Fired
1000	3	3	3	400
2000	6	6	6	800
3000	11	11	11	1200
4000	16	16	17	1600
5000	24	23	24	2000
6000	32	31	32	2400
7000	43	43	44	2800
8000	53	53	58	3200
9000	65	66	72	3600

To improve the performance of RetePlus algorithm you can do one of the following:                              (Click here for details)

• Optimize the object model
• Optimize with optimize method 
• Optimize with static agenda
• Activate dynamic rule compilation
• Improve the performance of equality and/or comparison evaluation 

To improve the performance of Sequential algorithm you can try: 

(Click here for details)

• Memory consumption reduction

Artur Sahakyan is an Associate Consultant at Prolifics specializing in IBM WebSphere Operational Decision Management (v5.xx - v8.xx). Artur has a strong background in mathematics and probability/statistics. He also has profound knowledge of IBM Business Process Manager, IBM Integration Bus (IIB v9), IBM WebSphere MQ (v7), IBM SPSS Modeler, IBM SPSS Statistics, Java, C++, C.

Case Management and Business Process Management – Benefits to Healthcare Payers

Executive Summary:

Impact is one of the eagerly awaited events of the year, the main reason being the slew of products and new features that are introduced by IBM. The application of new products and features to solve real world problems, demonstrated by solutions implemented at some of the prominent fortune 500 firms, makes every penny spent attending the event worth its value. The big product offering I am looking forward to in this year’s event is the Case Management features embedded with Business Process Manager (BPM) capabilities, thus making the processes truly smarter. Application of flexible, intelligent Case Management capabilities combined with the visibility, control and integration capabilities that BPM provides would be interesting to watch. This is even more valuable in the current setting of the Healthcare sector.

Need for Case Management in Healthcare:

With all the changes happening in the Healthcare payer sector in lieu of regulations and increasingly tough insurance market, now is the need more than ever to have flexible, smarter processes. The need of the hour is to continuously monitor market trends, identify insurance products that are not cost efficient, refine the market strategy, create flexible customized products and introduce the products within the shortest possible time to market. The best employees of Healthcare payers, with years of invaluable domain knowledge behind them, are better off applying their best judgment and making prudent decisions during the critical business processes than spend time in a swivel chair (duplicating data entry in multiple systems).

Case Management, with its feature to provide the user with the ability to review documents and choose a workflow depending on the case, can be a valuable asset.  For example, a claim review specialist reviewing a request for claim authorization, is better off reviewing the applicable benefits, claim pricing at one place in a single system with all required document images, rather than logging into different benefit systems and pricing systems, searching for the applicable benefits and pricings and performing the authorization review. After the review, the claim review specialist could choose to kick off a medical code review workflow or a payment approval workflow depending on the case. This flexibility, combined with the process visibility and legacy system integration capabilities offered by BPM could end up as a blessing. Robust document management capabilities provided by Case Management helps provide the user with the complete picture and reduces any time needed to develop a customized solution.

Case Management, BPM, Decision Management and Advanced Data Analytical capabilities combined could even lead to new business models, products and services for the Healthcare payers.

Smart people in organizations deserve to work with smarter processes and this new offering promises to provide that.

All in all, it sure is an exciting time to be in Vegas.

Next week, Prolifics will be a Platinum sponsor at IBM Impact 2014, where our team will be showcasing our BPM solutions and recent successes. If you are planning to attend IBM Impact, be sure to visit Prolifics at booth #401 or schedule a one-on-one meeting with one of our experts.

To learn more about Prolifics’ BPM solutions, visit www.prolifics.com or connect with N.R. Vijay.

N.R. Vijay is a Solution Architect in the Business Process Management division of Prolifics. He has over 10 years of consulting experience across domains such as Retail, Healthcare and Banking. Specializing in technology, management concepts and enterprise strategy, he is focused on change management and process improvement initiatives. He co-authored a whitepaper titled "Improving Customer Loyalty through Business Process Optimization and Advanced Business Analytics"

Facilitating Core Banking Transformation Through BPM and Rules

This is a guest blog entry by Scott Simmons of IBM. Scott is the BPM Solutions Architect for the Banking and Financial Markets.

Faced with aging systems, banks are reaching decision points in terms of buying a packaged solution or building/extending their existing core banking solutions.  Often banks find that packaged solutions will not meet the needs of the bank and opt for a transformation approach based on their existing solutions.  Using BPM and rules, organizations can extend existing core banking applications and not have to sacrifice the intellectual capital that is part of their current solution.  We often find that this is done in conjunction with (often) a service middle-tier normally implemented with an ESB.  As the BPM and Rules/Events technologies have evolved over the last few years, this approach has become a common and well tested pattern enabling banks to iteratively replace portions of the system while still providing key core banking functions to the business.

If we review how process and rules can be used to extend an existing solution - let's take retail lending as a key application.  In the legacy situation - Retail Lending is normally a set of COBOL programs residing on the mainframe.  In the current regulatory climate - this is an impediment to change as the 3GL solutions are not very flexible.  In short, it becomes increasingly difficult to modify code on an continual basis.  Equally important, when we need to introduce new functionality such as mobile, social or analytics functionality - this often requires code modifications as well.

So let's consider another approach.  First, understand that retail lending provides a number of high level business functions comprising multiple processes such as loan origination, loan servicing and loan closure.  We can model and simulate these functions quite easily without the need for direct code development.  The process flow logic and underlying validation/calculation activities can be modeled as decision services (e.g. rules and events).  The process flows can invoke atomic and composite services such as receive loan applications, check credit, approve loan and other key functions which in turn, provide interfaces to the operational systems.  As a result, we see that a process and decision management approach (based on a loosely coupled service design) provides a foundation to extend current core banking applications (e.g. to deal with regulatory change) and to introduce new business functionality more easily and rapidly than traditional 3GL development.  We see this approach being adopted as a key pattern to address the challenges of aging core systems in the face of ongoing market and technology changes.

We see our clients normally initiating these types of transformation projects through top-down process and rules discovery. The discovery process enables business architects to use process modeling tools and techniques to identify and decompose key business functions and requirements specifications.  One of our clients uses IBM Blueworks Live to map 1000s of key processes many of which become implemented as functions on existing core banking solutions.  Although business process and rules management can be undertaken as strictly a discovery exercise with a tool like Blueworks Live -- many tools provide the ability to develop and implement solutions.  These development tools  often provide for rapid prototyping and solution implementation facilitating collaborative design and development between business and IT stakeholders.  This capability is a key functionality of the IBM BPM and Decision Management solution offerings and is a key reason for their use in numerous banking transformation projects.

Interested in hearing more?
Next week at IBM Impact, Scott will be hosting a session titled: Raise Expectations for the Always-on Enterprise
Session Number: BTA-1221
Date/Time: Thu May 1; 10:30 a.m. – 11:30 a.m.
Location: Marcello 4503

Scott Simmons is the Banking/Financial Markets Solutions Architect for IBM’s NA Business Process Management Solution Architect team. Scott specializes on the design, development and implementation of BPM solution architectures with a focus for banking/financial markets customers. Scott has deep experience in the areas of Service Oriented Architecture and Enterprise Modernization and is a Certified SOA Solution Designer.