Debt collection practices

• US 7,403,923 B2
• Filed: 11/05/2001
• Issued: 07/22/2008
• Est. Priority Date: 10/12/2001
• Status: Expired due to Term

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services GmbH (Accenture PLC)
• Inventors: O'Neill, Patrick G., Elliott, Michael B., Nocedal, Jorge, Fourer, Robert
• Primary Examiner(s): Dass; Harish T
• Assistant Examiner(s): Milef; Elda G
• Application Number:
  US10/011,523
• Publication Number:
  US 20030078881A1
• Time in Patent Office: 2,451 Days
• Field of Search: 705/35, 705/36, 705/38, 705/40
• US Class Current: 705/38
• CPC Class Codes: G06Q 20/10 specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
• CPC Class Codes: G06Q 20/102 Bill distribution or payments
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof

Abstract

A method of optimizing debt collection attitudinally classifies debtors into one of several attitudinal segments. The approach uses an assessment of current attitudes rather than past behaviors as to predict future behavior. Each segment can be addressed with an offer, which is a combination of attributes which together, have an expected, measurable, and predictable response from the debtor. Debt collection requires the expenditure of resources, at least one of which the availability of a relatively small number of debt collectors. The offers that can be extended to debtors are identified on a debtor-by-debtor, offer-by-offer basis to identify the best offer to propose to each debtor by the limited number of debt collectors in order to maximize the economic return from all debtors.

Claims

1. A method in a digital computing device comprising at least one processor for optimizing debt collection from a plurality of delinquent debtors, the method comprising:

determining a set of debt collection strategies employable to recover debt from the plurality of delinquent debtors, at least one strategy of which is offerable to each delinquent debtor of the plurality of delinquent debtors; and

for each delinquent debtor of the plurality of delinquent debtors, assigning a debt collection strategy from the set of debt collection strategies and at least one debt collector having a predetermined skill level i that, when offered to the delinquent debtor, optimizes an expected economic recovery from the plurality of delinquent debtors through differentiation of those delinquent debtors of the plurality of delinquent debtors owing more money as compared to those delinquent debtors of the plurality of delinquent debtors owing less money,

wherein the predetermined skill level i of the at least one debt collector is expressed as a number of promises by debtors to said at least one debt collector that have been kept, divided by a number of promises by debtors to said at least one debt collector that have been made.

2. The method of claim 1, wherein the plurality of delinquent debtors are within a debtor classification category of a plurality of debtor classification categories as determined by the at least one digital computing device.

5. The method of claim 1, wherein said expected economic recovery is expressed by:

Σ

_i,j,k,pc(i,j,k,p)·

X(i,j,k,p)

where;

p is a delinquent debtor of the plurality of delinquent debtors;

c(i,j,k,p) is an expected collection amount;

i is the skill level of a particular debt collector;

j is a time period in a day;

k is a particular debt collection strategy chosen to be used on a delinquent debtor of the plurality of delinquent debtors,

where for each i, j, k, p, X(i,j,k,p) can take either the value 0 or 1 and is determined by optimally selecting i, j and k for all p'"'"'s.

3. An apparatus for optimizing debt collection from a plurality of delinquent debtors, comprising:

at least one digital computing device comprising at least one processor programmed to;

determine a set of debt collection strategies employable to recover debt from the plurality of delinquent debtors, at least one strategy of which is offerable to each delinquent debtor of the plurality of delinquent debtors; and

for each delinquent debtor of the plurality of delinquent debtors, assign a debt collection strategy from the set of debt collection strategies and at least one debt collector having a predetermined skill level i that, when offered to the delinquent debtor, optimizes an expected economic recovery from the plurality of delinquent debtors through differentiation of those delinquent debtors of the plurality of delinquent debtors owing more money as compared to those delinquent debtors of the plurality of delinquent debtors owing less money,

wherein the predetermined skill level i of the at least one debt collector is expressed as a number of promises by debtors to said at least one debt collector that have been kept, divided by a number of promises by debtors to said at least one debt collector that have been made.

4. The apparatus of claim 3, the at least one digital computing device further programmed to place the plurality of delinquent debtors within a debtor classification category of a plurality of debtor classification categories.

6. The apparatus of claim 3, the at least one digital computing device further programmed to determine said expected economic recovery as expressed by:

Σ

_i,j,k,pc(i,j,k,p)·

X(i,j,k,p)

where;

p is a delinquent debtor of the plurality of delinquent debtors;

c(i,j,k,p) is an expected collection amount;

i is the skill level of a particular debt collector;

j is a time period in a day;

k is a particular debt collection strategy chosen to be used on a delinquent debtor of the plurality of delinquent debtors,

where for each i, j, k, p, X(i,j,k,p) can take either the value 0 or 1 and is determined by optimally selecting i, j and k for all p'"'"'s.

7. A method in a digital computing device comprising at least one processor for optimizing debt collection from a plurality of delinquent debtors, the method comprising:

for each delinquent debtor of the plurality of delinquent debtors, assigning debt collection resources in order to optimize an expected economic recovery from the plurality of delinquent debtors,

wherein said expected economic recovery is expressed by;

Σ

_i,j,k,pc(i,j,k,p)·

X(i,j,k,p)

where;

p is a delinquent debtor of the plurality of delinquent debtors;

c(i,j,k,p) is an expected collection amount;

i is the skill level of a particular debt collector;

j is a time period in a day;

k is a particular debt collection strategy chosen to be used on a delinquent debtor of the plurality of delinquent debtors,

where for each i, j, k, p, X(i,j,k,p) can take either the value 0 or 1 and is determined by optimally selecting i, j and k for all p'"'"'s.

8. An apparatus for optimizing debt collection from a plurality of delinquent debtors, comprising:

at least one digital computing device comprising at least one processor programmed to;

for each delinquent debtor of the plurality of delinquent debtors, assign debt collection resources in order to optimize an expected economic recovery from the plurality of delinquent debtors,

wherein said expected economic recovery is expressed by;

Σ

_i,j,k,pc(i,j,k,p)·

X(i,j,k,p)

where;

p is a delinquent debtor of the plurality of delinquent debtors;

c(i,j,k,p) is an expected collection amount;

i is the skill level of a particular debt collector;

j is a time period in a day;

k is a particular debt collection strategy chosen to be used on a delinquent debtor of the plurality of delinquent debtors,

where for each i, j, k, p, X(i,j,k,p) can take either the value 0 or 1 and is determined by optimally selecting i, j and k for all p'"'"'s.